| Interestingly there’s another thread I’m in about generative AI where someone asserts “this goes for humans too” in a sort of similar vein. However it’s not the case. Humans have the ability to extrapolate from their training data and synthesize new thought and behavior from situations not seen before that’s fundamentally insightful and adaptive. Generative AI and all machine learning I’m aware of are fundamentally expectation driven probabilistic models that synthesize highly dimensional non linear functions from samples of those functions, which means they can’t adapt to new situations dynamically and extrapolate their experiences into new experiences and make decisions that are novel and intuitive given a new regime. When these models encounter new situations they’ve never experienced or new regimes they interpolate in their learning space to a most likely behavior, but the learning space has nothing similar in it, so the behavior can become seemingly random and highly maladapted. A classical example of this is obviously LLM hallucinations at the edge of their knowledge which an expert in a field can induce by asking questions beyond the horizon of the field. While humans might not have answers, they can pose interesting theories, while LLMs really can’t - if they appear to it’s simply because their training set is so massive they can interpolate into babbling that sounds good. You could assert humans do this to, and it’s true they do at times, but they also don’t at other times and have novel insights beyond their experience. The fact they can do this sometimes and AI mathematically due to its internal structure can’t at any time is the difference. Another example is Go playing AI. They can do really well against expert players until someone plays a nonsense series of plays that are random and the AI begin to play worse than amateurs. You can do this with LLMs too, if you give them enough random nonsense or repeated strings, they just leap into some random spot in their vector space and rant about weirdness. Even GPT4 does this. The answer isn’t to outlaw driving or to stop pursuing AI driving assistants. It’s to build models with an enormous well labeled corpus that covers almost every possible situation, but also build in fail safes that make it easy for a human to be called to attention and take control when things are confusing the AI. |