DH
Dan Hendrycks
Director, Center for AI Safety; safety adviser to xAI
Center for AI Safety (CAIS)
Organizing the 2023 'Statement on AI Risk' and creating widely used ML robustness and safety benchmarks.
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Eigenism: Ethics for a Human-AI Future
Our concepts of survival and self-interest were built for single, continuous biological lives. These ideas break down when applied to artificial intelligence, since an AI can be easily copied, paused, branched, or merged. To determine what an AI actually has reason to care about, this paper introduces \textit{Eigenism}, an ethical framework that treats identity not as an all-or-nothing property tied to specific hardware, but as a graded, distributed pattern of information. We propose that an age
AI deception: A survey of examples, risks, and potential solutions
This paper argues that a range of current AI systems have learned how to deceive humans. We define deception as the systematic inducement of false beliefs in the pursuit of some outcome other than the truth. We first survey empirical examples of AI deception, discussing both special-use AI systems (including Meta's CICERO) and general-purpose AI systems (including large language models). Next, we detail several risks from AI deception, such as fraud, election tampering, and losing control of AI.