mlsanityData to 14 Oct 2026

Advancing Trustworthy AI for Sustainable Development: Recommendations for Standardising AI Incident Reporting

arXiv 2501.14778 ↗First posted 1 Jan 2025cs.CY cs.AI cs.HCcited by 4

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Abstract (arXiv)

The increasing use of AI technologies has led to increasing AI incidents, posing risks and causing harm to individuals, organizations, and society. This study recognizes and addresses the lack of standardized protocols for reliably and comprehensively gathering such incident data crucial for preventing future incidents and developing mitigating strategies. Specifically, this study analyses existing open-access AI-incident databases through a systematic methodology and identifies nine gaps in current AI incident reporting practices. Further, it proposes nine actionable recommendations to enhance standardization efforts to address these gaps. Ensuring the trustworthiness of enabling technologies such as AI is necessary for sustainable digital transformation. Our research promotes the development of standards to prevent future AI incidents and promote trustworthy AI, thus facilitating achieving the UN sustainable development goals. Through international cooperation, stakeholders can unlock the transformative potential of AI, enabling a sustainable and inclusive future for all.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 5 of its 34 references that are in the map. First posted on arXiv 1 Jan 2025.

Builds on

5 of 34 references.

References · 5

  1. 2021Trustworthy AI: From Principles to Practicescited by 207
  2. 2020Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claimscited by 165
  3. 2019The role of artificial intelligence in achieving the Sustainable Development Goalscited by 100
  4. 2020Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Databasecited by 96
  5. 2021Filling gaps in trustworthy development of AIcited by 14

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 1.

4 papers.