AISN #20: LLM Proliferation, AI Deception, and Continuing Drivers of AI Capabilities.
AI Deception: Examples, Risks, SolutionsAI deception is the topic of a new paper from researchers at and affiliated with the Center for AI Safety. It surveys empirical examples of AI deception, then explores societal risks and potential solutions.The paper defines deception as “the systematic production of false beliefs in others as a means to accomplish some outcome other than the truth.” Importantly, this definition doesn't necessarily imply that AIs have beliefs or intentions. Instead, it focuses on patterns of behavior that regularly cause false beliefs and would be considered deceptive…
The skinny
The skinny isn't ready yet — notes appear once the transcript is processed.