AI-Mediated Exchange Theory

March 04, 2020 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Xiao Ma, Taylor W. Brown arXiv ID 2003.02093 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI Citations 13 Venue arXiv.org Last Checked 4 months ago
Abstract
As Artificial Intelligence (AI) plays an ever-expanding role in sociotechnical systems, it is important to articulate the relationships between humans and AI. However, the scholarly communities studying human-AI relationships -- including but not limited to social computing, machine learning, science and technology studies, and other social sciences -- are divided by the perspectives that define them. These perspectives vary both by their focus on humans or AI, and in the micro/macro lenses through which they approach subjects. These differences inhibit the integration of findings, and thus impede science and interdisciplinarity. In this position paper, we propose the development of a framework AI-Mediated Exchange Theory (AI-MET) to bridge these divides. As an extension to Social Exchange Theory (SET) in the social sciences, AI-MET views AI as influencing human-to-human relationships via a taxonomy of mediation mechanisms. We list initial ideas of these mechanisms, and show how AI-MET can be used to help human-AI research communities speak to one another.
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