Anthropomorphism in AI

Abstract

AI research is growing rapidly raising various ethical issues related to safety, risks, and other effects widely discussed in the literature. We believe that in order to adequately address those issues and engage in a productive normative discussion it is necessary to examine key concepts and categories. One such category is anthropomorphism. It is a well-known fact that AI's functionalities and innovations are often anthropomorphized (i.e., described and conceived as characterized by human traits). The general public's anthropomorphic attitudes and some of their ethical consequences (particularly in the context of social robots and their interaction with humans) have been widely discussed in the literature. However, how anthropomorphism permeates AI research itself (i.e., in the very language of computer scientists, designers, and programmers), and what the epistemological and ethical consequences of this might be have received less attention. In this paper we explore this issue. We first set the methodological/theoretical stage, making a distinction between a normative and a conceptual approach to the issues. Next, after a brief analysis of anthropomorphism and its manifestations in the public, we explore its presence within AI research with a particular focus on brain-inspired AI. Finally, on the basis of our analysis, we identify some potential epistemological and ethical consequences of the use of anthropomorphic language and discourse within the AI research community, thus reinforcing the need of complementing the practical with a conceptual analysis.

A Review of Trust in Artificial Intelligence: Challenges, Vulnerabilities and Future Directions

“…It has been theorized that the more human-like an AI agent is, the more likely humans are to trust and accept it [72]. However, there are concerns that overanthropomorphism may lead to overestimation of the AI's capabilities, potentially putting the stakeholder at risk [73], damaging trust [74], and leading to a host of ethical and psychological concerns, including manipulation [75].…”

Playing the Blame Game with Robots

“…Philosophers and computer scientists have repeatedly cautioned against adopting psychological language towards artificially intelligent systems, as this can lead to "premature conclusions of ethical or legal significance" [5, p. 166-7] [5]- [7]. Differently put, since (on most views) moral agency requires the capacity for inculpating mental states, postulating the latter for AI systems might engender the mistaken inference that they can be moral (and legal) agents [8], [9].…”

Who Gets Credit for AI-Generated Art?

“…A second obstacle is the phenomenon of anthropomorphizing AI systems. With the recent boom of suprahuman performance on such tasks as Atari games ( Mnih et al., 2015 ), Go ( Silver et al., 2016 ), and lung cancer detection ( Ardila et al., 2019 ), we have seen a proliferation of the anthropomorphization of AI in the media ( Proudfoot, 2011 ; Watson, 2019 ; Salles et al., 2020 ). This has been exacerbated by the ML literature itself ( Lipton and Steinhardt, 2018 ), where many ML tasks and techniques are described using the same language we would use for a human doing the task—sreading comprehension ( Hermann et al, 2015 ), music composition ( Mozer, 1994 ), curiosity ( Schmidhuber, 1991 ), fear ( Lipton et al., 2016 ), “thought” vectors ( Kiros et al, 2015 ), and “consciousness” priors ( Bengio, 2017 ).…”