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  1. How do people judge the credibility of algorithmic sources?Donghee Shin - 2022 - AI and Society 37 (1):81-96.
    The exponential growth of algorithms has made establishing a trusted relationship between human and artificial intelligence increasingly important. Algorithm systems such as chatbots can play an important role in assessing a user’s credibility on algorithms. Unless users believe the chatbot’s information is credible, they are not likely to be willing to act on the recommendation. This study examines how literacy and user trust influence perceptions of chatbot information credibility. Results confirm that algorithmic literacy and users’ trust play a pivotal role (...)
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  • In AI we trust? Perceptions about automated decision-making by artificial intelligence.Theo Araujo, Natali Helberger, Sanne Kruikemeier & Claes H. de Vreese - 2020 - AI and Society 35 (3):611-623.
    Fueled by ever-growing amounts of (digital) data and advances in artificial intelligence, decision-making in contemporary societies is increasingly delegated to automated processes. Drawing from social science theories and from the emerging body of research about algorithmic appreciation and algorithmic perceptions, the current study explores the extent to which personal characteristics can be linked to perceptions of automated decision-making by AI, and the boundary conditions of these perceptions, namely the extent to which such perceptions differ across media, (public) health, and judicial (...)
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  • Social choice ethics in artificial intelligence.Seth D. Baum - 2020 - AI and Society 35 (1):165-176.
    A major approach to the ethics of artificial intelligence is to use social choice, in which the AI is designed to act according to the aggregate views of society. This is found in the AI ethics of “coherent extrapolated volition” and “bottom–up ethics”. This paper shows that the normative basis of AI social choice ethics is weak due to the fact that there is no one single aggregate ethical view of society. Instead, the design of social choice AI faces three (...)
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  • Ten simple rules for responsible big data research.Matthew Zook, Solon Barocas, Danah Boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson & Frank Pasquale - 2017 - PLOS Computational Biology 13 (3):e1005399.
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  • The problem of machine ethics in artificial intelligence.Rajakishore Nath & Vineet Sahu - 2020 - AI and Society 35 (1):103-111.
    The advent of the intelligent robot has occupied a significant position in society over the past decades and has given rise to new issues in society. As we know, the primary aim of artificial intelligence or robotic research is not only to develop advanced programs to solve our problems but also to reproduce mental qualities in machines. The critical claim of artificial intelligence advocates is that there is no distinction between mind and machines and thus they argue that there are (...)
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