The relationship between subjectivity and its substrate can be understood via the notion of compatibilist emergence, accounting for the plurality of ways nature can host new dynamical laws at higher scales. We discuss how the autopoietic character of life may require and promote the kind of emergence necessary, albeit not sufficient, for consciousness.

Brain waves driven by electrochemical processing may be necessary for consciousness, and if so, that will challenge consciousness in artificial intelligence (AI) and perhaps in some invertebrates.

We comment on Anil Seth’s target article from the perspective of theoretical computer science, a branch of mathematics that considers computation under limited resources, and from our own perspective developing a formal machine model for consciousness, the Conscious Turing Machine. From these perspectives, we argue that Seth makes a case for artificial intelligence consciousness. We also address misconceptions about computation.

Digital computation may not be sufficient for consciousness, but this does not warrant biological naturalism. Rejecting coarse-grained Turing-computational functionalism and adopting a broader computationalism with no built-in syntax/semantics distinction, undermines the motivation for biological naturalism. Substrate-dependent processes of the kind found in living things may be necessary for the emergence of consciousness, but these are functional requirements, not intrinsic properties.

Living things are special because they are valuing subjects, for whom things can be good or bad. This is in virtue of their having internalized optimization processes, tied to persistence, that evaluate whether things are going well or poorly and adjust appropriately. Those evaluations, when integrated from diverse sources and widely available, provide the basis for conscious experience.

Seth’s arguments for biological naturalism are not actually arguments for substrate dependence. Most of the criteria he proposes – including embodiment, embeddedness, active inference, allostasis, and metabolism – could be satisfied by digital organisms existing within a sufficiently detailed simulation running on Turing computation.

Seth’s argument relies on the unargued-for claim that if computational functionalism is false, conscious AI is impossible. I show why the claim is in need of support by way of an analogy. I use a different analogy, involving artificial flight, to show that even if human consciousness is ineliminably biological, this does not imply the impossibility of non-biological, computational AI.

The paper assumes a fundamental difference between the study of consciousness and the study of intelligence and cognition more widely construed. I question this assumption, drawing on work by the (badly named) “illusionists.” Once we see past the illusions, the landscape looks different, although Seth’s core conclusions (about the importance of living organisations) might still obtain.

We challenge Seth’s claim that simulations of consciousness necessarily lack the causal powers or intrinsic properties of real consciousness. We argue that Seth’s position risks begging the question against computational functionalism and faces a dilemma over the reducibility of qualia. This weakens his case, leaving open the possibility that simulations could, in principle, realize consciousness.

Andy Clark’s notion of microfunctionalism (1989) offers a biologically grounded form of functionalism, narrowing the scope of “multiple realizability.” While computation is substrate-independent in principle, only select systems – such as brains – can implement its computational complexity. Extending this view, I challenge Seth’s skepticism of computationalism and conscious AI, emphasizing the difference between possible and actual substrate independence. Current digital architectures fall short, but future systems might instantiate conscious states if built on appropriate computational substrates.

I make three claims: First, denying biological naturalism does not logically require computational functionalism. Second, while Seth’s arguments establish biological naturalism as a view worth taking seriously, they fail to make it more plausible than the view that AI can be conscious. Third, there are independent arguments suggesting the overall more plausible view is that AI can be conscious.

In addition to arguments for scepticism concerning the technical feasibility of conscious AI, there are grounds for scepticism concerning its desirability and safety. Conscious AI created by human beings could, especially if it reflects human nature, be extremely dangerous. It could also be very different from human consciousness and thus (a) undetectable, (b) incomprehensible, and (c) incommunicable. The latter consideration could increase the risks of the former and cut both ways, if the conscious AI has valenced experience.

In this commentary, we focus on three interrelated issues of particular importance for determining the possibility of “artificial consciousness”: 1) the distinctions between sentience and consciousness, 2) why the physical substrate of a complex system is critical for the emergence of sentience, and 3) how Emergence in Systems Theory helps explain consciousness in animals and whether “artificial consciousness” could exist.

We argue that by focusing on an unanswerable ontological question, both computational functionalism and biological naturalism miss the empirical question of scientific and practical interest: what are systems of some kind capable of experiencing?

The target article draws a sharp contrast between intelligence and consciousness. We believe this contrast is premature and rests on an overly narrow characterisation of intelligence as abilities that can be exhaustively characterised as mappings from sensory inputs to behavioural outputs. Instead, we argue that the fortunes of intelligence and consciousness are interwoven more tightly than Seth’s framing implies.

It is a pleasure to comment upon, which covers everything that could – and should – be said about the matter. It left me wondering whether artificial consciousness is an oxymoron. I take this opportunity to unpack the thermodynamic issues that attend mortal computation and their implications for conscious artefacts.

Seth’s defense of biological naturalism is valuable and timely. But his endorsement of the predictive processing framework, in an ambitious form that aims to cover more than perception itself, is probably a wrong turn.

I have recently suggested not to ask what science can do for consciousness but what consciousness can do for science. Here, I extend such a recommendation in the context of naturalism, the meta-ontology shared by most contrasting approaches to the problem of “conscious artificial intelligence”: do not ask what naturalism can do for AI but what AI can do for naturalism.

Seth argues in favour of strongly substrate-dependent biological naturalism. I suggest we need more reason to believe the substrates in question are consciousness-specific. Instead, the case for mortal computational biological naturalism is more promising. A self-evidencing framing helps elucidate what the consciousness-specific functional characteristics of mortal computation might be, leaving conscious AI waiting in the wings.

Seth’s claim that only biological or biological-like systems can be conscious leaves open the question of what renders only some organisms conscious. We address this question by pointing to the material, ontogenetic, memory, and evaluative affordances of living organisms and arguing that evolved, minimal consciousness requires complex cognitive-affective architecture for which these biological affordances are obligatory. Conscious thinking of humans cannot be separated from minimal consciousness, and non-biological AI robots’ computations do not render these operations conscious.