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Cited by 123Ethics and Social Impacts of AISustainable Supply Chain ManagementInnovation, Sustainability, Human-Machine Systems

Artificial intelligence in support of the circular economy: ethical considerations and a path forward

Open access
Roberts, Huw, Zhang, Joyce, Bariach, Ben, Cowls, Josh, Gilburt, Ben, Juneja, Prathm, Tsamados, Andreas, Ziosi, Marta +2 more·2024·AI & SOCIETY
DOI 10.1007/s00146-022-01596-8
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Abstract

The world’s current model for economic development is unsustainable. It encourages high levels of resource extraction, consumption, and waste that undermine positive environmental outcomes. Transitioning to a circular economy (CE) model of development has been proposed as a sustainable alternative. Artificial intelligence (AI) is a crucial enabler for CE. It can aid in designing robust and sustainable products, facilitate new circular business models, and support the broader infrastructures needed to scale circularity. However, to date, considerations of the ethical implications of using AI to achieve a transition to CE have been limited. This article addresses this gap. It outlines how AI is and can be used to transition towards CE, analyzes the ethical risks associated with using AI for this purpose, and supports some recommendations to policymakers and industry on how to minimise these risks.

AI snapshot

Written from the paper’s full text.

TL;DR

This article argues that AI is a crucial enabler of the circular economy (CE) but that its use for CE raises under-examined ethical risks around privacy, bias, inequality, and epistemological over-simplification. It proposes micro-, meso-, and macro-level policy recommendations to promote an ethical “AI4CE.”

Key findings

  • AI can support CE by helping design and maintain circular products (e.g., “Accelerated Metallurgy,” digital twins, Apple’s on-device ML for battery charging) and by facilitating circular businesses through dynamic pricing, AI-enabled sorting, and energy optimisation; Apple’s Daisy robot can “take apart up to 200 iPhone devices per hour,” and DeepMind’s data-centre cooling system reduced Google’s cooling energy bill by 40%.
  • The paper identifies four main ethical risk areas: data privacy (e.g., IoT-tracked shoes revealing geospatial data; smart meters, over 30% of UK homes/small businesses by 2020, enabling inferences about behaviour), algorithmic bias (e.g., Uber drivers in Boston “twice as likely to cancel an accepted ride” for African American-sounding names; SAT prep pricing where Asians were almost twice as likely to be offered higher prices), economic inequality/exclusion (McKinsey estimate: leading countries could capture 20–25% net AI benefits vs. 5–15% for Global South; UK internet use 99% among 16–44s vs. 54% among 75+), and epistemological risks (computing power to train state-of-the-art models rose over 300,000 times from 2012 to 2018; data centres could use 13% of world electricity by 2030 vs. 1% in 2010).
  • CE progress remains limited: only 8.6% of the world economy was circular in 2020, down from 9.1% in 2018; resource extraction has tripled globally over 50 years, with demand projected to require more than two planets’ worth of resources by 2030 and three by 2050; roughly one-third of food is wasted.
  • Recommendations include micro-level privacy-enhancing technologies and AI auditing, meso-level open source, reskilling, and inclusive design, and macro-level government research funding (e.g., UKRI’s £30 million CE research programme) plus guidance and standards.

Methods

  • Conceptual and normative ethical analysis, combined with a review of CE literature, AI use cases, policy documents, and secondary examples; no empirical sample, experiment, or primary data collection is reported.
  • The paper first outlines CE and its criticisms, then assesses how AI can aid CE, analyses ethical risks, and derives policy recommendations at micro, meso, and macro levels.
  • Analysis draws on cited academic, industry, and policy sources to illustrate benefits and harms rather than testing hypotheses statistically.

Limitations

  • The paper states that CE lacks an agreed definition, that its social outcomes are unclear, and that its theoretical robustness has been questioned; it also notes that AI auditing is nascent, PETs for IoT are immature, open source is limited by structural inequalities, and governance must adapt to evolving scientific knowledge.
  • Evident from the text: the analysis is conceptual and illustrative rather than a systematic empirical evaluation, and the proposed recommendations are not tested or validated.
  • Evident from the text: the discussion centres on AI and complementary digital technologies, with examples drawn largely from Global North contexts, so coverage of other regions and implementation contexts is limited.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1007/s00146-022-01596-8

Cites

71 of 71 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 52 cited sources checked · 0 supported · 0 flagged

  • Interpretationreasoning

    The use of AI for CE is not just a hypothetical consideration.

    “Hence, it is not just a hypothetical consideration.”
    Quote in the paperSubstantial claim
  • Interpretationreasoning

    AI can make precise inferences about individual behaviours, even through seemingly banal applications.

    “This example is indicative of how AI can make precise inferences about individual behaviours, even through seemingly banal applications.”
    Quote in the paperSubstantial claim
  • Interpretationcitation

    Matching algorithms can help connect buyers and sellers more effectively.

    “Likewise, matching algorithms can help connect buyers and sellers more effectively (Gailhofer et al. 2021).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Gailhofer et al. 2021

      Not checked in the free run.

  • Premisecitation

    Academics, businesses, and policymakers are increasingly interested in applying AI technologies for CE initiatives.

    “Second, there has been significant growth in the use of these technologies in recent years (The State of AI in 2021 2021), with academics, businesses, and policymakers increasingly interested in applying these technologies for CE initiatives (Ellen MacArthur Foundation and Google 2019).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Ellen MacArthur Foundation and Google 2019

      Not checked in the free run.

  • Interpretationcitation

    The transition towards circularity is still nascent.

    “These initiatives are promising, but the transition towards circularity is still nascent.”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. 28
  • May combine two claims. 18

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationreasoning

    Without AI, it would be extremely difficult to make sense of the data needed for CE and use them to aid in designing and maintaining products, supporting circular businesses, or achieving a high degree of circularity.

    “At the same time, without AI, it would be extremely difficult to make sense of these data and use them to aid in designing and maintaining products, supporting circular businesses, or achieving a high degree of circularity in the economy.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    AI can help design new materials to substitute unsustainable resources, such as harmful chemicals, enhancing durability and easing recycling.

    “Similarly, AI can help design new materials to substitute unsustainable resources, such as harmful chemicals.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Gailhofer et al. 2021

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    The unethical use of AI for CE presents several plausible risks, including privacy risks.

    “The unethical use of AI presents several plausible risks, as we detail in the remainder of this section.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Data collection and analysis for CE could exacerbate privacy risks.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    AI can aid in designing robust and sustainable products.

    “It can aid in designing robust and sustainable products, facilitate new circular business models, and support the broader infrastructures needed to scale circularity.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    AI can analyse data collected over a product's lifecycle to make real-time efficiency improvements or determine whether a returned product should be reused, remanufactured, or recycled.

    “More generally, AI can be used to analyse data collected over a product's lifecycle to either make real-time efficiency improvements or to determine whether a returned product should be reused, remanufactured, or recycled (Blunck et al. 2019).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Blunck et al. 2019

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The world's current model for economic development is unsustainable because it encourages high levels of resource extraction, consumption, and waste that undermine positive environmental outcomes.

    “The world's current model for economic development is unsustainable.It encourages high levels of resource extraction, consumption, and waste that undermine positive environmental outcomes.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Oberle et al. 2019

      Not checked in the free run.

    • cites Osborne 2006

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Only 8.6% of the world economy was circular in 2020, a decline from 9.1% in 2018.

    “Despite predictions that the circular economy will replace the linear economy by 2029 (Hippold 2019), a 2022 report showed that only 8.6% of the world economy was circular in 2020, which is, in fact, a decline from 2018, when 9.1% of the global economy was circular (de Wit and Haigh 2022) 6 .”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites de Wit and Haigh 2022

      Not checked in the free run.

    • cites Hippold 2019

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  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    AI does not function in a vacuum; AI systems are typically developed and deployed in tandem with other digital technologies.

    “However, it is important to acknowledge from the outset that AI does not function in a vacuum; AI systems are typically developed and deployed in tandem with other digital technologies.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Askoxylakis 2018 source

      Not checked in the free run.

    • cites Reuter 2016 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    The use of AI in support of CE tacitly encourages increased data collection through allowing data analysis capabilities to be scaled, in turn threatening consumer privacy.

    “Accordingly, the use of AI in support of CE tacitly encourages increased data collection through allowing data analysis capabilities to be scaled, in turn threatening consumer privacy.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    AI can support the broader infrastructures needed to scale circularity.

    “It can aid in designing robust and sustainable products, facilitate new circular business models, and support the broader infrastructures needed to scale circularity.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    To date, considerations of the ethical implications of using AI to achieve a transition to CE have been limited, and the potential harms from using AI for CE have not been comprehensively analysed.

    “However, to date, considerations of the ethical implications of using AI to achieve a transition to CE have been limited.”
    • Also stated in: § 1 Introduction: artificial intelligence, circular economy, and their challenges · plain
      “By contrast, the potential for harms to emerge from using AI to achieve this circular transition has not been comprehensively analysed.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Acerbi et al. 2021 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    AI can support designers by suggesting initial designs for eco-friendly products or adjusting designs based on environmental parameters and/or considerations of other actors in the circular value chain.

    “AI can support designers by suggesting initial designs for eco-friendly products or adjusting designs based on environmental parameters and/or considerations of other actors in the circular value chain (Acerbi et al. 2021;Gailhofer et al. 2021).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Acerbi et al. 2021 source

      Not checked in the free run.

    • cites Gailhofer et al. 2021

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    A public engagement exercise by the Geospatial Commission revealed that individuals were concerned that geospatial data are not being used in their best interests, that they could not control the use of these data meaningfully, and that there were real risks of the data being misused or breached.

    “A recent public engagement exercise by the Geospatial Commissionan expert committee housed within the UK Government's Cabinet Office-revealed that individuals were concerned that geospatial data are not being used in their best interests, that they could not control the use of these data meaningfully, and that there were real risks of the data being misused or breached (Maxwell et al. 2021).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Maxwell et al. 2021

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Circularity can hardly be achieved without collaboration, posing a need for cooperative networks, and data and interoperable systems are critical to this end.

    “A single actor does not”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Alexandris et al. 2018

      Not checked in the free run.

    • cites Larsson and Lindfred 2019 source

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    • cites Sankaran 2020 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    AI can facilitate new circular business models.

    “It can aid in designing robust and sustainable products, facilitate new circular business models, and support the broader infrastructures needed to scale circularity.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisenone given

    AI technologies have novel features, including an ability to process vast amounts of data, autonomously or semi-autonomously, to make inferences, predictions, decisions, or generate content.

    “First, AI technologies have several novel features, including an ability to process vast amounts of data, autonomously or semi-autonomously, to make inferences, predictions, decisions, or to generate content.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning

    For AI-powered CE products to be designed inclusively, those creating the systems must be reflective of a society's diversity.

    “More generally, for AI-powered CE products to be designed inclusively, those creating the systems must be reflective of a society's diversity.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Many AI systems are (semi-)autonomous and opaque, making it more difficult to detect and rectify issues ex-post.

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationreasoning

    Positive social and environmental outcomes could be undermined by a disjointed, uneven, or misguided application of AI in transitioning to a circular economy.

    “Moreover, positive social and environmental outcomes could be undermined by a disjointed, uneven, or misguided application of AI in transitioning to a circular economy.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: CE offers an alternative vision to the current linear economic model.

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Using AI to develop and maintain circular products and businesses may pose significant challenges.

    “Using AI to develop and maintain circular products and businesses may pose significant challenges.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: CE offers an alternative vision to the current linear economic model.
    • Rests on an assumption: There has been little scrutiny of the ethical consequences of using AI to transition to CE and how to address potential risks.
    • Rests on an assumption: AI will be crucial to realising the transition to CE.

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationnone given

    These risks can be minimised and, in some cases, avoided altogether.

    “These risks can be minimised and, in some cases, avoided altogether.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: CE offers an alternative vision to the current linear economic model.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationreasoning

    Failing to correct the diversity gap will lead to the development of AI products that only work well for specific demographic groups.

    “Failing to do so will lead to the development of AI products that only work well for specific demographic groups.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Many AI systems are (semi-)autonomous and opaque, making it more difficult to detect and rectify issues ex-post.

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning

    Privacy, equality, and well-being could all be harmed through the unethical use of AI.

    “Privacy, equality, and well-being could all be harmed through the unethical use of AI.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: CE offers an alternative vision to the current linear economic model.

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationreasoning

    Open source can provide a promising first step for reducing global inequalities, but it is necessary to recognise the limited change it can make within wider power structures.

    “Accordingly, open source can provide a promising first step for reducing global inequalities, but it is necessary to recognise the limited change it can make within wider power structures.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The resultant shift would be a polarisation in the types of occupations available, thus leading to wage inequality.

    “The resultant shift would be a polarisation in the types of occupations available, thus leading to wage inequality (Lawrence et al. 2017).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Lawrence et al. 2017

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Bamboo chopsticks are less energetically expensive than a highly specialised plastic fork.

    “For example, bamboo chopsticks are less energetically expensive than a highly specialised plastic fork.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Murray et al. 2017 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationreasoning

    If left unaddressed, these risks could affect the potential successful adoption of a connected circular economy or make its implementation more problematic than it needs to be through undermining public trust.

    “If left unaddressed, these risks could affect the potential successful adoption of a connected circular economy or make its implementation more problematic than it needs to be through undermining public trust.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.

    Premisenone given

    AI has novel features including an ability to process vast amounts of data, autonomously or semi-autonomously, and to make inferences, predictions, decisions, or to generate content.

    “the novel features of AI which include (i) an ability to process vast amounts of data, (ii) autonomously or semi-autonomously, and (iii) to make inferences, predictions, decisions, or to generate content.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    When disposed, bamboo chopsticks can be easily reassimilated into nature through bio-degradation.

    “the bamboo chopsticks can be easily reassimilated into nature through bio-degradation”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Murray et al. 2017 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationnone given

    Adopting AI ethics best practices within organisations, such as using privacy-enhancing technologies and AI ethics-based auditing, will help mitigate potential risks from privacy infringements and harmful biases.

    “At the micro-level, adopting AI ethics best practices within organisations, such as using privacy-enhancing technologies and AI ethics-based auditing, will help mitigate potential risks from privacy infringements and harmful biases.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationnone given

    Promoting open source, industry-wide collaboration on reskilling, and supporting inclusive design could help minimise the exacerbation of social and economic inequalities, both internationally and domestically.

    “At the meso-level, the promotion of open source, industry-wide collaboration on reskilling, and supporting inclusive design, could help minimise the exacerbation of social and economic inequalities, both internationally and domestically.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    This figure does not necessarily suggest that CE initiatives are shrinking in real terms.

    “One important caveat is that this does not necessarily suggest that CE initiatives are shrinking in real terms.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    The risk is that governance policies may standardise the wrong trade-offs and thus scale harms.

    “The risk here is that governance policies may standardise the wrong trade-offs and thus scale harms.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationnone given

    Governments can help address some epistemological questions associated with using AI for CE by providing further funding for research and developing guidance and standards collaboratively.

    “At the macro-level, governments can help to address some of the epistemological questions associated with using AI for CE by providing further funding for research and developing guidance and standards collaboratively.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Adopting these recommendations would leverage the good potential of AI to foster CE.

    “Adopting these recommendations would leverage the good potential of AI to foster CE.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    CE's reduction of linear consumption will change the labour structure from creating products to maintaining products-as-a-service, leading to a greater emphasis on higher skilled work and a lesser emphasis on factory floor product creation.

    “CE's reduction of linear consumption will change the labour structure from creating products to maintaining products-as-a-service.This will mean a greater emphasis on higher skilled work designing and maintaining products, and a lesser emphasis on factory floor product creation.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Interpretationcitation

    One may over-simplify the ecosystem, adopting a reductionist approach, formalising what cannot be reduced to formulae, and using mathematical modelling in which crucial variables are removed.

    “The risk is that one may over-simplify the ecosystem, adopting a reductionist approach, formalising what cannot be reduced to formulae, and using mathematical modelling in which crucial variables are removed (Murray et al. 2017).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Murray et al. 2017 source

      Not checked in the free run.

    • Rests on an assumption: Nature is a complex and balanced ecosystem.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    This figure may be indicative of higher levels of overall consumption.

    “Instead, this figure may be indicative of higher levels of overall consumption.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Algorithmic profiling is problematic.

    “This is not to say that algorithmic profiling is not problematic.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Sweeney 2013 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    AI and CE can be mutually supportive.

    “AI and CE can be mutually supportive”
    Quote in the paperNot a substantial claim
39 of 39

  • The paper relies on this without support.

    Data collection and analysis for CE could exacerbate privacy risks.

    “However, this data collection and analysis could also exacerbate privacy risks.”

  • The paper relies on this without support.

    Nature is a complex and balanced ecosystem.

    “Nature is a complex and balanced ecosystem.”

  • The paper relies on this without support.

    Global South countries have fewer resources to promote an AI-powered circular transition.

    “Global South countries have fewer resources to promote an AI-powered circular transition.”

  • The paper relies on this without support.

    The field of AI auditing is still relatively nascent.

    “It is important to stress that the field of AI auditing is still relatively nascent, meaning research is necessary for determining which framework is appropriate for a specific product or organisation.”

  • The paper relies on this without support.

    Current reskilling initiatives are left mainly to individual organisations and are inadequate for managing longer term occupational shifts.

    “Current reskilling initiatives are left mainly to individual organisations; these initiatives can help manage immediate business needs but are inadequate for managing longer term occupational shifts, due to their frequent disconnect and parochial focus.”

  • The paper relies on this without support.

    Many AI systems are (semi-)autonomous and opaque, making it more difficult to detect and rectify issues ex-post.

    “While this is true for all digital technologies, it is particularly important for AI, given that many systems are (semi-)autonomous and opaque, making it more difficult to detect and rectify issues ex-post.”

  • The paper relies on this without support.

    CE offers an alternative vision to the current linear economic model.

    “CE offers an alternative vision to the current linear economic model.”

  • The paper relies on this without support.

    There has been little scrutiny of the ethical consequences of using AI to transition to CE and how to address potential risks.

    “However, there has been little scrutiny of the ethical consequences of using AI to transition to CE and how to address potential risks.”

  • The paper relies on this without support.

    AI will be crucial to realising the transition to CE.

    “AI will be crucial to realising this transition.”

  • The paper relies on this without support.

    The 3Rs are typically adopted, though many scholars go further through adding other 'Rs' pertaining to CE behaviours.

    “The 3Rs are typically adopted, though many scholars go further through adding other 'Rs' pertaining to CE behaviours.”
10 of 10

Cites

Flagged first, then by citations

Research works printed but not linked: 10

  1. Angwin J, Larson J, Mattu S (2015) The tiger mom tax: Asians are nearly twice as likely to get a higher price from Princeton review. ProPublica. https://www.propublica.org/article/asians-nearly-twice-as-likely-to-get-higher-price-from-princeton-review?token=UnpQVP7I8tJbGlMfvfYJisVdJ7aaZ7jl. Accessed 01 Jan 2022
  2. Chander A (2017) The racist algorithm? Mich Law Rev 115(6):1023–1045. https://doi.org/10.3316/agispt.20190905016562 · DOI
  3. Floridi L (2019) The green and the blue: naïve ideas to improve politics in a mature information society. Springer, pp 183–221
  4. Floridi L (2020) The green and the blue: a new political ontology for a mature information society. Philos Jahrb 127(2):307–338
  5. Hippold S (2019) Gartner Predicts Circular Economies Will Replace Linear Economies in 10 Years. Gartner. https://www.gartner.com/en/newsroom/press-releases/2019-09-26-gartner-predicts-circular-economies-will-replace-line. Accessed 10 Nov 2021
  6. Notes from the AI Frontier (2018) Modeling the impact of AI on the world economy. McKinsey Global Institute. pp. 3–4
  7. Ramadoss TS, Alam H, Seeram R (2018) Artificial intelligence and internet of things enabled circular economy. Int J Eng Sci (IJES) 7(9 Ver III):55–63
  8. Smart Meter Statistics in Great Britain: Quarterly Report to end March 2020 (2020). Department for Business, Energy and Industrial Strategy
  9. Tremblay J-F (2016) How rare earths bring clean technologies, dirty landscapes. Chem Eng News 94(32):24
  10. Frank AG (1986) The Development of Underdevelopment. In Promise of Development. Routledge.

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Authors
Roberts, H., Zhang, J., Bariach, B., Cowls, J., Gilburt, B., Juneja, P., Tsamados, A., Ziosi, M., Taddeo, M., & Floridi, L.
Affiliations
  • Peking University (CN)
  • University of Oxford (GB)
Corresponding author
Floridi, Luciano
ORCID
Venue
AI & SOCIETY
Publisher
Springer Science and Business Media LLC
Published
2022-11-28
Volume
39
Issue
3
Pages
1451-1464
ISSN
  • 0951-5666 (ISSN-L)
  • 1435-5655
DOI
10.1007/s00146-022-01596-8
OpenAlex
W4310248850
Semantic Scholar
b88f63212029a72dc1bf2848747a7d050c93f80c
Cited by
123
References
71
Citations by year
2026: 41 · 2025: 43 · 2024: 20 · 2023: 16 · 2022: 2 · 2021: 1
FWCI
23.45
Type
journal article
Language
en
Open access
Licence
Locations
  • AI & Society (publishedVersion, cc-by)
  • SSRN Electronic Journal (acceptedVersion)
  • PhilPapers (PhilPapers Foundation) (submittedVersion)
Funders
  • University of Oxford
  • European Commission
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Sustainable Supply Chain Management
  • Social Sciences › Sociology and Political Science › Innovation, Sustainability, Human-Machine Systems
Keywords
artificial intelligence, circular economy, AI ethics, ethical risks, sustainable product design, circular business models, resource extraction, waste reduction, sustainable development, policy recommendations

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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.

What counts as a claim ›How we measure confidence ›How we check this ›

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