AI Incidents: Key Components for a Mandatory Reporting Regime

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The report advocates for a federated and comprehensive AI incident reporting framework to systematically document, analyze, and respond to AI incidents, emphasizing the need for standardized components in reporting [2][8][46] Summary by Sections Executive Summary - The report proposes a hybrid AI incident reporting framework that includes mandatory, voluntary, and citizen reporting mechanisms to enhance AI safety and security [2][4][8] Key Components of AI Incidents - A set of standardized key components for AI incidents is defined, including information about the type of incident, nature and severity of harm, technical data, affected entities, and context [3][15][18] Types of Events - The report distinguishes between AI incidents and near misses, suggesting both should be included in mandatory reporting to improve data collection and safety measures [22][26] Harm Dimensions - The report categorizes harm into several types, including physical, environmental, economic, reputational, public interest, human rights, and psychological [29][34] Technical Data - It recommends that AI actors submit AI system or model cards and datasheets as part of mandatory reporting to capture vital technical dimensions of AI incidents [37][38] Context, Circumstances, and Stakeholders - Key components related to context include the goals of the AI system, sector, location, and existing safeguards, which help assess the conditions surrounding an incident [39][40] Post-incident Data - The report emphasizes the importance of documenting incident responses and ethical impacts to promote transparency and improve incident management practices [43][44] Policy Recommendations - It recommends publishing standardized AI incident reporting formats and establishing an independent investigation agency to enhance data collection and analysis [46][48]