Stronger Together: on the Articulation of Ethical Charters, Legal Tools, and Technical Documentation in ML
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Abstract (arXiv)
The growing need for accountability of the people behind AI systems can be addressed by leveraging processes in three fields of study: ethics, law, and computer science. While these fields are often considered in isolation, they rely on complementary notions in their interpretation and implementation. In this work, we detail this interdependence and motivate the necessary role of collaborative governance tools in shaping a positive evolution of AI. We first contrast notions of compliance in the ethical, legal, and technical fields; we outline both their differences and where they complement each other, with a particular focus on the roles of ethical charters, licenses, and technical documentation in these interactions. We then focus on the role of values in articulating the synergies between the fields and outline specific mechanisms of interaction between them in practice. We identify how these mechanisms have played out in several open governance fora: an open collaborative workshop, a responsible licensing initiative, and a proposed regulatory framework. By leveraging complementary notions of compliance in these three domains, we can create a more comprehensive framework for governing AI systems that jointly takes into account their technical capabilities, their impact on society, and how technical specifications can inform relevant regulations. Our analysis thus underlines the necessity of joint consideration of the ethical, legal, and technical in AI ethics frameworks to be used on a larger scale to govern AI systems and how the thinking in each of these areas can inform the others.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 May 2023.
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Citing papers per year: 2023: 1; 2024: 4; 2025: 3; 2026: 1.
9 papers.
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- 2025SCOR: A Framework for Responsible AI Innovation in Digital Ecosystems12 Sep 2025
- 2025Better Aligned with Survey Respondents or Training Data? Unveiling Political Leanings of LLMs on U.S. Supreme Court Cases25 Feb 2025
- 2024Acceptable Use Policies for Foundation Models29 Aug 2024
- 2024The Future of Open Human Feedback15 Aug 2024
- 2024AI Cards: Towards an Applied Framework for Machine-Readable AI and Risk Documentation Inspired by the EU AI Act26 Jun 2024
- 2024Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?19 Apr 2024
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