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Abstract
Artificial intelligence (AI) has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised learning methods—namely lasso penalties, bagging, and boosting—offer subtler, more interesting analogies to human reasoning as both an individual and a social phenomenon. Despite the temptation to fall back on anthropomorphic tropes when discussing AI, however, I conclude that such rhetoric is at best misleading and at worst downright dangerous. The impulse to humanize algorithms is an obstacle to properly conceptualizing the ethical challenges posed by emerging technologies.
Highlights
Ever since the seminal work of Turing (1950) if not before, experts and laypeople alike have tended to frame computational achievements in explicitly epistemological terms
I attempt to move beyond the platitudes and critically examine specific examples of algorithms that employ learning strategies found in cognitive science and social epistemology
More illuminating analogies can be found in other areas of computational statistics, notably three cases I shall explore in considerable depth: lasso penalties, bagging, and boosting
Summary
Ever since the seminal work of Turing (1950) if not before, experts and laypeople alike have tended to frame computational achievements in explicitly epistemological terms. We speak of machines that think, learn, and infer. The name of the discipline itself—artificial intelligence—practically dares us to compare our human modes of reasoning with the behavior of algorithms. It is not always clear whether such language is meant to be literal or metaphorical
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