I went back to complete the test, and it tells you what it guessed, which helped to explain both things. It also didn't guess my drawing of a bulldozer, which I was surprised at since my drawing wasn't bad, and easily recognizable to any human of any age as a bulldozer. > It seems the answers are pre-programmed because I drew just a car and it said 'I know! It's a police car' even though I'd drawn no siren.Įxactly the same thing happened to me (I did a CTRL+F on 'police' to find this post), which immediately turned me from 'this is cool' to almost quitting, and coming here to see if anyone else experienced the same thing (perhaps with different images). It's a quite fascinating time from an ontological perspective. Because AI and humans share the same environment, we should see converging 'intelligence' (skills, familiarity, etc). I realize another wording is that we should apply sound evolutionary (Darwin etc.) principles in 'growing' AI at large.

Think of plants: you can tweak the growing all you want, but the root deciding factors lie in genetics (their potential, and in understanding how to maximize it). Basically, I don't think it would be practical nor cost efficient to induce too much perturbations in deep learning, better work on refining the process itself. I don't really think you can hard-code 'human bias' as it's an emergent property of our biology: too complex (we don't really understand much of it, imho you're bound to miss the mark and induce subjective biases), and somewhat contradictory to how NNs are supposed to evolve (thinking long term here). Visually lots of cats, lots of cars, mountains and coasts functionally all the tasks we accomplish daily, like driving or cooking or cleaning. nothing more and nothing less than elements of our lives/civs.

Imho, precisely because NNs will be fed with nothing else than the reality (physical or virtual) we live in, it should gradually develop the same familiarity as humans have i.e. I don't see a fundamental difference between biological and electronic neural nets so please take the following with a physicalist grain of salt. humans have become pretty good at identifying cats.

I think the word you're looking for is 'familiarity', insofar as it describes a particularly efficient means of recognition.

Download free quickdraw withgoogle com