"A cold, technical decision-maker": Can AI provide explainability, negotiability, and humanity?
Allison Woodruff, Yasmin Asare Anderson, Katherine Jameson, Armstrong, Marina Gkiza, Jay Jennings, Christopher Moessner and, Fernanda Viegas, Martin Wattenberg, and Lynette Webb, Fabian Wrede, and Patrick Gage Kelley

TL;DR
This study explores perceptions of AI as a decision-maker, highlighting its strengths in mechanical tasks and limitations in moral judgments, and introduces the concept of 'negotiability' in decision processes.
Contribution
It provides qualitative insights into how people perceive AI's explainability, humanity, and negotiability across different countries and decision-making contexts.
Findings
AI viewed as rigid and mechanical but lacking moral judgment
Participants value negotiability as flexibility beyond formal criteria
Concerns about AI's opacity and alignment with social values
Abstract
Algorithmic systems are increasingly deployed to make decisions in many areas of people's lives. The shift from human to algorithmic decision-making has been accompanied by concern about potentially opaque decisions that are not aligned with social values, as well as proposed remedies such as explainability. We present results of a qualitative study of algorithmic decision-making, comprised of five workshops conducted with a total of 60 participants in Finland, Germany, the United Kingdom, and the United States. We invited participants to reason about decision-making qualities such as explainability and accuracy in a variety of domains. Participants viewed AI as a decision-maker that follows rigid criteria and performs mechanical tasks well, but is largely incapable of subjective or morally complex judgments. We discuss participants' consideration of humanity in decision-making, and…
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Taxonomy
TopicsEthics and Social Impacts of AI · Explainable Artificial Intelligence (XAI) · Artificial Intelligence in Healthcare and Education
