11 Nov Can an AI Learn Political Theory?
Abstract
Alan Turing’s 1950 paper, “Computing Machinery and Intelligence,” contains much more than its proposal of the “Turing Test.” Turing imagined the development of what we today call AI by a process akin to the education of a child. Thus, while Turing anticipated “machine learning,” his prescience brings to the foreground the yet unsolved problem of how humans might teach or shape AIs to behave in ways that align with moral standards. Part of the teaching process is likely to entail AIs’ absorbing lessons from human writings. Natural language processing tools are one of the ways computer systems extract knowledge from texts. An example is given of how one such technique, Latent Dirichlet Allocation, can draw out the most prominent themes from works of classical political theory.
Keywords: Artificial intelligence, Machine learning, Latent Dirichlet allocation, Alan Turing, Human/AI interactions
AI Perspectives 2(3) (2020)
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