As far as I know, all sensory evolution prior to this point has been motivated based on incremental gains in fitting a changing environment. True vision requir

As far as I know, all sensory evolution prior to this point has been motivated based on incremental gains in fitting a changing environment. True vision requires motive and embodied self. I’m ignorant about the state of the art here, but I’m way more terrified of what these things don’t see than interested in what they could show us. It seems to me that the only human motives accessible to machines are extremely superficial and behavioral based. Knowledge is not some disconnected map of symbols that results in easily measurable behavior, it has a deep and fundamental relation to conscious and unconscious human motivation. I don’t see any possible way to give a machine that same set of motives without having it go through our same evolutionary and cultural history, and strongly believe most of our true motives are under many protective layers of behavioral feints and tests and require voluntary connection and deep introspection to fractionally expose to our conscious selves, let alone others, let alone a computer. These models seem to be amazingly good at combining maps of already travelled territory. Trying to use them to create maps for territory that is new to us seems incredibly dangerous. Am I missing something here, or is it not true that AI models operate purely on bias? What we chose to measure and train the model on seems to predetermine the outcome, it’s not actually empirical because it can’t evaluate whether it’s predictions make sense outside of that model. At some point it’s always dependent on a human saying “success/fail”, and seems more like an incredibly complicated kaleidoscope. Maybe they can cause humans to see patterns we didn’t see before, but I don’t think it’s something that could actually make new discoveries on its own.