The DOI matches its Crossref record; 2 of the 19 references it cites were found in a registry or an index.
Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI
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Claims the paper makes
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?
In the citing paper
“Additionally grounding the definition of our proposed values in Human Rights frameworks constitutes an appealing starting point to addressing these limitations given their global reach, varied realizations (both historically and geographically), and general recognition as an accepted foundation of good governance [55].”
From Data Governance in the Age of Large-Scale Data-Driven Language Technology (2022) · cites this paper as [55]
In the citing paper
“It is worth mentioning that most of these AI principles guides directly approach XAI as a key aspect to consider and include in AI systems.”
From Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI (2020) · cites this paper as [385]
In the citing paper
“For instance, the survey in [385] evinces that 26 out of the 28 AI principles that deal with XAI, also talk about fairness explicitly.”
From Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI (2020) · cites this paper as [385]
In the citing paper
“In fact, the overview for these principles introduced before [385], indicates that 28 out of the 32 AI principles guides covered in the analysis, explicitly include XAI as a crucial component.”
From Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI (2020) · cites this paper as [385]
In the citing paper
“A recent review of some of the main AI principles published since 2016 appears in [385].”
From Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI (2020) · cites this paper as [385]
In the citing paper
“Looking at several examples of principles declared by different organizations [385], we can divide them into two groups:”
From Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI (2020) · cites this paper as [385]
In the citing paper
“These better coverages can be attributed to several factors. They include more accessible advanced AI technology, stringent regulatory environments, and robust scholarly communication networks [50–52].”
From Generative artificial intelligence (GAI) usage guidelines for scholarly publishing: a cross-sectional study of medical journals (2025) · cites this paper as [51]
In the citing paper
“This practice aligns with broader principles of responsible AI governance, which call for evaluating potential societal and ethical impacts before deployment to ensure technologies contribute positively to goals like energy justice [7,73].”
From Addressing Challenges for the Effective Adoption of Artificial Intelligence in the Energy Sector (2025) · cites this paper as [73]
In the citing paper
“Meta-analyses of AI ethics proposals have thus far focused mainly on classifying and comparing the ethical principles suggested, where some convergence can be identified for principles like transparency, fairness, privacy and responsibility [4][5][6].”
From Putting AI ethics to work: are the tools fit for purpose? (2022) · cites this paper as [6]
In the citing paper
“In the first phase from 2016 to 2019, many high-level ethical principles for AI were published as evidenced by these catalogues of ethical principles and frameworks for ethical, trustworthy responsible AI [4-6, 18, 19].”
From Putting AI ethics to work: are the tools fit for purpose? (2022) · cites this paper as [6]
Citations
Cites
Recommendation of the Council on Artificial Intelligence (OECD)
Yeung, K. (2020) · International Legal Materials · doi:10.1017/ilm.2020.5 · Cited by 845
(2019) · Datenschutz und Datensicherheit - DuD · doi:10.1007/s11623-019-1183-6 · Cited by 51
Cited by
Sorted by citations
Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., et al. (2020) · Information Fusion · doi:10.1016/j.inffus.2019.12.012 · Cited by 10,423
Shneiderman, B. (2020) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3419764 · Cited by 768
“The HCAI movement has raised these issues again with frequent calls for Algo-rithmic Accountability and Transparency [40], Ethically Aligned Design [56], and Professional Responsibility [36].”
BackgroundInfluentialManaging artificial intelligence
Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021) · MIS Quarterly · doi:10.25300/misq/2021/16274 · Cited by 898
Responsible Artificial Intelligence Governance: A Review and Research Framework
Papagiannidis, E., Mikalef, P., & Conboy, K. (2025) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2024.101885 · Cited by 565
Artificial intelligence, systemic risks, and sustainability
Galaz, V., Centeno, M. A., Callahan, P. W., Causevic, A., Patterson, T., Brass, I., Baum, S., Farber, D., Fischer, J., Garcia, D., et al. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101741 · Cited by 497
“…risks could potentially be ameliorated through the application of principles defining “ ethical AI ” , “ responsible AI ” or “ AI for Good ” that have emerged in the last years [115,116], especially those that address fairness, non-discrimination, accountability, transparency, privacy and security.”
Background
Metadata
- Authors
- Fjeld, J., Achten, N., Hilligoss, H., Nagy, A., & Srikumar, M.
- Affiliations
- Harvard University (US)
- Corresponding author
- Fjeld, Jessica
- ORCID
- Srikumar, Madhulika
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2020
- ISSN
- 1556-5068 (ISSN-L)
- OpenAlex
- W2999331643
- Cited by
- 998
- References
- 19
- Citations by year
- 2026: 114 · 2025: 231 · 2024: 186 · 2023: 180 · 2022: 143 · 2021: 102 · 2020: 41
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- SSRN Electronic Journal (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
- Keywords
- AI principles, AI ethics, human rights-based approach, AI governance, privacy, accountability, safety and security, transparency and explainability, human control of technology, professional responsibility
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