Patterns and Antipatterns, Principles, and Pitfalls: Accountability and Transparency in Artificial Intelligence
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This article discusses a set of principles for accountability and transparency in AI as well as a set of antipatterns or harmful trends too often seen in deployed systems. It provides concrete suggestions for what can be done to shift the balance away from these antipatterns and toward more positive ones.
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The composite and gradient nature of openness can be grounded directly in prior work on openness and accountability in AI systems.
“The composite and gradient nature of openness can be grounded directly in prior work on openness and accountability in AI systems [29, 37, 42, 58].”
From Rethinking open source generative AI: open washing and the EU AI Act (2024) · cites this paper as [37]
Data sheets, model cards, and system cards are frameworks that can help structure the systematic presentation of metadata about models and systems and that feed into auditing procedures.
“Important constituent elements are the notions of data sheets [18, 25, 38], model cards [40], and system cards [22]: frameworks that can help structure the systematic presentation of metadata about models and systems and that feed into auditing procedures [37].”
From Rethinking open source generative AI: open washing and the EU AI Act (2024) · cites this paper as [37]
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Responsible Artificial Intelligence Governance: A Review and Research Framework
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- Authors
- Matthews, J.
- Affiliations
- Clarkson University (US)
- Corresponding author
- Matthews, Jeanna
- ORCID
- Matthews, Jeanna
- Venue
- AI Magazine
- Publisher
- Wiley
- Published
- 2020-03
- Volume
- 41
- Issue
- 1
- Pages
- 82-89
- ISSN
- 0738-4602 (ISSN-L)
- 2371-9621
- OpenAlex
- W3017645313
- Cited by
- 22
- References
- 24
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 5 · 2023: 2 · 2022: 2 · 2021: 5
- FWCI
- 3.07
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- AI Magazine (publishedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Social Sciences › Law › Digitalization, Law, and Regulation
- Keywords
- AI transparency, anti-patterns, AI principles, AI governance
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