Can a Robot Lie? Exploring the Folk Concept of Lying as Applied to Artificial Agents

Lying about the future: Shuar-Achuar epistemic norms, predictions, and commitments

Is there variation across cultures in what counts as a lie? Here we present evidence for a potentially unique conceptualization of lying in Shuar-Achuar communities in Ecuador, contrasting this conceptualization with people in twelve other countries and non-Shuar-Achuar Ecuadorians. In Shuar-Achuar communities, but not others, predictions of the future that turn out to be false are considered lies, even when the events that render them false are unforeseen. Failed commitments, on the other hand, are not seen as lies when unforeseen events prevent them from being kept. To explain this phenomenon, we suggest that there is an epistemic norm that regulates predictive speech acts in Shuar-Achuar communities, linked to the view that the future can be known under certain special circumstances. This norm holds that claiming knowledge of the future is a form of lying when events prove the prediction false. Commitments, on the other hand, do not imply certainty about the future and so are not considered lies when circumstances prevent them from being fulfilled. In addition, we found several other factors that influence whether speech acts are categorized as lies, including the speaker's expertise, group membership, and the nature of the outcome.

Intelligence brings responsibility - Even smart AI assistants are held responsible

People will not hold cars responsible for traffic accidents, yet they do when artificial intelligence (AI) is involved. AI systems are held responsible when they act or merely advise a human agent. Does this mean that as soon as AI is involved responsibility follows? To find out, we examined whether purely instrumental AI systems stay clear of responsibility. We compared AI-powered with non-AI-powered car warning systems and measured their responsibility rating alongside their human users. Our findings show that responsibility is shared when the warning system is powered by AI but not by a purely mechanical system, even though people consider both systems as mere tools. Surprisingly, whether the warning prevents the accident introduces an outcome bias: the AI takes higher credit than blame depending on what the human manages or fails to do.

Can Artificial Intelligence Make Art?

In two experiments (total N=693) we explored whether people are willing to consider paintings made by AI-driven robots as art, and robots as artists. Across the two experiments, we manipulated three factors: (i) agent type (AI-driven robot v. human agent), (ii) behavior type (intentional creation of a painting v. accidental creation), and (iii) object type (abstract v. representational painting). We found that people judge robot paintings and human paintings as art to roughly the same extent. However, people are much less willing to consider robots as artists than humans, which is partially explained by the fact that they are less disposed to attribute artistic intentions to robots.

What Might Machines Mean?

This essay addresses the question whether artificial speakers can perform speech acts in the technical sense of that term common in the philosophy of language. We here argue that under certain conditions artificial speakers can perform speech acts so understood. After (§1) explaining some of the issues at stake in these questions, we (§2) elucidate a relatively uncontroversial way in which machines can communicate, namely through what we call verbal signaling. But verbal signaling is not sufficient for the performance of a speech act. To explain the difference, we (§3) elucidate the notion of a speech act developed by Austin (How to Do Things with Words, 1962) in the mid-twentieth century and then discuss Strawson’s ("Intention and Convention in Speech Acts", 1964) influential proposal for how that notion may be related to Grice’s ("Meaning", 1957) conception of speaker meaning. We then refine Strawson’s synthesis in light of Armstrong’s ("Meaning and Communication", 1971) reconceptualization of speaker meaning in terms of objectives rather than intentions. We next (§4) extend this conception of speech acts to the cases of recorded, proxy, and conditional speech acts. On this basis, we propose (§5) that a characteristic role for artificial speakers is as proxies in the performance of speech acts on behalf of their human creators. We (§6) also consider two objections to our position, and compare our approach with others: while other authors appeal to notions such as “quasi-assertion,” we offer a sharp characterization of what artificial speakers can do that does not impute intentions or similarly controversial powers to them. We conclude (§7) by raising doubts that our strategy can be applied to speech acts generally.