Yesterday I posted this: Inconsistency in AI It’s a game where I insert myself into a hybrid Human-Machine LLM with two agents working together to construct a thought one word at a time. The machine LLM does so with probabilities and billions of parameters and I do so with a lifetime of experience with the human language. Yesterday I ran it with a biased prompt of “This prompt is wrong” which eventually produced a self-referential performative contradiction. Interesting but I wanted to see how it would run if I didn’t bias the initial prompt. Every response is also a prompt and vice-versa so this hybrid LLM is talking to itself. AI began with “A” which prompted me to choose “response” and so on until AI ended the sentence with “itself”. This is the final thought: “A response is false if truthfully it can never falsify itself.” This is a self-referential paradox like the liar’s paradox. The statement is a response from a self-referential LLM. Since the response refers to a response it is self-referential too. Assume the response is true, since it cannot truthfully ever falsify itself, it must be false. Assume it’s false, then not being able to truthfully falsify itself doesn’t preclude it from being true. Goedel’s incompleteness theorems say that any system that can talk to itself will be inconsistent (logical paradox), there will be truths that it cannot prove (incomplete) and questions it cannot answer with a simple yes/no (undecidable). submitted by /u/Frequent_Mountain_17
Originally posted by u/Frequent_Mountain_17 on r/ArtificialInteligence
You must log in or # to comment.