How are those who design, deploy and manage AI systems currently reconfiguring the dimensions of human-machine cooperation?
As part of Data & Society’s Intelligence & Autonomy Initiative, Madeleine Elish and Tim Hwang conducted long-term research with a range of practitioners working in the intelligent systems and AI industry. Collected in booklet form, An AI Pattern Language presents a taxonomy of social challenges that emerged from these interviews and discussions with practitioners and articulates an array of patterns that practitioners have developed in response.
In this talk, Madeleine Clare Elish will present an overview of the findings from An AI Pattern Language, and then elaborate on the unexpected patterns that emerged around enabling human-machine cooperation. In theory, the “human factor” is imagined to be removed from the equation when deploying AI systems. In reality, humans remain integral, and their roles within AI systems must be seriously considered and accounted for. Embracing these “human frames” creates the conditions for more fair and just, as well as effective, AI systems.
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This event will also be streamed live.
Madeleine Clare Elish is a cultural anthropologist focusing on the social impact of artificial intelligence and automation. Her research investigates how new technologies affect understandings of values and ethical norms, particularly in professional and labor contexts. Her dissertation examines how the sociotechnical systems of drone operations are implicated in changing conceptions of skill, honor and military service in the United States. Madeleine also works as a researcher with the Intelligence & Autonomy Initiative at Data & Society which develops empirical and historical research in order to ground policy debates around the rise of machine intelligence. She is currently a doctoral candidate in Anthropology at Columbia University and previously earned an S.M. in Comparative Media Studies at MIT.