How to resist the Fading Qualia Argument

Andreas Mogensen (Global Priorities Institute, University of Oxford)

GPI Working Paper No. 5-2024

The Fading Qualia Argument is perhaps the strongest argument supporting the view that in order for a system to be conscious, it does not need to be made of anything in particular, so long as its internal parts have the right causal relations to each other and to the system’s inputs and outputs. I show how the argument can be resisted given two key assumptions: that consciousness is associated with vagueness at its boundaries and that conscious neural activity has a particular kind of holistic structure. I take this to show that what is arguably our strongest argument supporting the view that consciousness is substrate independent has important weaknesses, as a result of which we should decrease our confidence that consciousness can be realized in systems whose physical composition is very different from our own.

Other working papers

Against Willing Servitude: Autonomy in the Ethics of Advanced Artificial Intelligence – Adam Bales (Global Priorities Institute, University of Oxford)

Some people believe that advanced artificial intelligence systems (AIs) might, in the future, come to have moral status. Further, humans might be tempted to design such AIs that they serve us, carrying out tasks that make our lives better. This raises the question of whether designing AIs with moral status to be willing servants would problematically violate their autonomy. In this paper, I argue that it would in fact do so.

Calibration dilemmas in the ethics of distribution – Jacob M. Nebel (University of Southern California) and H. Orri Stefánsson (Stockholm University and Swedish Collegium for Advanced Study)

This paper presents a new kind of problem in the ethics of distribution. The problem takes the form of several “calibration dilemmas,” in which intuitively reasonable aversion to small-stakes inequalities requires leading theories of distribution to recommend intuitively unreasonable aversion to large-stakes inequalities—e.g., inequalities in which half the population would gain an arbitrarily large quantity of well-being or resources…

AI alignment vs AI ethical treatment: Ten challenges – Adam Bradley (Lingnan University) and Bradford Saad (Global Priorities Institute, University of Oxford)

A morally acceptable course of AI development should avoid two dangers: creating unaligned AI systems that pose a threat to humanity and mistreating AI systems that merit moral consideration in their own right. This paper argues these two dangers interact and that if we create AI systems that merit moral consideration, simultaneously avoiding both of these dangers would be extremely challenging. While our argument is straightforward and supported by a wide range of pretheoretical moral judgments, it has far-reaching…