The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index; none of the 118 sources its claims cite is checked for support yet.
Artificial Intelligence and Sustainable Decisions
Open accessAbstract
When addressing corporate sustainability challenges, artificial intelligence (AI) is a double-edged sword. AI can make significant progress on the most complicated environmental and social problems faced by humans. On the other hand, the efficiencies and innovations generated by AI may also bring new risks, such as automated bias and conflicts with human ethics. We argue that companies and governments should make collective efforts to address sustainability challenges and risks brought by AI. Accountable and sustainable AI can be achieved through a proactive regulatory framework supported by rigorous corporate policies and reports. Given the rapidly evolving nature of this technology, we propose a harmonised and risk-based regulatory approach that accommodates diverse AI solutions to achieve the common good. Ensuring an adequate level of technological neutrality and proportionality of the regulation is the key to mitigating the wide range of potential risks inherent to the use of AI. Instead of promoting sustainability, unregulated AI would be a threat since it would not be possible to effectively monitor its effects on the economy, society and environment. Such a suitable regulatory framework would not only create a consensus concerning the risks to avoid and how to do so but also include enforcement mechanisms to ensure a trustworthy and ethical use of AI in the boardroom. Once this objective is achieved, it will be possible to refer to this technological development as a common good in itself that constitutes an essential asset to human development.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
The paper argues AI is a double-edged sword for corporate sustainability: it can support CSR and SDG progress, but also creates bias, opacity, data monopolisation and ethical risks. It proposes a harmonised, risk-based regulatory framework with enforcement to ensure trustworthy, sustainable AI in the boardroom and treat AI as a common good.
Key findings
- AI can act as an enabler on 134 targets (79%) across all SDGs, but the paper identifies risks including data bias, lack of transparency/“black-box” systems, monopolisation of data and expertise, and conflicts with human ethics.
- Data-driven decision-making is associated with corporate benefits: companies using it are estimated to be, on average, 6% more profitable and 5% more productive than competitors.
- The regulatory landscape is fragmented: more than 84 initiatives describe AI principles and values, but they lack enforcement mechanisms; the paper proposes a harmonised, risk-based approach with low-risk flexible/voluntary codes, medium-to-high-risk standards with disclosure, and comprehensive regulation for high-risk systems.
- Sustainable AI should address the entire AI life cycle; training one natural language processing model can result in more than 600,000 lb of CO₂ emissions, so environmental costs should be justified by intended benefits.
Methods
- Doctrinal and policy analysis: the paper reviews CSR, corporate law, AI governance and regulatory instruments rather than conducting an empirical study.
- It draws on legal and policy sources such as the UK Companies Act 2006, EU AI regulation proposals, OECD materials, case law, and secondary literature to build a normative argument.
- No dataset, sample, population, or statistical test is used; the proposed risk-based framework is argued conceptually rather than tested.
Limitations
- The paper states it does “not have space to explore this in depth in this article” regarding the risk-based regulatory approach.
- It notes that AI lacks a universally accepted definition, the technology is rapidly evolving, there is no one-size-fits-all solution, and current regulatory approaches are fragmentary and inconsistent.
- Evident from the text: the article is normative and conceptual, with no empirical validation of the proposed framework and heavy reliance on secondary sources and illustrative examples.
Model-written summary. Check it against the paper before relying on it.
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Verification
Claims the paper makes
104 Not checked yet · 100 Own interpretation · 25 No basis given
In the paper
“In a corporate setting, AI can be applied to advance the effectiveness and efficiency of corporate social responsibility (CSR) programmes.3”
§ Artificial Intelligence and Sustainable Decisions > 1 Introduction
What the sources say
- Not checked yetcites Naqvi (2021)
plainconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“Poor data quality is 'enemy number one' to the use of ML. 74”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites Redman (2018)
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“When properly fed with adequate and high-quality big data, AI can help board members to unveil hidden insights and valuable knowledge, resulting in an improvement of the efficacy and quality of the decision-making processes.86”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [86]
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None of the sources cited for this claim have been checked yet.
In the paper
“Studies have shown that integrating sustainability aspects in the organisation is beneficial in terms of reputation, 47 productivity 48 and access to financial resources.49”
§ Artificial Intelligence and Sustainable Decisions > 2.2 CSR and Sustainable Decisions
What the sources say
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“Ethical and legitimate application of data can provide companies with valuable evidence and options that enable them to make more informed decisions and obtain a competitive 'data advantage' over rivals.76”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites [76] source
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In the paper
“The increasing availability of big data, together with the technologies to collect and process the data in real-time, can revolutionise the senior management of organisations.79”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites [79]
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In the paper
“The possibility of harnessing the potential of AI-especially in the case of ML-crucially depends on the availability of high-quality big data.69”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites Sanchez-Graells (2020)
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In the paper
“Similarly, it can play an essential role in complex situations that require big data processing at speed 'beyond the cognitive capabilities of even the smartest human decision-makers'.96”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [96] source
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In the paper
“Instead of replacing human intelligence, AI improves it by providing certain information or advice that otherwise would be difficult to obtain.94”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [94]
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In the paper
“The use of AI would tackle problems such as 'choice overload' 97 or 'analysis paralysis', 98 where the excess of available information is overwhelming due to a large number of potential outcomes and the inherent risks and directors cannot give a swift response.99”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
hedgeddirect- Asserted: passes — The authors put it forward as true.
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In the paper
“When designing this system, the solution to an optimisation problem is not coded in advance but is derived from data analysis.”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites Armour and Eidenmüller (2020)
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Data is crucial to building a model of corporate governance that relies on AI.”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“The problem is that most directors do not have the necessary knowledge and skills in terms of sustainability to make a well-informed and diligent decision.52”
§ Artificial Intelligence and Sustainable Decisions > 2.2 CSR and Sustainable Decisions
What the sources say
- Not checked yetcites The Sustainability Board (2021)
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In the paper
“When there is a lack of information about alternative decisions and/or their consequences, AI can overcome this uncertainty with predictive analysis, for example, by generating new ideas through probability and data-driven statistical inference approaches.95”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [95] source
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In particular, AI can support corporations and boards in situations of uncertainty, complexity or equivocality.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plainconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“The first step in this direction was the creation, in 2014, of VITAL (Validating Investment Tool for Advancing Life Science), an ML programme capable of making investment recommendations.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [107]
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Third, monopolisation of data and expertise is another hazard for AI's application.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
plain- Asserted: passes — The authors put it forward as true.
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Second, a significant deficiency that compromises the correct performance of AI systems is the lack of transparency in the decision-making process.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
plaindirect- Asserted: passes — The authors put it forward as true.
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In addition, the opacity of these systems (so-called 'black-box' systems) makes the detection of bias and errors extremely difficult.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
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In the paper
“A good example of this dangerous trend is Microsoft's AI bot 'Tay', taken offline in 2016 after developing racist behaviour by learning from Twitter users' statements.117”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [117]
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In the paper
“Evidence has shown that AI can act as an enabler on 134 targets (79%) across all SDGs.135”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [135]
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“Deep Knowledge Ventures, a venture capital firm from Hong Kong, appointed VITAL as a member of the board with observer status 107 due to its ability to 'automate due diligence and use historical data-sets to uncover trends that are not immediately obvious to humans surveying top-line data'.108”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [107]
- Not checked yetcites [108]
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In the paper
“First, AI will encourage transparency, which is regarded as a core value and critical approach to enhance sustainability.140”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [140]
plaindirect- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Even though it is expected that AI will be more accessible to SMEs as its maturity level increases, if the situation remains as it is today, these companies will be in a second division due to the limitations on accessing data and expertise.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
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In the paper
“There is still much that is not understood about human brains and how to replicate their internal connections.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [109]
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In the paper
“According to McKinsey, big tech companies-such as Alibaba, Amazon and Google-are securing qualified talent to develop their AI strategy by buying startups and hiring many of the available experts in the market.126”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [126] source
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In the paper
“The problem is that the vast demand for AI-related jobs clashes with a shortage of highly qualified professionals.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [126] source
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As ML systems become more powerful, being capable of incorporating new algorithms and modifying the features of the programme autonomously, new biases could also be created.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
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In the paper
“On the other hand, data can also mirror the preconceptions and biases of their designers, who might want to favour their clients' interests or steer the decision in a particular direction.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
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In the paper
“AI can also measure disclosure against standards that may be legally required nationally and internationally to ensure compliance with regulations or voluntary standards.141”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [141]
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In the paper
“Strubell has estimated that training one model of natural language processing can result in more than 600,000 lb of CO 2 emissions.137”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [137] source
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In the paper
“Until then, the concept of general human-level intelligence (also known as general AI) remains in the realm of science fiction.109”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [109]
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In the paper
“The imbalances in market power concerning the access and use of data have been identified by the European Commission as one of the main issues that prevent the European Union from realising its potential in the data economy.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [124] source
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In the paper
“The training and development of algorithms generate a substantial portion of greenhouse gas emissions.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [137] source
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In the paper
“First, one of the most often recognised hazards is the one brought by data bias.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [111]
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In the paper
“Finally, the third problem concerns the lack of enforcement mechanisms.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
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In the paper
“In addition, the use of AI can involve conflicts of interest that show the partial nature of algorithms. 147”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [147]
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The first problem, as mentioned above, is the uncertainty derived from the existence of numerous bodies of ethical principles with different approaches.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“Otherwise, the oversight policy 'is likely to be ineffective at best and counterproductive at worst'.150”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [150] source
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In the paper
“Meanwhile, globalisation has further increased the complexity of the legal environment by exposing corporations to international law and the laws of foreign nations.163”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
What the sources say
- Not checked yetcites [163]
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“Since 2018, when announcing the strategy for artificial intelligence for Europe, the European Commission has taken a clear position in favour of regulating AI.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
What the sources say
- Not checked yetcites European Commission (2018)
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In the paper
“Fourth, AI, which uses big data to run algorithms, can provide boards with opportunities to enhance their adaptive capabilities and shape their ability to address environmental changes rapidly.144”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [144] source
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“A wave of new AI tools, designed for functions such as document processing or responding to shareholders' or stakeholders' queries, will enhance the efficiency of boards' decision-making processes.145”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [145] source
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“The second problem, and probably one of the main reasons why there is no harmonised regulation yet, is the vast influence of the private sector.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
What the sources say
- Not matchedcites Jobin et al. (2019); Benkler (2019), p 161
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked yetcites Wagner (2018), pp 84-89 source
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In the paper
“The non-binding character of the existing bodies of principles that aim to discipline AI design and deployment means that, in practice, deviating from the ethical guidelines has no consequences for companies beyond reputational losses in case of misconduct or abuse.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
What the sources say
- Not checked yetcites Hagendorff (2019), pp 99-100 source
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“The first problem, as mentioned above, is the uncertainty derived from the existence of numerous bodies of ethical principles with different approaches.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
What the sources say
- Not checked yetcites [160]
- Not checked yetcites [161]
- Not checked yetcites [162]
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The good intentions written down on paper have no actual effectiveness in practice.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“At the same time, the European Parliament and the European Council have repeatedly demanded legislative action to ensure that both benefits and risks of AI are adequately addressed and to facilitate the enforcement of rules.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
What the sources say
- Not checked yetcites Council of the European Union (2020)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Instead of providing certainty to designers, users and even courts in case of disputes about AI-based decisions, the high number of approaches and proposals creates the opposite effect.”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The current scenario is characterised by the existence of fragmentary and inconsistent approaches to AI regulation.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The problem, however, is that we cannot pretend to regulate such a complex and immature technology with a fragmentary regulatory context.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“This approach is extensively used in aspects as diverse as the environment, finance, food, and legal services.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
What the sources say
- Not checked yetcites [178]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Furthermore, to ensure consistency, avoid duplication and minimise additional burdens, the regulatory framework will be integrated into the existing sectoral safety legislation.187”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
What the sources say
- Not checked yetcites [187]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 149
- It may state two separate claims as one. 79
- The quote only partly states this claim. 1
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“AI can make significant progress on the most complicated environmental and social problems faced by humans.”
- Also stated in: § 6 Conclusion · plain
“AI can make significant progress on the most complicated environmental and social problems faced by humans.”
§ Artificial Intelligence and Sustainable Decisions > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Also stated in: § 6 Conclusion · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“On the other hand, the efficiencies and innovations generated by AI may also bring new risks, such as automated bias and conflicts with human ethics.”
§ Artificial Intelligence and Sustainable Decisions > Abstract
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Although AI applications for sustainability are at their early stage, this trend is already starting to impact corporate sustainability in the application of AI to achieve Sustainable Development Goals (SDG) such as CO 2 emissions reductions, or ML applications to improve horticultural products.4”
§ Artificial Intelligence and Sustainable Decisions > 1 Introduction
What the sources say
- Not checked yetcites Riffle (2017)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As for the second branch, AI and big data will also help companies adopt ideal corporate governance principles, such as accountability, transparency and appropriate cooperation with stakeholders.”
§ Artificial Intelligence and Sustainable Decisions > 1 Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, Al will help establish management systems that effectively mitigate CSR risks so as to achieve economic and social benefits based on big data.”
§ Artificial Intelligence and Sustainable Decisions > 1 Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“The lack of a legal system regarding the application and design of AI may lead to the rise of private standardisation, as voluntary adjustment enables the steady establishment of the future legal framework.8”
§ Artificial Intelligence and Sustainable Decisions > 1 Introduction
What the sources say
- Not checked yetcites Darnault et al. (2019)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“CSR has been recognised and promoted through company law approaches and corporate governance mechanisms, mainly executed through information discourse and directors' duties, as a vehicle for incorporating social and environmental concerns into the business decision-making process.17”
§ Artificial Intelligence and Sustainable Decisions > 2.1 CSR and Corporate Law
What the sources say
- Not checked yetcites Gill (2008)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We believe that AI can change the corporate law and CSR framework, moving towards a more sustainable model of corporate governance.”
§ Artificial Intelligence and Sustainable Decisions > 1 Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“AI also generates adverse effects, such as infringing on privacy and bringing additional algorithmic bias.”
§ Artificial Intelligence and Sustainable Decisions > 1 Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Instead of promoting sustainability, unregulated AI would be a threat since it would not be possible to effectively monitor its effects on the economy, society and environment.”
§ Artificial Intelligence and Sustainable Decisions > Abstract
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“Social, environmental and human rights issues are core elements for sustainable corporate operations.16”
§ Artificial Intelligence and Sustainable Decisions > 2.1 CSR and Corporate Law
What the sources say
- Not checked yetcites McBarnet (2007)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this role, it will support decision-making in more complex issues by-for instance-asking and answering the right questions, identifying opportunities, detecting irregularities and mitigating risks.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“This approach focuses on the availability, selection and analysis of data, which has become the most valuable asset for companies.92”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [92]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“AI can help directors navigate options, correct error-prone humans, and comment on proposed strategies at senior-level meetings.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“It contributes to anticipating future needs and risks, predicting better solutions, making more efficient use of resources and increasing profits, as well as evaluating companies' performance and ensuring continuous improvement.87”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [87] source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“AI will assist companies in identifying a new paradigm or pattern of thinking for formulating CSR policies and implementing CSR, particularly in terms of emphasis on creativity.”
§ Artificial Intelligence and Sustainable Decisions > 2.1 CSR and Corporate Law
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“This model is already working on the board of the software company Salesforce, which relies on a robot called Einstein to improve corporate plans and decision-making in general.93”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [93]
plaindirectSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Relevant technical and analytic expertise will soon become essential for board members.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Big data provides the opportunity to make better decisions, i.e., well-informed and based on trustworthy information, and bypass possible gaps concerning knowledge of the market or other factors that are decisive for the success of the action.”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“Once the data extracted from various sources has been stored, it will be analysed using algorithms to find correlations and construct an optimal predictive model.71”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites Shrestha et al. (2019) source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By putting together the information and possible lines of action, the company will reach the optimal solution in each case.”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In particular, the success of applying AI and ML to CSR-oriented challenges relies on compliance with hard laws, soft laws, guidance and standardisation.”
§ Artificial Intelligence and Sustainable Decisions > 3 AI and Corporate Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In a scenario of uncertainty, big data can be used to discard lines of action that a priori seemed to be feasible and/or avoid incorrect or unnecessarily risky decisions.”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Companies' efforts in this direction will positively impact the value of the brand and corporate financial performance.”
§ Artificial Intelligence and Sustainable Decisions > 2.2 CSR and Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“What is clear, though, is that AI applications need to be fed with large volumes of data (big data) to perform the stipulated functions or achieve specific goals.”
§ Artificial Intelligence and Sustainable Decisions > University of Washington (2006).
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“However, SMEs can also use this mechanism to understand their customers better and improve revenues.77”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites [77] source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The information extracted from data can be transformed into knowledge that will help individuals to make the correct movement at the right time.80”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites [80] source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The advantages brought by AI in analysing information quickly and suggesting lines of action for directors will be crucial for them to make smart decisions.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This role may allow directors to delegate time-consuming tasks such as analysing and monitoring information flows, enabling them to concentrate on strategic business decisions and operational management.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At the lowest level, AI may perform simple administrative tasks with very little autonomy or no autonomy, so the decision rights exclusively belong to human beings.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“In order to train the programme properly, historical data must be correct and meet high-quality standards.75”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites Redman (2018)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The conflict of interests that these decisions usually involve is limited to a minimum.”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the current intelligence age and cognitive era, AI has enormous potential to change the nature of corporate governance practices and radically improve CSR practice by suggesting options, solving complex problems in an informed manner, or taking proper actions to achieve specific corporate goals.”
§ Artificial Intelligence and Sustainable Decisions > 3 AI and Corporate Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“In terms of corporate decision-making, the primary duty of the board of directors is to make strategic decisions that shape the company's general direction.78”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites [78] source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The reason is that this technology uses historical data to develop predictive models and new data to make future decisions.”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“AI is essential for establishing high-quality data architecture.”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It may recommend particular courses of action by taking into account the outcome information.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“These companies will be able to obtain better resources, better employees and better opportunities.50”
§ Artificial Intelligence and Sustainable Decisions > 2.2 CSR and Sustainable Decisions
What the sources say
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“It is estimated that companies that use data-driving decision-making are, on average, 6% more profitable and 5% more productive than their competitors.84”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites [84] source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“This 'knowledge gap' prevents them from posing the right questions and, consequently, obtaining the most accurate information-in retrospective and prospective terms-to deal with the complex trade-offs and dilemmas inherent to this type of decision.53”
§ Artificial Intelligence and Sustainable Decisions > 2.2 CSR and Sustainable Decisions
What the sources say
- Not checked yetcites Jorgensen (2021)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The supply of relevant data samples in real-time will result in better knowledge, better predictions and ultimately better decisions.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Since data is the fuel of AI systems and determines its outcomes, we will claim that the correct performance of this technology is subjected to the existence of high-quality data architecture.”
§ Artificial Intelligence and Sustainable Decisions > 3 AI and Corporate Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The range of functions that AI can effectively perform will depend on the level of maturity of these disruptive technologies.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This precondition contributes to smart and well-informed decisions and mitigates some of the hazards that might arise when using digital technologies in the boardroom.”
§ Artificial Intelligence and Sustainable Decisions > 3 AI and Corporate Decisions
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
In the paper
“However, AI can also take autonomous decisions, become a member of the board, or even replace board directors.88”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [88] source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The current development of ML requires human intervention to provide input information and interpret the outputs.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At the same time, technologies such as AI, including the application of big data, ML and robotics, will play a key role in longterm enhancement to society and achieving the common good.”
§ Artificial Intelligence and Sustainable Decisions > 2.1 CSR and Corporate Law
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By relying on data, metrics and statistics, directors can gather all relevant information to align strategic business decisions with their goals and objectives.”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Advanced AI that simulates a human brain will facilitate technological innovations that empower real-time big data collection and data-informed reporting, which are new means for stakeholder communication to help with innovative CSR.”
§ Artificial Intelligence and Sustainable Decisions > 2.1 CSR and Corporate Law
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“Companies that adopt data-driven decisions are in a solid position to enhance their visibility and reach a high level of corporate performance.83”
§ Artificial Intelligence and Sustainable Decisions > 3.2 Big Data As an Enabler of AI
What the sources say
- Not checked yetcites [83]
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Otherwise, they will be at risk of violating the duty of care and open themselves to litigation.54”
§ Artificial Intelligence and Sustainable Decisions > 2.2 CSR and Sustainable Decisions
What the sources say
- Not checked yetcites Hinks (2020)
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“With AI in corporate governance, board decisions can be based on analysis of corporate patterns and industry trends rather than on gut feelings.”
§ Artificial Intelligence and Sustainable Decisions > 3 AI and Corporate Decisions
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The implementation of AI solutions usually demands significant financial investments that are not affordable for every company, as it involves creating an adequate data infrastructure and the acquisition, or even development, of specific technology.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“For example, Section 155(1) of the UK Companies Act 2006 provides that a company must have at least one natural director, which makes it difficult for the AI to be appointed as the only board member.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [103]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“On the other hand, the relevant knowledge extracted from data leads to a competition to create powerful and innovative AI solutions.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“It is still plausible that in the medium term AI will assume more managerial tasks and make routine decisions on behalf of the company.106”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [106]
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Bearing in mind that the use of these technologies is in companies' best interest, the board might be falling short in meeting its duty of care if, considering a case's specific circumstances, it would be reasonable to implement them to improve directors' actions.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
- Rests on an assumption: The use of AI technologies is in companies' best interest.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Supported by big data and complemented by directors' supervision, AI will be able to contribute to data-driven decisions in directors' business judgement and strategic management policies to help promote sustainability.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Rests on an assumption: Implementing AI-based solutions has the potential for a win-win across business and society.
In the paper
“A consensus is that effectively embracing AI and other advanced technologies will require cooperation from multiple stakeholders, especially directors and the public sector.133”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [133] source
boostedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The reason is that data-driven technologies, such as AI, are inherently past-oriented and can reproduce and reinforce the patterns of inequality and discrimination that exist in societies.112”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [112]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although algorithms can learn on their own, humans still have to decide how they are deployed and integrated into the decision-making process.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“On the contrary, data reflects the existing social and cultural biases and can even perpetuate them, leading to discriminatory or unethical decisions.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [112]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Smart algorithms can analyse variables and relationships extracted from big data, but the way it occurs is not always clear for users and even programme developers.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
In the paper
“It would contribute to setting the 'game rules' and ensuring that AI systems are lawful, ethical and robust, i.e., comply with the existing law and regulations, meet a set of ethical standards, and are capable of avoiding unintended consequences.130”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [130]
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: The ethical and legal risks inherent to the use of AI and the lack of clear responses to address them create uncertainty and even some fear in using this technology in the heart of the company.
In the paper
“Accordingly, bias will appear when the decision-maker considers irrelevant consideration or fails to consider relevant consideration.113”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [113]
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The problem, however, is that an uncoordinated approach may result in conflicting obligations and over-regulation.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: The ethical and legal risks inherent to the use of AI and the lack of clear responses to address them create uncertainty and even some fear in using this technology in the heart of the company.
In the paper
“AI driven by data science for social good will enable AI to address societal challenges and use AI methods to tackle unsolved societal challenges in a measurable manner.138”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [138] source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“This process, however, requires a deep knowledge of computing science since it focuses on documentation intelligence sense-making and the review and validation of the logic details. 123”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [123]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“This market power might allow large players to 'set the rules on the platform and unilaterally impose conditions for access and use of data or, indeed, allow leveraging of such”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [125]
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“In other words, companies and other stakeholders could rely upon some basic safeguards when using or being affected by these systems.131”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [131] source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: The ethical and legal risks inherent to the use of AI and the lack of clear responses to address them create uncertainty and even some fear in using this technology in the heart of the company.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A fragmentary approach is likely to have a chilling effect on the different actors and discourage companies from digitalising the decision-making process, given the divergent paths to liability and other legal requirements.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
- Rests on an assumption: Many companies, notably tech companies, operate at an international level and usually have to comply with the rules of various legal systems.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At the highest level, AI will own decision rights due to human trust and delegation.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“It is becoming increasingly decisive for boards to have the expertise to engage in adequate oversight of data governance,”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [103]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Although it is an impressive advance, the truth is that its role, far from being autonomous, is limited to providing advice and supporting human directors' decisions.”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This is achievable since basic algorithms can be programmed to drive AI towards more ethical and sustainable corporate actions.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Generally, there is agreement amongst stakeholders on the need to build trust and design a regulatory framework grounded on sustainable development and respect for human rights.129”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [129] source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“As with any new technology, the deployment of AI can entail both opportunities and risks.110”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [110] source
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“It will proactively and autonomously evaluate options and make business judgements without human input by analysing information from the actual business environment and perceiving patterns in data.104”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [104]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The difficulty of explaining why a specific decision or solution has been adopted may conflict with the duty to act on an informed basis and motivate board decisions, 118 resulting in legal disputes inside the company or with third parties.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [118]
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“which is regarded as a core value and critical approach to enhance sustainability.140”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [140]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“Although data-driven decisions are expected to be objective and to overcome human subjectivity, the reality shows that this assumption is a myth.111”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
What the sources say
- Not checked yetcites [111]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If data samples are not sufficiently representative of the different populations and social groups, then the system will be flawed from the outset and the results will be necessarily biased.”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Thus, it can be claimed that ML algorithms are autonomous 'only in the sense that they can run continuously and have the potential to translate their outputs automatically into regulatory actions'.105”
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
What the sources say
- Not checked yetcites [105] source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Second, AI will be able to recommend sustainable policies and make sustainable decisions.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
- Rests on an assumption: Implementing AI-based solutions has the potential for a win-win across business and society.
None of the sources cited for this claim have been checked yet.
In the paper
“it is a promising instrument to increase human well-being, bringing progress and innovation, and achieve sustainable goals that benefit society as a whole.128”
§ Artificial Intelligence and Sustainable Decisions > 3.4 Challenges of Using AI in the Boardroom: Risks, Uncertainty and Lack of Regulation
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, it also comes with the responsibility to monitor data collection, data quality, and how data impacts social justice, addresses vulnerabilities and builds resilience.”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
In the paper
“In line with the willingness to include social and environmental considerations in corporate decisions, some of these principles focus on sustainability issues such as respecting human rights, including social purposes, and the significance of shared benefits and prosperity to achieve 'common good' through AI. 156”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
What the sources say
- Not checked yetcites [156] source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Along with the data dependency and bias problems mentioned before, AI-enabled technology can conflict with human ethics and exacerbate inequalities in society.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Complementing human directors' capacities, AI can understand companies' ability to generate positive outcomes by organising ethical goals using a smart system.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“In February 2020, the Commission launched a White Paper on AI entitled 'A European approach to excellence and trust', aiming to build a coordinated European plan for a trustworthy AI environment.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
What the sources say
- Not checked yetcites European Commission (2020d)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The algorithms from this automated process will identify the assets that meet the thresholds and constantly compose the portfolio return to give the company and director the best possible portfolio options.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, the expertise and professionalisation of regulators is as important as the regulatory instrument to be implemented.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Due to the various forms of manifestation of CSR-related performance, the regulations governing CSR also come in multiple shapes.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A first step to elaborate a regulatory framework is ensuring that policy-makers have a sufficient understanding of the risks and challenges of AI.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“On the one hand, this scenario creates uncertainty among directors and might even discourage them from digitalising some tasks in the boardroom due to the unpredictable legal consequences.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one. The quote only partly states this claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It can also make recommendations on integrating the CSR strategy and policy with the overall business strategy.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Boards of directors could use preventive measures designed by AI to formulate the most suitable CSR plan and strategic policies for the long-term interests of companies.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: Implementing AI-based solutions has the potential for a win-win across business and society.
In the paper
“As the societal use of and dependency on AI and ML increases, it is crucial to identify what needs exist from a regulatory perspective.158”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
What the sources say
- Not checked yetcites [158] source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
“There is consensus among different actors about laying down a set of rules to discipline this new reality, even though divergences about how to do it and who should do it also exist.154”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
What the sources say
- Not checked yetcites [154]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Over the last few years, numerous national and international organisations have developed a range of ethical guidelines related to AI.”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
What the sources say
- Not checked yetcites [152] source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“One of the pioneers in this field was the Future of Life Institute, which developed 23 'Asilomar AI Principles' in productivity, ethics and security in 2017.155”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
What the sources say
- Not checked yetcites [155]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Taking the legal approach as a starting point, we can identify three issues that demonstrate the insufficiency of the current model and the urgency to take action.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“On the other hand, it provides a low standard of protection to stakeholders and society since their privacy, fundamental rights and well-being can be in danger due to AI.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Local government bodies issue public regulations that are regional, national or supra-national, 160 based on delegated state, government or international powers 161 founded on each country's membership.162”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
What the sources say
- Not checked yetcites [160]
- Not checked yetcites [161]
- Not checked yetcites [162]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Third, AI can also play a preventive role by providing a barrier to corporate damage to society and the environment.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Rests on an assumption: Implementing AI-based solutions has the potential for a win-win across business and society.
In the paper
“manage both the risk of an asset from a financial performance perspective and the risk from the ESG perspective.143”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [143] source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Besides, an excessively detailed framework would make it unsuitable for future AI developments.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Progressive advocates who are engaged in promoting more sustainable businesses, more environmentally friendly companies and companies focused on human rights will also drive corporations to embrace more socially responsible ethical codes and guidelines for conduct, the adoption of which is mainly voluntarily.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“They are drafted and enforced by regulatory bodies at different levels.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Besides, the design of high-level guidelines could project an image of false ethics to potential customers and investors or even convince society that there is no need for binding regulation or new legislation to tackle the technological risks of AI.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
What the sources say
- Not checked yetcites Wagner (2018), pp 84-89 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Several expert committees have been created to this end, such as the High-Level Expert Group on Artificial Intelligence appointed by the European Commission, the Expert Group on AI in Society of the OECD, and the Select Committee on Artificial Intelligence of the UK's House of Lords.153”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
What the sources say
- Not checked yetcites [153] source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this context, there is a need for regulation to ensure a responsible design and deployment of AI-based solutions, on the one hand, and due consideration of public values and interests, on the other.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This role can also contribute to automating the process of planning the ESG investment strategy and some complementary tasks such as identification of stakeholder network, assessment of variables, and measurements following the strategy clarification part.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“To develop the said trust ecosystem by creating a legal framework, the European Commission approved a proposal to lay down harmonised rules on AI on 24 April 2021.”
§ Artificial Intelligence and Sustainable Decisions > Council of the European Union (2020).
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A uniform approach would ensure that the use of AI does not violate the interests and rights of the citizens and that compliance with a certain standard of ethical behaviour is real, not merely a marketing strategy.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Algorithms could be trained to predict the effectiveness of sustainable-oriented corporate policies with an impressive level of precision, helping in the formulation and optimisation of the CSR programme to achieve distributive justice.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Creating a policy framework that contributes to a reasonable standard of transparency and increases trust in AI decision-making is essential.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Preventive measures could be achieved through smart technology that identifies discrimination, fraud, or conflicts of interest, with AI playing a vital role in providing more predictive and preventive measures to mitigate social and environmental risks.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
In the paper
“There is no unanimity on the principles or guidelines that should govern AI and, even when the different initiatives agree on one or more principles, there are considerable differences in how to interpret and implement them.159”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
What the sources say
- Not checked yetcites [159]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this regard, it can be claimed that the type of regulation should efficiently achieve the mentioned objectives but without dissuading software developers from innovating and investing.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
In the paper
“AI continues to 'gain in complexity and sophistication', 151 offering tremendous benefits in terms of efficiency and innovation.”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
What the sources say
- Not checked yetcites [151] source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Using AI responsibly and ethically is a crucial component of 'global commons' and a prerequisite for the 'common good' in the global business environment.”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Cultivating trust with stakeholders, particularly indirect stakeholders such as extraterritorial local communities, requires regulating data quality and data governance, including the processes for gathering, cooperating and scrutinising data through the regulatory framework to be applied to assist companies more effectively.”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Rests on an assumption: Big data will help the board of directors induce predictive CSR policy that fits the stakeholder network and stakeholder priorities for companies' business model, enabling both informed and supportive predictions and improving trust with constituents.
In the paper
“As Truby has pointed out, 'any irresponsible development of AI software leaves the utility of the technology exposed to the immense risk of negative consequences', and it may entail damage for humans and sustainable development.149”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [149]
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
In the paper
“Given that AI systems usually consider the needs and values of the regions in which they are designed, it might benefit developed countries while discriminating against developing countries and minorities.146”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [146]
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“To this effect, the development of sustainability screens or indexes could reduce the burden of understanding data analytics by facilitating the generation of synthetic data visualisations.142”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
What the sources say
- Not checked yetcites [142] source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Hence the need to reach a reasonable level of harmonisation in this area by establishing a set of minimum requirements that AI should meet or a system of red flags as to principles that under no circumstances should be violated.”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Over-regulation of AI may involve intolerable bureaucratic requirements and harm innovation.”
§ Artificial Intelligence and Sustainable Decisions > 4 AI's Contribution Towards More Sustainable Decisions
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At the most fundamental level, government regulations are generally formal and binding in law, or some recommendations have guiding effects but no legal standing.”
§ Artificial Intelligence and Sustainable Decisions > 5.1 The Need for Harmonised AI Regulation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It is particularly stimulating to observe that the shared benefits and achieving the 'common good' through AI are suggested as principles for designing, programming, utilising and distributing AI.”
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“While the First Industrial Revolution used water and steam for production, the Second electric power and the Third information and technology, AI now leads the Fourth Industrial Revolution to a fusion of technologies that is likely to redefine the most valuable human skills.197”
§ Artificial Intelligence and Sustainable Decisions > 5.3 The Ultimate Goal: AI for the Common Good
What the sources say
- Not checked yetcites [197]
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Given the adverse effects that the use of AI can entail for stakeholders, workers and other individuals, the proposed regulatory framework aims to balance the different objectives and interests of the parties involved and to avoid potential violations of fundamental rights.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Given that it is an essential asset for the progress of society, it should observe shared ethical ideals and convergent values.”
§ Artificial Intelligence and Sustainable Decisions > 5.3 The Ultimate Goal: AI for the Common Good
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“As stated in the explanatory memorandum, those codes may also include commitments related to environmental sustainability, accessibility for persons with disabilities, stakeholders' participation in the design and development of AI systems, and diversity of development teams.191”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
What the sources say
- Not checked yetcites [191]
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There is a long way to go in building harmonised regulation on AI.”
§ Artificial Intelligence and Sustainable Decisions > Council of the European Union (2020).
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It can contribute to the realisation of CSR goals by enabling boards of directors to analyse vast amounts of data in real-time and predict what is the best plan of action.”
§ Artificial Intelligence and Sustainable Decisions > 6 Conclusion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In corporate governance, companies can benefit from the use of AI in different ways, obtaining important gains in terms of efficiency and enhancing the long-term interests of the corporation while taking into account the interests of shareholders and other stakeholders.”
§ Artificial Intelligence and Sustainable Decisions > 6 Conclusion
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In the UK, governmental bodies such as the UK's House of Lords Select Committee on AI and the All-Party Parliamentary Group on AI have been created to address the economic, social and ethical implications of developing and implementing artificial intelligence.”
§ Artificial Intelligence and Sustainable Decisions > Council of the European Union (2020).
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This 'de minimis' regulation would allow creating a uniform model to be applied to the different actors in the market while, at the same time, not hindering technological development and innovation.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Therefore, the higher the probability of causing harm, the more intense the regulator's intervention.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“This proposal is based on the concept of trustworthy AI developed by the above-mentioned High-Level Expert Group on AI.”
§ Artificial Intelligence and Sustainable Decisions > Council of the European Union (2020).
What the sources say
- Not checked yetcites High-Level Expert Group on Artificial Intelligence (2019), p 4; see also Thiebes et al. (2021)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As claimed before, mitigating risks and achieving global AI for the common good will require international cooperation and present a unique governance opportunity for regulators.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The proposed approach relies on the observance of the principle of proportionality since it balances regulatory intervention against the burden it creates for companies, especially SMEs.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In this regard, AI providers will have to provide meaningful information about their systems and the conformity assessments carried out on those systems.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Instead of promoting sustainability, unregulated AI would be a threat to it because it would not be possible to effectively monitor its effects on the economy, society and the environment.”
§ Artificial Intelligence and Sustainable Decisions > 6 Conclusion
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Rests on an assumption: It would not be possible to effectively monitor AI's effects on the economy, society and the environment if AI is unregulated.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, the initiative of the European Commission-if successfully implemented-will lead this journey and might stimulate the development of new proposals.”
§ Artificial Intelligence and Sustainable Decisions > Council of the European Union (2020).
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The proposal imposes regulatory burdens only when an AI system is likely to pose high risks to fundamental rights and safety.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“risk-based regulation 'facilitates robust governance, contributing to efficient and effective use of regulatory resources and delivering interventions in proportion to risk'.182”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
What the sources say
- Not checked yetcites [182]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The European Commission suggests establishing a 'European Artificial Intelligence Board' to coordinate and assist the competent national authorities in charge of ensuring the application and implementation of the European Regulation.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Ensuring that corporate decisions are well-informed and based on trustworthy information will optimise the decision-making process and increase the success rate of sustainability policies.”
§ Artificial Intelligence and Sustainable Decisions > 6 Conclusion
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“AI encompasses various technologies with different features and potential risks, and there is no one-size-fits-all solution.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
In the paper
“As stated in the explanatory memorandum, the proposal is based on EU values and fundamental rights and aims to give people and other users the confidence to embrace AI-based solutions while encouraging businesses to develop them.”
§ Artificial Intelligence and Sustainable Decisions > Council of the European Union (2020).
What the sources say
- Not checked yetcites European Commission (2021), p 1
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“At the same time, providers of non-high-risk AI systems are encouraged to create codes of conduct on a voluntary basis to apply the mandatory requirements for high-risk schemes.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“On the other hand, the efficiencies and innovations generated by AI may also bring new risks, such as automated bias and conflicts with human ethics.”
§ Artificial Intelligence and Sustainable Decisions > 6 Conclusion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The specific measures to regulate AI systems will be different depending on the risk of causing harmful and unwanted consequences.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Those that create an unacceptable risk, for example, by violating fundamental rights, will be prohibited.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although it imposes some restrictions on the freedom to conduct business, this consequence is consistent with the objective to ensure that only safe products find their way to the market, and it is justified by overriding reasons of public interest.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The combination of both mechanisms would facilitate early intervention and avoidance of foreseeable potential harms.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When it comes to corporate sustainability challenges, it has been found that artificial intelligence is a double-edged sword.”
§ Artificial Intelligence and Sustainable Decisions > 6 Conclusion
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“The full potential of AI will only be realised if human beings and communities have confidence in it.”
§ Artificial Intelligence and Sustainable Decisions > Council of the European Union (2020).
What the sources say
- Not checked yetcites High-Level Expert Group on Artificial Intelligence (2019), p 4; see also Thiebes et al. (2021)
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Following this reasoning, it can be argued that AI not only contributes to achieving social and environmental goals but can also be considered as a 'common good' itself since its use entails significant benefits for society.”
§ Artificial Intelligence and Sustainable Decisions > 5.3 The Ultimate Goal: AI for the Common Good
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“It means that each Member State has to designate a national supervisory authority among the already existing structures.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“This ex-post enforcement will complement companies' ex-ante conformity assessment through internal checks and auditing by third parties.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The harmonisation of law may help regulators define their approach to AI's risk clearly and consistently.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“At the same time, it aims to establish a set of transparent, predictable and proportionate obligations to ensure legal certainty and effective enforcement of existing law on fundamental rights and safety requirements applicable to AI systems.”
§ Artificial Intelligence and Sustainable Decisions > Council of the European Union (2020).
What the sources say
- Not checked yetcites European Commission (2021), p 3
plaindirect- Asserted: fails — The authors may not put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The authors may not put it forward as true. The paper’s conclusions may not depend on it.
In the paper
“It distinguishes between AI systems that create an unacceptable risk, a high risk, and a low or minimal risk.188”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
What the sources say
- Not checked yetcites [188]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“In this vein, the UK Parliament has suggested that the first overarching principle for an AI Code is that AI 'should be developed for the common good and benefit of humanity'.196”
§ Artificial Intelligence and Sustainable Decisions > 5.3 The Ultimate Goal: AI for the Common Good
What the sources say
- Not checked yetcites [196]
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, all these regulatory efforts would be wasted in the absence of effective enforcement mechanisms.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The AI systems that generate a high risk or are likely to do so in the future are listed in Annex III, based on the area in which they will be applied and their specific purpose.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Such a suitable regulatory framework would not only create a consensus concerning the risks to avoid and how to do so, but also include enforcement mechanisms to ensure a trustworthy and ethical use of AI in the boardroom.”
§ Artificial Intelligence and Sustainable Decisions > 6 Conclusion
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
In the paper
“However, we believe this approach will help companies develop AI in a safe and beneficial direction, particularly suitable for regulators with a mission to address risks from AI-associated accidents (safety) or misuse of AI (security).”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
What the sources say
- Not checked yetcites [181]
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Besides, the technology evolves by leaps and bounds, and the traditional regulatory instruments are not suitable for immediate response to the new reality.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“This model has recently been endorsed by the European Commission in its proposal for a Regulation for AI.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“As established in the proposal, AI providers will be obliged to inform national competent authorities about serious incidents or malfunctioning that constitute a breach of fundamental rights obligations as soon as they become aware of them, as well as any recalls or withdrawals of AI systems from the market.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“For AI systems that can result in a high risk for the health and safety or fundamental rights of natural persons, the proposal includes specific rules that should be observed as a condition to operate on the European market-such as requirements of high-quality data, documentation and traceability, transparency, human oversight, accuracy and robustness-and an ex-ante conformity assessment.189”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
What the sources say
- Not checked yetcites [189]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The advantages of risk-based regulation will accelerate companies' commitment to incorporating rigorous analysis of potential risks into corporate decisions.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“In order to protect privacy, personal data and other sensitive information, it is closely related to the Open Data Directive, 183 the Proposal for a Regulation on European Data Governance 184 and the proposed Data Act, 185 and complements the General Data Protection Regulation 186 (GDPR) as well as legislation on consumer protection, non-discrimination and environmental protection.”
§ Artificial Intelligence and Sustainable Decisions > 5.2 Risk-based Regulatory Approach
What the sources say
- Not checked yetcites [183]
- Not checked yetcites [184]
- Not checked yetcites [185]
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
The use of AI technologies is in companies' best interest.
“Bearing in mind that the use of these technologies is in companies' best interest, the board might be falling short in meeting its duty of care if, considering a case's specific circumstances, it would be reasonable to implement them to improve directors' actions.”
The paper relies on this without support.
Currently, there is no regulation governing the data used to train algorithms.
“Currently, there is no regulation governing the data used to train algorithms, whereas its owners can easily manipulate data.”
The paper relies on this without support.
The ethical and legal risks inherent to the use of AI and the lack of clear responses to address them create uncertainty and even some fear in using this technology in the heart of the company.
“The ethical and legal risks inherent to the use of AI and the lack of clear responses to address them create uncertainty and even some fear in using this technology in the heart of the company.”
The paper relies on this without support.
The implementation of AI-based solutions in the boardroom depends on an atmosphere of trust and certainty.
“the implementation of AI-based solutions in the boardroom depends on an atmosphere of trust and certainty”
The paper relies on this without support.
Many companies, notably tech companies, operate at an international level and usually have to comply with the rules of various legal systems.
“many companies-notably tech companies-operate at an international level and usually have to comply with the rules of various legal systems.”
The paper relies on this without support.
The implications that stem from the relation between AI and sustainability have not been fully considered yet.
“The implications that stem from the relation between AI and sustainability have not been fully considered yet.”
The paper relies on this without support.
Implementing AI-based solutions has the potential for a win-win across business and society.
“implementing AI-based solutions has the potential for a win-win across business and society.”
The paper relies on this without support.
AI may support or replace humans in situations where technology is more likely to make a better and more informed decision, where decisions have to be made quickly, or where the process is complicated and requires a large amount of data that humans are unable to process.
“AI may also support or replace humans in situations where technology is more likely to make a better and more informed decision, where decisions have to be made quickly or where the process is complicated and requires a large amount of data that humans are simply unable to process.”
The paper relies on this without support.
AI can be programmed to act in a way that aligns with the organisation's core values.
“Finally, AI can be programmed to act in a way that aligns with the organisation's core values.”
The paper relies on this without support.
AI offers an opportunity for directors and companies to promote their CSR portfolio and manage the CSR programme in active collaboration with internal and external stakeholders informed by big data.
“AI offers a fantastic opportunity for directors and companies to promote their CSR portfolio and manage the CSR programme in active collaboration with internal and external stakeholders informed by big data.”
The paper relies on this without support.
Big data will help the board of directors induce predictive CSR policy that fits the stakeholder network and stakeholder priorities for companies' business model, enabling both informed and supportive predictions and improving trust with constituents.
“Big data will help the board of directors induce predictive CSR policy that fits the stakeholder network and stakeholder priorities for companies' business model, enabling both informed and supportive predictions and improving trust with constituents.”
The paper relies on this without support.
The current scenario is characterised by the existence of fragmentary and inconsistent approaches to AI regulation.
“The current scenario is characterised by the existence of fragmentary and inconsistent approaches.”
The paper relies on this without support.
Like other countries such as the US and the UK, the European Union has actively worked on a harmonised framework to regulate AI.
“Like other countries, such as the US and the UK, the European Union has actively worked on a harmonised framework to regulate AI.”
The paper relies on this without support.
The result of the European Union's efforts was a proposal for a regulation launched on 24 April 2021.
“As we will explain below, the result of such efforts was a proposal for a regulation launched on 24 April 2021.”
The paper relies on this without support.
AI is a complex and immature technology.
“The problem, however, is that we cannot pretend to regulate such a complex and immature technology with a fragmentary regulatory context.”
The paper relies on this without support.
There is no harmonised regulation for AI yet.
“The second problem, and probably one of the main reasons why there is no harmonised regulation yet, is the vast influence of the private sector.”
The paper relies on this without support.
It would not be possible to effectively monitor AI's effects on the economy, society and the environment if AI is unregulated.
“because it would not be possible to effectively monitor its effects on the economy, society and the environment”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“AI improves the efficiency of sustainable business model decision-making when deployed as a decision-support system that complements, rather than substitutes, human managerial judgment.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [54]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The legitimacy of AI-enabled decision-making in sustainable business models is positively associated with the transparency, explainability, and governance of AI systems.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [54]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“AI enhances decision effectiveness in sustainable business models when AI systems are explicitly aligned with environmental, social, and governance (ESG) objectives rather than purely economic performance metrics.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [54]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“AI contributes to sustainable business model innovation when conceptualized as a dynamic capability that enables continuous adaptation to environmental and social complexity.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [54]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Artificial Intelligence and Sustainable Decisions > 5 Regulating AI for the Common Good: The Need for a Harmonised and Risk-based Approach
“a proposal for a regulation launched on 24 April 2021.”
§ Artificial Intelligence and Sustainable Decisions > References
“Brussels, 21.4.2021 (COM(2021) 206 final)”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Artificial Intelligence and Sustainable Decisions > References
“Nikkei Asia, 8 September 2021.”
§ Artificial Intelligence and Sustainable Decisions > References
“Accessed 25 May 2021”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Artificial Intelligence and Sustainable Decisions > 1 Introduction
“Section 2 offers a critical analysis of AI and corporate decisions.”
§ Artificial Intelligence and Sustainable Decisions > 3 AI and Corporate Decisions
“## 3 AI and Corporate Decisions”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Artificial Intelligence and Sustainable Decisions > University of Washington (2006).
“Russell and Norvig (2020), pp 1-3.”
§ Artificial Intelligence and Sustainable Decisions > References
“Russell S, Norvig P (2021) Artificial intelligence: a modern approach, 4th edn.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Artificial Intelligence and Sustainable Decisions > 1 Introduction
“5 Vinuesa et al. (2020), p 233.”
§ Artificial Intelligence and Sustainable Decisions > References
“Vinuesa R, Azizpour H, Leite I, Balaam M, Dignum V, Domisch S, Felländer A, Daniela Langhans S, Teg- mark M, Fuso Nerini F (2020) The role of artificial intelligence in achieving the Sustainable Develop- ment Goals. Nat Commun 11:1-10”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Artificial Intelligence and Sustainable Decisions > 3.3 Using AI in the Boardroom
“Coglianese and Lehr (2017), p 1177.”
§ Artificial Intelligence and Sustainable Decisions > References
“Coglianese C, Lehr D (2017) Regulating by robot: administrative decision making in the machine-learn- ing era. Georgetown Law J 105:1147-1157”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Artificial Intelligence and Sustainable Decisions > 2.2 CSR and Sustainable Decisions
“Martins et al. (2021), p 296”
§ Artificial Intelligence and Sustainable Decisions > References
“Martins A, Gomes D, Branco M (2021) Managing corporate social and environmental disclosure: an accountability vs. impression management framework. Sustainability 13(1):1-15”
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Janković, S. D., & Curović, D. (2023) · Sustainability · doi:10.3390/su152115208 · Cited by 124
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Metadata
- Authors
- Zhao, J., & Gómez Fariñas, B.
- Affiliations
- Guangdong University Of Finances and Economics (CN)
- Corresponding author
- Zhao, Jingchen
- ORCID
- Zhao, Jingchen
- Venue
- European Business Organization Law Review
- Published
- 2022-11-28
- Volume
- 24
- Issue
- 1
- Pages
- 1-39
- ISSN
- 1566-7529 (ISSN-L)
- 1741-6205
- OpenAlex
- W4310118256
- Semantic Scholar
- 788fa6d21adf3933693b9e5618e216beafe94a41
- Cited by
- 197
- References
- 79
- Citations by year
- 2026: 49 · 2025: 79 · 2024: 58 · 2023: 11
- FWCI
- 42.93
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- European Business Organization Law Review (publishedVersion, cc-by)
- Nottingham Trent University's Institutional Repository (Nottingham Trent Repository) (acceptedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Physical Sciences › Environmental Science › Management, Monitoring, Policy and Law › Innovation, Sustainability, Human-Machine Systems
- Keywords
- artificial intelligence, corporate sustainability, AI regulation, risk-based regulation, algorithmic bias, ethical use of AI, corporate governance, regulatory harmonization, technological neutrality, proportionality, accountability, common good, environmental and social risks
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-08, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-08 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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