Hi All
A useful paper.
The risks posed by Artificial Intelligence (AI) are of considerable concern to academics, auditors,
policymakers, AI companies, and the public. However, a lack of shared understanding of AI risks
can impede our ability to comprehensively discuss, research, and react to them. This paper
addresses this gap by creating an AI Risk Repository to serve as a common frame of reference.
This comprises a living database of 777 risks extracted from 43 taxonomies, which can be filtered
based on two overarching taxonomies and easily accessed, modified, and updated via our website
and online spreadsheets. We construct our Repository with a systematic review of taxonomies and
other structured classifications of AI risk followed by an expert consultation. We develop our
taxonomies of AI risk using a best-fit framework synthesis. Our high-level Causal Taxonomy of AI
Risks classifies each risk by its causal factors (1) Entity: Human, AI; (2) Intentionality: Intentional,
Unintentional; and (3) Timing: Pre-deployment; Post-deployment. Our mid-level Domain Taxonomy
of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy &
security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6)
Socioeconomic & environmental, and (7) AI system safety, failures, & limitations. These are further
divided into 23 subdomains. The AI Risk Repository is, to our knowledge, the first attempt to
rigorously curate, analyze, and extract AI risk frameworks into a publicly accessible,
comprehensive, extensible, and categorized risk database. This creates a foundation for a more
coordinated, coherent, and complete approach to defining, auditing, and managing the risks posed
by AI systems.
https://cdn.prod.website-files.com/669550d38372f33552d2516e/66bc918b580467717e194940_The%20AI%20Risk...
Regards
Caute_Cautim
