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To assess how artificial intelligence impacts us in multidimensional ways, the novel notion of code capital serves as an account of the sociotechnical features that shape each system. Combining the evolution of capital towards a repository of socialised leverage with the history of technology studies, this concept facilitates analysis along four dimensions: conception, operations, data and environment. In this book, two case studies on facial recognition and synthetic speech generation demonstrate how code capital can act as a form of shared ontology for interdisciplinary stakeholders to anticipate and manage the effects of applied AI.Dr. Léa Steinacker is a researcher, journalist and entrepreneur active in the field where human and machine systems overlap.
Résumé
To assess how artificial intelligence impacts us in multidimensional ways, the novel notion of code capital serves as an account of the sociotechnical features that shape each system. Combining the evolution of capital towards a repository of socialised leverage with the history of technology studies, this concept facilitates analysis along four dimensions: conception, operations, data and environment. In this book, two case studies on facial recognition and synthetic speech generation demonstrate how code capital can act as a form of shared ontology for interdisciplinary stakeholders to anticipate and manage the effects of applied AI.
Dr. Léa Steinacker is a researcher, journalist and entrepreneur active in the field where human and machine systems overlap.
