https://community.isc2.org/t5/Governance-Risk-Compliance/The-AI-Risk-Repository/m-p/73156#M1201 <P>Hi All</P><P>&nbsp;</P><P>A useful paper.</P><P>&nbsp;</P><P>The risks posed by Artificial Intelligence (AI) are of considerable concern to academics, auditors,<BR />policymakers, AI companies, and the public. However, a lack of shared understanding of AI risks<BR />can impede our ability to comprehensively discuss, research, and react to them. This paper<BR />addresses this gap by creating an AI Risk Repository to serve as a common frame of reference.<BR />This comprises a living database of 777 risks extracted from 43 taxonomies, which can be filtered<BR />based on two overarching taxonomies and easily accessed, modified, and updated via our website<BR />and online spreadsheets. We construct our Repository with a systematic review of taxonomies and<BR />other structured classifications of AI risk followed by an expert consultation. We develop our<BR />taxonomies of AI risk using a best-fit framework synthesis. Our high-level Causal Taxonomy of AI<BR />Risks classifies each risk by its causal factors (1) Entity: Human, AI; (2) Intentionality: Intentional,<BR />Unintentional; and (3) Timing: Pre-deployment; Post-deployment. Our mid-level Domain Taxonomy<BR />of AI Risks classifies risks into seven AI risk domains: (1) Discrimination &amp; toxicity, (2) Privacy &amp;<BR />security, (3) Misinformation, (4) Malicious actors &amp; misuse, (5) Human-computer interaction, (6)<BR />Socioeconomic &amp; environmental, and (7) AI system safety, failures, &amp; limitations. These are further<BR />divided into 23 subdomains. The AI Risk Repository is, to our knowledge, the first attempt to<BR />rigorously curate, analyze, and extract AI risk frameworks into a publicly accessible,<BR />comprehensive, extensible, and categorized risk database. This creates a foundation for a more<BR />coordinated, coherent, and complete approach to defining, auditing, and managing the risks posed<BR />by AI systems.</P><P>&nbsp;</P><P><A href="https://cdn.prod.website-files.com/669550d38372f33552d2516e/66bc918b580467717e194940_The%20AI%20Risk%20Repository_13_8_2024.pdf" target="_blank" rel="noopener">https://cdn.prod.website-files.com/669550d38372f33552d2516e/66bc918b580467717e194940_The%20AI%20Risk%20Repository_13_8_2024.pdf</A></P><P>&nbsp;</P><P>Regards</P><P>&nbsp;</P><P>Caute_Cautim</P> Fri, 16 Aug 2024 00:15:36 GMT Caute_cautim 2024-08-16T00:15:36Z https://community.isc2.org/t5/Governance-Risk-Compliance/The-AI-Risk-Repository/m-p/73156#M1201 <P>Hi All</P><P>&nbsp;</P><P>A useful paper.</P><P>&nbsp;</P><P>The risks posed by Artificial Intelligence (AI) are of considerable concern to academics, auditors,<BR />policymakers, AI companies, and the public. However, a lack of shared understanding of AI risks<BR />can impede our ability to comprehensively discuss, research, and react to them. This paper<BR />addresses this gap by creating an AI Risk Repository to serve as a common frame of reference.<BR />This comprises a living database of 777 risks extracted from 43 taxonomies, which can be filtered<BR />based on two overarching taxonomies and easily accessed, modified, and updated via our website<BR />and online spreadsheets. We construct our Repository with a systematic review of taxonomies and<BR />other structured classifications of AI risk followed by an expert consultation. We develop our<BR />taxonomies of AI risk using a best-fit framework synthesis. Our high-level Causal Taxonomy of AI<BR />Risks classifies each risk by its causal factors (1) Entity: Human, AI; (2) Intentionality: Intentional,<BR />Unintentional; and (3) Timing: Pre-deployment; Post-deployment. Our mid-level Domain Taxonomy<BR />of AI Risks classifies risks into seven AI risk domains: (1) Discrimination &amp; toxicity, (2) Privacy &amp;<BR />security, (3) Misinformation, (4) Malicious actors &amp; misuse, (5) Human-computer interaction, (6)<BR />Socioeconomic &amp; environmental, and (7) AI system safety, failures, &amp; limitations. These are further<BR />divided into 23 subdomains. The AI Risk Repository is, to our knowledge, the first attempt to<BR />rigorously curate, analyze, and extract AI risk frameworks into a publicly accessible,<BR />comprehensive, extensible, and categorized risk database. This creates a foundation for a more<BR />coordinated, coherent, and complete approach to defining, auditing, and managing the risks posed<BR />by AI systems.</P><P>&nbsp;</P><P><A href="https://cdn.prod.website-files.com/669550d38372f33552d2516e/66bc918b580467717e194940_The%20AI%20Risk%20Repository_13_8_2024.pdf" target="_blank" rel="noopener">https://cdn.prod.website-files.com/669550d38372f33552d2516e/66bc918b580467717e194940_The%20AI%20Risk%20Repository_13_8_2024.pdf</A></P><P>&nbsp;</P><P>Regards</P><P>&nbsp;</P><P>Caute_Cautim</P> Fri, 16 Aug 2024 00:15:36 GMT https://community.isc2.org/t5/Governance-Risk-Compliance/The-AI-Risk-Repository/m-p/73156#M1201 Caute_cautim 2024-08-16T00:15:36Z