REVIEW 3 cited by
Regulatory Markets for AI Safety
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
We propose a new model for regulation to achieve AI safety: global regulatory markets. We first sketch the model in general terms and provide an overview of the costs and benefits of this approach. We then demonstrate how the model might work in practice: responding to the risk of adversarial attacks on AI models employed in commercial drones.
Forward citations
Cited by 3 Pith papers
-
Structural transparency of societal AI alignment through Institutional Logics
Introduces a five-component analytical framework, grounded in Institutional Logics, for making visible the organizational and institutional decisions that shape AI alignment.
-
Real-World Gaps in AI Governance Research
Corporate AI safety research is dominated by pre-deployment alignment and evaluation work, while high-risk deployment topics such as medical error, misinformation, bias, behavioral design, and copyright are measured t...
-
Co-evolution of social reward and punishment under institutional interventions
In a four-strategy Prisoner's Dilemma with peer punishers and rewarders, institutional rewards should target the enforcers, institutional punishment should target defectors only, and punishing enforcers destroys coope...
Discussion (0). Continue with ORCID to comment.