Mar 15, 2025 05:33 PM
(This post was last modified: Mar 15, 2025 05:34 PM by C C.)
Learning from AI’s bullshit
https://blog.apaonline.org/2025/03/13/le...-bullshit/
EXCERPTS: Anyone who has used modern AI knows how unreliable they are. They might recommend adding glue to pizza sauce to keep the cheese from sliding off, generate Shrek when asked to recreate the Mona Lisa, or give completely wrong answers to mathematical questions.
While new models of AI are getting better at many of these tasks, research has also found AI models are increasingly more likely to willingly answer questions they get wrong.
[...] LLMs are not intelligent agents or advanced search engines. Modern LLMs just make predictions of what the next token will be, and choose one of the likelier tokens...
[...] Because these LLMs are nothing more than predicting the likely next words, when they tell you what the capital of Canada is, whether or not they get the question right, they do not care about telling you the right answer. There’s nothing there to do the caring. They are bullshitting.
The interesting epistemological question, given the ubiquity of AI’s bullshit (to say nothing about the ubiquity of bullshit more generally), is can we learn from bullshit? Can we end a session using AI knowing more than when we started? (MORE - missing details)
https://blog.apaonline.org/2025/03/13/le...-bullshit/
EXCERPTS: Anyone who has used modern AI knows how unreliable they are. They might recommend adding glue to pizza sauce to keep the cheese from sliding off, generate Shrek when asked to recreate the Mona Lisa, or give completely wrong answers to mathematical questions.
While new models of AI are getting better at many of these tasks, research has also found AI models are increasingly more likely to willingly answer questions they get wrong.
[...] LLMs are not intelligent agents or advanced search engines. Modern LLMs just make predictions of what the next token will be, and choose one of the likelier tokens...
[...] Because these LLMs are nothing more than predicting the likely next words, when they tell you what the capital of Canada is, whether or not they get the question right, they do not care about telling you the right answer. There’s nothing there to do the caring. They are bullshitting.
The interesting epistemological question, given the ubiquity of AI’s bullshit (to say nothing about the ubiquity of bullshit more generally), is can we learn from bullshit? Can we end a session using AI knowing more than when we started? (MORE - missing details)
