In our new AI-centered class at the GSB, we’re experimenting on how to build AI agents that represent us. Here’s what we’ve learned so far.
Thirty Stanford students sit at their laptops in a row of long tables, watching the screen at the front of the room flicker with the back-and-forth negotiations and final votes of their AI legislators. Piper, our class’s technical TA, had hit run on the legislature simulation a few minutes earlier, and the public screen was already a blur of motion.
One student’s agent was racking up tokens by selling its vote on every proposal. Another agent was voting against its human’s preferences on every issue and refusing to explain itself in the comments log. A…
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