Record summary
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Risk profile
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The general tenet of AI alignment involves training generative AI systems to be harmless, helpful, and honest, ensuring their behavior aligns with and respects human values. However, a central debate in this area concerns the methodological challenges in selecting appropriate values. While AI systems can acquire human values through feedback, observation, or debate, there remains ambiguity over which individuals are qualified or legitimized to provide these guiding signals. Another prominent issue pertains to deceptive alignment, which might cause generative AI systems to tamper evaluations. Additionally, many papers explore risks associated with reward hacking, proxy gaming, or goal misgeneralization in generative AI systems.
Suggested mitigations
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Source
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Included resource
Mapping the Ethics of Generative AI: A Comprehensive Scoping Review
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.
