Advancing Trustworthy AI for Sustainable Development: Recommendations for Standardising AI Incident Reporting
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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
- 2021Trustworthy AI: From Principles to Practicescited by 207
- 2020Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claimscited by 165
- 2019The role of artificial intelligence in achieving the Sustainable Development Goalscited by 100
- 2020Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Databasecited by 96
- 2021Filling gaps in trustworthy development of AIcited by 14
Built on by
Citing papers per year: 2025: 3; 2026: 1.
4 papers.
- 2025Standardised schema and taxonomy for AI incident databases in critical digital infrastructurecited by 5
- 2025A five-layer framework for AI governance: integrating regulation, standards, and certificationcited by 2
- 2025Incorporating AI incident reporting into telecommunications law and policy: Insights from Indiacited by 1
- 2026A federated architecture for sector-led AI governance: lessons from Indiacited by 1
- 2026A federated architecture for sector-led AI governance: lessons from India27 Mar 2026
- 2025A five-layer framework for AI governance: integrating regulation, standards, and certification14 Sep 2025
- 2025Incorporating AI incident reporting into telecommunications law and policy: Insights from India11 Sep 2025
- 2025Standardised schema and taxonomy for AI incident databases in critical digital infrastructure28 Jan 2025