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Artificial intuition

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Human intuition looks different if we adopt this type of conceptual model for it. Intuition is not about auras or somehow peering directly into someone’s essence. It instead results from the interaction of so many factors in our brains that we correctly intuit that you’re a vegetarian but can’t tell you why, other than some vague statement such as, “I don’t know. Nothing in particular. It’s just the sense I got.” “Nothing in particular” might actually stand for “Too many small particulars and cues that when combined make me think you’ re probably a vegetarian.” Likewise for the teacher who has learned so much about each of her students that she correctly intuits the class will do well learning about atoms by holding hands to form molecules.

A new model

Our new model of intuition is not anything akin to a special faculty of the mind, something that some people have more of than others. Rather, it is the product of a mind that is so complex, considering so many factors in their interrelationships, that we can produce correct outputs without being able to tell you why.

We allow machine learning to do its job without always insisting on knowing exactly how it works, so maybe we’ll start to give human intuition more respect. After all, historically we’ve seen how we’ ve reshaped our self-understanding based on how our latest technology works.

Maybe the rise of machine learning will so transform our model of intuition that we’ll start to trust it much more. But if we do, we’ll also face the same problem that “intuitive” AI faces—for lots of pernicious biases thrive in the darkness intuition embraces.

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