Actionable Guidance for High-Consequence AI Risk Management: Towards Standards Addressing AI Catastrophic Risks.
š Description
Actionable Guidance for High-Consequence AI Risk Management: Towards Standards Addressing AI Catastrophic Risks Anthony M. Barrett ? *, Dan Hendrycks ? , Jessica Newman ? , Brandie Nonnecke ? ? UC Berkeley * Corresponding author: [email address redacted] This version last revised 23 February 2023 arXiv non-exclusive license ( https://arxiv.org/licenses/nonexclusive-distrib/1.0/license.html ) 1 Abstract Artificial intelligence (AI) systems can provide many beneficial capabilities but also risks of adverse events. Some AI systems could present risks of events with very high or catastrophic consequences at societal scale. The US National Institute of Standards and Technology (NIST) has been developing the NIST Artificial Intelligence Risk Management Framework (AI RMF) as voluntary guidance on AI risk assessment and management for AI developers and others. For addressing risks of events with catastrophic consequences, NIST indicated a need to translate from high level principles to ...
š Game Impacts
Not verified in gameWhich variables this event was proposed to move, and in which direction. The magnitudes are held in the corpus but are not shown here, because they have not been verified against the shipped game. They come from pdoom-data. They describe what an event was proposed to do, not what the shipped game does with it. Most events in the corpus are flavour: they are shown for colour and do not move any game variable. Only a small minority reach the systems below, and several of the variables listed here are not read by the game at all yet. Treat this table as a design proposal under review, not as a measurement of play. Corrections and arguments are welcome — the suggestion links at the foot of this page go straight to the data repo.
| Variable | Direction | Condition |
|---|---|---|
| Research | proposed: up | Always |
| Papers | proposed: up | Always |
| Vibey Doom | proposed: up | Always |
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This event data is sourced from the pdoom-data repository. If you notice errors or want to suggest improvements:
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