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

TL;DR

This paper emphasizes the importance of standardizing AI incident reporting to improve trustworthiness and safety, proposing actionable recommendations to fill existing gaps and support sustainable development goals.

Contribution

It systematically analyzes current AI incident databases, identifies reporting gaps, and proposes nine standardization recommendations to enhance AI incident data collection and management.

Findings

Identified nine gaps in current AI incident reporting practices.

Proposed nine actionable recommendations for standardization.

Highlighted the role of standardized reporting in trustworthy AI and sustainable development.

Abstract

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.