Artificial intelligence and scientific problem choice at the nexus of industry and academia

Le résumé fourni par la source

Academic scientists working in the areas of artificial intelligence and machine learning have long been opportunistic, seeking funding from government science agencies, industry or venture capital investment, and other commercialization schemes. However, the so-called “Great AI Awakening” of the last few years has generated tremendous interest and investment in data-intensive and predictive AI techniques and technologies. This, in turn, has reinvigorated critical attention to the research problem choice at the nexus of industry and academia. Industry and commercial logics tend to find their most pernicious influence not at the level of direct control over academic research portfolios or in terms of ethical corruption, but at the far more diffuse level of the questions that get asked in the first place, what questions are subsequently neglected in the asking, and the silences that result.

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