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AI Risk RepositoryTechXplore
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90% Informative
A new analysis of AI -related risks finds significant gaps in our understanding of the risks posed by AI .
The most frequently addressed risk domains included "AI system safety, failures, and limitations" "Socioeconomic and environmental harms" ( 73% ) "Discrimination and toxicity" ( 71% ) "Privacy and security" ( 68% ) "Malicious actors and misuse" received comparatively less attention.
On average, frameworks mentioned just 34% of the 23 risk subdomains identified.
MIT 's AI Risk Repository is the first attempt to rigorously curate, analyze, and extract AI risk frameworks into a publicly accessible, comprehensive, extensible, and categorized risk database.
It is part of a larger effort to understand how we are responding to AI risks and to identify if there are gaps in our current approaches.
The repository is freely available online to download, copy and use.
VR Score
94
Informative language
98
Neutral language
34
Article tone
formal
Language
English
Language complexity
71
Offensive language
not offensive
Hate speech
not hateful
Attention-grabbing headline
not detected
Known propaganda techniques
not detected
Time-value
long-living
External references
11
Source diversity
9
Affiliate links
no affiliate links