Remaking Intelligence? Of Machines, Media, and Montage

Philippe Sormani


Abstract: Over the last decade, there has been a renewed interest in “artificial intelligence” (AI), notably in the form of “machine learning” (ML). This renewed interest may seem paradoxical, insofar as John McCarthy introduced the term “AI” in the mid-1950s to mark a distinction with ML, championing deductive reasoning over automated induction (e.g., Cardon et al. 2018). By contrast, the current reversal, towards ML-based forms of “AI,” marks the statistical, if not spectacular, revival of automated induction. However, the terms used – revival, renewal, reversal – beg the question of the common ground of the involved alternatives. Taking its cue from recent historical (e.g., Penn 2020), relevant conceptual (e.g., Shanker 1998), and prior critical (e.g., Agre 1997) inquiries, this paper outlines a praxeological answer to the raised question. For the purpose, the paper develops a practice-based video analysis of a recent demonstration of “machine intelligence,” the video demonstration of an “agent system” playing Breakout at “superhuman level,” if not opening the gate for the advent of “general AI” (Hassabis 2017). In examining and engaging in “remaking intelligence” in situ, the paper dwells on the tricky interplay between machines, media, and montage, while making explicit and reflecting upon how particular configurations of “enchanted determinism” (Campolo and Crawford 2020) are staged and locally performed.

Keywords: artificial intelligence; breakout game; common ground; machine learning; practical reenactment(s); video demonstration.

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