Upcoming Event

Abstract: In recent work, I argued that there is an AI-specific no miracles argument (NMA) which is at least as plausible as the traditional NMA. In this talk, I will express two doubts about this claim, relative to the AI-specific NMA that I previously proposed. I will then develop a new AI-specific NMA in response,

Abstract: Making AI explainable has become an increasingly urgent demand, and one of the popular approaches is to generate so-called counterfactual explanations. In this talk, I attempt a philosophical critique of the key aspects of this approach, and raise an important challenge arising from a tension between two constraints on a good counterfactual explanation in

Abstract: To avoid predicting that certain kinds of compulsions contribute to welfare, many desire satisfaction theorists draw a distinction between genuine desires and other desires. Such theorists hold that it is only the satisfaction of genuine desires that contributes to welfare; other desires do not count. From the perspective of AI welfare, then, we must

Abstract: With rapid advances in the social and cognitive capabilities of AI, questions concerning their consciousness and moral status are becoming increasingly pressing. In this talk, I contrast two radically different approaches—Deep and Shallow—to addressing these issues. Deep approaches dominate mainstream philosophy of mind and consciousness science, viewing consciousness as an empirically discoverable natural kind

Abstract: Around 40% of philosophers believe that future AI systems will be conscious (Bourget and Chalmers 2023). Others have argued that the realization of phenomenal consciousness in conventional computer hardware is infeasible, nomologically impossible, or even metaphysically impossible (Block 2009; Godfrey-Smith 2016; Searle 1992; Shiller 2024; Tononi and Koch 2015). Whether or not the AI systems

Abstract: Late in his career, Daniel Dennett changed his mind about minds. If his new view is correct, it has deep implications for both the moral standing of nascent AIs and for the existential danger they may pose. He suggests in his (2017) that genuine minds require a different kind of architecture than he previously

Abstract: Most agree that consciousness bears some sort of important connection to well-being. For example, consciousness is necessary for having experiences of pleasure and pain, and these experiences are often — if not always — good and bad for us, respectively. The subject of AI consciousness is therefore highly relevant to the subject of AI

Abstract: Much of the recent discourse on AI consciousness has centered around two questions: is artificial consciousness possible in principle and do current systems meet the requirements laid out by prominent theories. For many practical purposes, it matters more whether we are likely to see nontrivial numbers of conscious artificial minds as the technology matures.

Abstract: Identifying the presence of consciousness is difficult even in humans when one does not want to rely on subjective reports [1,2], but it is increasingly more difficult in animals [3,4], and, due to the lack of common evolutionary history, even more so in artificial systems [5,6]. Currently, there are two major alternatives on the

Abstract: One of the more promising empirical theories of phenomenal consciousness is the Global Workspace Theory (GWT), which says that a mental representation becomes conscious when it enters a global workspace from which it can be broadcast to various specialized psychological modules [1-3]. There has been some discussion of GWT in connection with recent advancements