Despite impressive advances, machine learning has abandoned many of its early profound insights. The discipline has become overly reliant on statistical analysis of massive data sets and strayed far from its conceptual roots. A promising alternative, common at the field's founding four decades ago, is to develop mechanisms that learn like humans. We can use findings from cognitive psychology to devise a computational gauntlet that systems must traverse, giving new criteria for evaluation. Here are six core features of human learning that provide constraints: • Learning involves the acquisition of modular cognitive structures. This does not specify the structures' details; only that expertise consists of discrete mental elements.
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