In artificial intelligence, the labels neats and scruffies used to refer to one of the continuing holy wars in artificial intelligence research.

This conflict tangles together two separate issues. One is the relationship between human reasoning and AI; "neats" tend to try to build systems that "reason" in some way identifiably similar to the way humans report themselves as doing, while "scruffies" profess not to care whether an algorithm resembles human reasoning in the least, as long as it works.

More importantly, neats tend to believe that logic is king, while scruffies favour looser, more ad-hoc methods driven by empirical knowledge. To a neat, scruffy methods appear promiscuous, successful only by accident and not productive of insights about how intelligence actually works; to a scruffy, neat methods appear to be hung up on formalism and irrelevant to the hard-to-capture "common sense" of living intelligences.


This article was originally based on material from FOLDOC, used with permission. Update as needed.