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nice expose of human biases involved, need more of these to balance the hype.

1) Instead of identifying a problem and then trying to find a solution, we start by assuming that AI will be the solution and then looking for problems to solve.

hammer in search of a nail

2) nearly complete non-publication of negative results

survivorship (and confirmation bias)

3) same people who evaluate AI models also benefit from those evaluations

power of incentives (and conflicts therein)

4) ai bandwagon effect, and fear of missing out

social-proof




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