Trustless Economic Agency
AI summary of the linked articleThe author describes using AI to improve individual economic output, centered on a concept called Economic Agency: an entity making money by choosing a profitable game and winning it. In a "Deterministic Agency Experiment," a Post Fiat token on the XRP network issued tasks from a user-written Context Document, and GPT-4 scored the user's focus, motivation, efficacy and honesty over repeated runs. A "Game-Selection Enhancement Experiment" then used Claude to rewrite sections of the context document and O1 to produce a final version, with a reported 41.2% score improvement on a sample text. The author says the scores port almost linearly to other models and that the approach yields linear, not transformative, improvements. |
1 comment  timSubmitter Previously - this would require the mechanics of a large corporation - managers talking to one another, coordinating performance reviews and so forth. But now, you can just run an LLM 50 times and get a fairly objective take on a User's performance over time. Not correct. The author claims that LLMs come to an „objective conclusion“ if you have them run the same prompt over many times, and then the author says that this is capable of rationalizing humans. But this is an argumentation error. yes, you can prompt multiple times and come to a conclusion that is the aggregate of LLM outputs and so potentially your output is of higher quality, but the LLM model could still have biases that would lead it to make bad choices, even on 50 runs. Let‘s remember, some „finger in the air“ managers are much better than others. Some of them make or break an organization. Some make an organization world class. And here you have a guy who says they can just all be replaced by running an LLM 50 times. Good luck mate! |
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