People’s comfort with and acceptability of artificial intelligence (AI) instantiations is a topic that has received little systematic study. This is surprising given the topic’s relevance to the design, deployment and even regulation of AI systems. To help fill in our knowledge base, we conducted mixed-methods analysis based on a survey of a representative sample of the US population (_N_ = 2254). Results show that there are two distinct social dimensions to comfort with AI: as a peer and as a (...) superior. For both dimensions, general and technological efficacy traits—locus of control, communication apprehension, robot phobia, and perceived technology competence—are strongly associated with acceptance of AI in various roles. Female and older respondents also were less comfortable with the idea of AI agents in various roles. A qualitative analysis of comments collected from respondents complemented our statistical approach. We conclude by exploring the implications of our research for AI acceptability in society. (shrink)

This book addresses the growing use of computerized systems to influence people’s decisions without their awareness, a significant but underappreciated sea-change in the way the world works. To assess these systems, this volume’s contributors explore the philosophical and ethical dimensions of algorithms that guide people’s behavior by nudging them toward choices preferred by systems architects. Particularly in an era of heightened awareness of bias and discrimination, these systems raise profound concerns about the morality of such activities. This volume brings together (...) a diverse array of thinkers to critically examine these nudging systems. Not only are high-level perspectives presented, but so too are of those who use them on a day-to-day basis. While algorithmic nudging can produce benefits for users there are also many less-obvious costs to using such systems, costs that require examination and deliberation. This book is a major step towards delineating these concerns and suggesting ways to provide a sounder basis for future policies for algorithms. It should be of interest to system designers, public policymakers, scholars, and those who wonder more deeply about the nudges they receive from various websites and on their phones. (shrink)