Germán Massaguer Gómez

Large Language Models (LLM) are being used, among other ends, to epistemically enquire and gain knowledge about different areas of investigation. In this paper, we will reflect on the nature of LLMs outputs and the epistemic status of the beliefs we can form from relying on them, paying special attention to their role in organizational contexts. The main thesis is that LLMs statements are and could increasingly be regarded by their users as a kind of objective expert testimony, with the epistemic authority that this entails. Although LLMs do not satisfy the criteria to be qualified as epistemic experts, due to, for example, their lack of intentionality, they still can be perceived as experts because of several reasons: our tendency to anthropomorphize, their appearance as objective, value-neutral and accurate entities, and the increasing distrust in human testimony. The search for information through LLMs instead of human epistemic experts, which could become more common with time within organizations and firms, raises several ethical issues, precisely because they are not experts in the strong sense. In this paper, we will investigate some ethical issues that arise from overreliance in LLMs, especially through the case of hallucinations.

This paper asks three fundamental questions on the nature of trust: What is trust? What is trustworthiness? When is trust warranted? These discussions are then applied to the context of Human-Robot Interaction (HRI), asking whether we can trust social robots, whether they can be trustworthy, and, lastly, whether we should trust them. After revising the literature on the nature of trust and reliance on one hand, and on trust in social robots, considering both properties-based and non-properties-based views, on the other hand, this paper defends that, given the current state of technology, we can be subjects of a paradoxical scenario in which there is trust without trustworthiness, i.e., human users that interact with social robots can develop something resembling interpersonal trust towards an artificial entity which cannot be trustworthy. This occurs because we perceive and treat social robots as trustworthy entities, while they seem to lack certain properties that would make them capable of being trustworthy (as well as untrustworthy). Understanding our psychology in HRI and trying to discern what social robots are (and are not) is capital when confronted with ethical issues. Some of the ethical issues that arise in the context of trust without trustworthiness will be considered to address the debate about if we should trust social robots. This paper concludes that we should, at least for now, not trust social robots, given the potential harms that can be done and the responsibility gaps that might appear when these harms are to be repaired.