2 résultats pour « catastrophic risk »
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This paper extends prior work to model an insurance company facing a future "tipping point" where catastrophe risks increase. Using viscosity solutions of a Hamilton-Jacobi-Bellman equation, the authors solve an optimal control problem to find the best dividend strategy. They show that, under fair premium adjustments and full observability, increased catastrophe risk may benefit shareholders. Numerical examples support these findings, and future research may explore relaxing model assumptions.
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This paper addresses the inadequacy of the current U.S. tort liability system in handling the catastrophic risks posed by advanced AI systems. The author proposes punitive damages to incentivize caution in AI development, even without malice or recklessness. Additional suggestions include recognizing AI as an abnormally dangerous activity and requiring liability insurance for AI systems. The paper concludes by acknowledging the limits of tort liability and exploring complementary policies for mitigating catastrophic AI risk.
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