Designing Artificial Intelligence for Autonomy

AI can be understood historically is a subfield of computer and cognitive science. It can also be characterized as a specific set of computational techniques that extract statistical correlations from large datasets, currently dominated by machine learning and neural network approaches. Today, for the most part, these techniques are applied to natural language processing, analysis and generation of ‘content’ (e.g., text, images, datasets, and programming code), and automated decision/recommendation systems. AI also is a “floating signifier” with strategic vagueness that escapes precise definition while suggesting technological autonomy, serving the interests of its promoters while obscuring the material practices, labor and political economies that make it up. This account is important for our purposes because by treating AI as an “uncontroversial thing” with autonomous agency, rather than a situated set of practices and relations, we contribute to its mystification and shield it from critical examination (Suchman, 2023). [...]