More Than Bias: Social and Technological Selectivities of (Subsymbolic) Artificial Intelligence

This paper explores, under the key concept of selectivity, various structuring effects of subsymbolic artificial intelligence (AI) as a social phenomenon, from targeted development to specific technical functionality, to its embedding in usage contexts, associated with latent societal adaptation processes. In doing so, the paper extends discussions about discrimination and data bias to include further aspects of latent social design and technology-immanent structuring. Based on the systematization of eleven AI selectivities, central questions of a changing human–AI resp. human–technology relationship are discussed, and a guiding principle for a possible future relationship beyond competition resp. linear substitution is outlined.