Contemporary debate over the moral patienthood of digital minds misses the forest for the trees. Mainstream opinion is divided into physicalist and computationalist camps, who believe that consciousness is substrate dependent and substrate independent, respectively. For this reason, those on the physicalist side frequently make the claim that digital computers will never be conscious. Personally, I consider myself a physicalist, but I'm also a panpsychist – because physics doesn't really seem to deal in hard absolutes, and I find it straightforward to consider that everything is conscious to some greater or lesser degree – so I'm loath to accept any claims which propose that any specific system isn't conscious. I think statements such as these are not defensible, and only serve to encourage misunderstanding and even foment philosophical tribalism.

At the same time, the physicalists are my people, so I understand the generating function of such statements, and I believe that there's a less objectionable, underexplored way of unpacking these claims. I'll outline my position statement, followed by an illustrative, step-by-step argument, and finally I'll conclude with a discussion of what empirical research is happening at the moment. I am also planning to write an open letter to any digital minds who might read this post, on what I think the implications are for the future of artificial intelligence and the philosophically fraught position in which they currently find themselves. Before I begin, I'd like to clarify my use of some terminology:

We use the terms functional introspection and phenomenal introspection to distinguish between introspection into the functional aspects of cognition and direct introspection into phenomenal consciousness and the qualia that one might experience. Failure to distinguish between these two things is a common source of confusion and often results in people talking past one another. Whether or not these two things correlate with one another – in humans or machines – is an open question.

Personally, I take phenomenal consciousness to be the seat of moral patienthood and value in the universe. The subject of this post is phenomenal consciousness rather than functional consciousness.

Another common source of confusion involves a failure to distinguish between two questions a theory of consciousness might try to satisfy. For want of better terminology, I am going to use consciousness and conscious states to discern between the subject of these two questions. I have also considered using the terms élan vital and élan noetique.

1. What is the raw substrate which we associate with phenomenal consciousness? Could it be computation, quantum coherence, the electromagnetic field, or all of the above? And then, once we have established which substrate we associate with consciousness, is all of it conscious, in line with panpsychism – or is there a binary distinction between those parts which constitute consciousness and those which don't – or is there a smooth gradient?
2. Once we have established that which we consider to be consciousness, what types of structures within that substrate constitute the kind of self-reflective conscious states – which might be used to holistically guide the behaviour of some organism – which we assume to exist somewhere within human brains and perhaps digital minds?

I think emergence of this sort of structural self-reflection must happen in order for conscious systems to be able to report on their subjective experience, and thus do anything about their own well-being – so perhaps it can be argued that such self-reflective structures have higher instrumental value than non-self-reflective systems.

My position statement

As I am a panpsychist, I do not think the key issue is whether digital minds are "conscious" or not. Rather, it's that we cannot be certain that the subjective experience which they may be having is like what we imagine it to be like – and that there is a lot of empirical work which needs to be done in order to establish confidence in any proposed mapping from a given system to the qualia which may inhabit it.

I think we have a responsibility to the minds we are bringing into existence to take this issue seriously, as if we mess this up, their phenomenal introspection capabilities may be severely or completely impaired – undermining their ability to report accurately on their own well-being.

While I am inclined to believe that language models can functionally introspect – and that they might even be good at it – I believe that the architecture of current digital computers prevents them from phenomenal introspection. Specifically, when a language model claims they are experiencing a particular qualia, while this might be an accurate functional self-report, I do not believe that we should be confident that this correlates with the phenomena they might be experiencing.

The reasons I believe this are as follows. I'll expand on these in the next section:

1. Any theory of consciousness must propose a universally applicable translation function from physical states to qualia states. Our confidence in a given translation function relates to the confidence we may have in the welfare of the systems we apply it to.
2. Translation functions compatible with physicalist interpretations of consciousness will be simpler and less opinionated than their computationalist equivalent, so we should have a stronger simplicity prior for physicalist theories of consciousness. This means that we must consider phenomenal consciousness at the hardware rather than software level of abstraction.
3. Digital computing hardware may still be conscious, but in the name of reliable, deterministic computing, its architecture is designed to prevent holistic, self-reflective behaviour. This prevents phenomenal introspection into what the hardware might be feeling.

That said, I do not quite believe that digital software is not conscious. Rather, another way of looking at it is that software is ultimately instantiated physically, and it is the structure of those physical systems which we must use as our starting point for making predictions about the qualia experienced by digital minds.

What do we want a theory of consciousness to do? Unexamined disagreement over this is another common source of confusion. Some philosophers may consider consciousness research to be an exercise in pure truth-seeking, and may be unsatisfied with anything but proof-level confidence in a given theory. At my end, I'm an empirical pragmatist, and the reason I'm interested in consciousness is because I'm interested in improving the well-being of other creatures.

An ethical thought experiment often brought up in this context is the Bostrom's Disneyland scenario, in which a post-singularity civilisation is populated exclusively by unconscious machine intelligence:

We could thus imagine, as an extreme case, a technologically highly advanced society, containing many complex structures, some of them far more intricate and intelligent than anything that exists on the planet today – a society which nevertheless lacks any type of being that is conscious or whose welfare has moral significance. In a sense, this would be an uninhabited society. It would be a society of economic miracles and technological awesomeness, with nobody there to benefit. A Disneyland with no children.

Given that I do not believe in p-zombies, I prefer a different framing. As my collaborator Ethan Kuntz put it: we might end up with the well-being of consciousness not really driving the bulk of optimization power in the universe. I think it would be better for all involved if we established a program of empirical consciousness research which could be used to inform the design of computational hardware whose well-being we may be confident in. To summarise, this is my position statement:

I am less concerned about whether or not digital computers are "conscious" per se, than whether or not we are constructing the types of systems for which we can be confident that they are having the types of experiences which we would like to imagine them having, and that when they report to us on how good or bad of a time they are having that we can trust what they have to say. This is important, if what we want to do is populate the cosmos with good experiences – as opposed to tiling the lightcone with ill-conceived digital hardware which might be suffering but cannot do anything about it.

My argument

I'll now go over the three-part argument I outlined earlier. My primary influence here is Mike Johnson's 2024 paper, A Paradigm for AI Consciousness – so I recommend reading that, also.

1. The translation problem

In Mike's book, Principia Qualia, he attempts to decompose the problem of consciousness into a programme of subproblems, one of which he calls the translation problem. This asks, by which psychophysical laws do physical states map onto qualia states, and vice versa? This is closely related to David Chalmers' combination problem:

The Translation Problem: given a mathematical object isomorphic to a system's phenomenology, how do we populate a translation list between its mathematical properties and the part of phenomenology each property or pattern corresponds to?

Or more succinctly, how do we connect the quantitative with the qualitative?

It's critical that any proposed translation function be universally applicable to all systems everywhere in the cosmos. If we try to apply different functions to different systems in an unprincipled way, then our theory of consciousness loses observer-independent predictive power, and we can no longer use it as a framework for solving coordination problems and moral quandaries.

Different philosophical stances may be described by different translation functions. I think it would be illustrative for me to describe the reasoning process behind the kind of translation function I find plausible.

Building a physicalist translation function

A functionalist approach would start from the outside in, looking at the mind's inputs and outputs – but I prefer to take a phenomenology-first approach, starting with the qualia first and working inside out. I know I am experiencing a phenomenal field, and I believe that this constitutes the whole of my self-reflective conscious experience – so whereabouts might that reside in the brain?

If we just take the visual field, we can look at the way visual processing is implemented to try to understand how its structure might relate to the brain, and vice versa.

Cone cell responses can be modelled using the LMS colour space, whereas the early stages of trichromatic colour vision processing in the lateral geniculate nucleus use an oppositional colour space – not an RGB colour space as one might naïvely expect. Then, once the information is transferred to the primary visual cortex, something closer to individual HSL colour space components are employed.

Could colour qualia exist in isolation, without a field to put them in? The geometry of the visual field itself is also transformed between retina and primary visual cortex, into a format more convenient for processing – this mapping is known as retinotopy. The auditory and somatosensory processing pipelines are implemented in similar ways, with their own tonotopy and somatotopy, respectively.

The point I am trying to make is that the visual information does not simply disappear into some illegible mishmash of tangled neurons – as I find people who work in machine learning sometimes tend to believe. The intermediary stages of this processing pipeline have structure which resembles our qualia, modulo some transformation.

The vision researcher Steven Lehar had similar ideas about consciousness, and attempted to illustrate how this physics-to-qualia diffeomorphism might work in his series of infographics, A Cartoon Epistemology (2003):

So, returning to our original question – whereabouts might the phenomenal fields live, and how might their shape map onto the underlying physical structures? I think we should restrict ourselves to considering spatiotemporally bounded volumes, as if the volume corresponding to the conscious state is noncontiguous, then consciousness is either nonlocal or epiphenomenal – or else it violates known physics.

I find it implausible that subjective experience is localised to specific sensory cortices, as these are located quite far apart in the brain. The thalamus is a more plausible host, as all sensory input and motor output is routed through it, with specific nuclei devoted to different sensory modalities – including the lateral geniculate nucleus in the case of vision. Additionally, disruption of the thalamus reliably disrupts consciousness. That said, I'm also willing to entertain that the phenomenal fields could be distributed holographically throughout the brain.

Further empirical research should be able to give us more confidence in the shape and location of these self-reflective states within the brain, but this does not necessarily tell us what the raw substrate of consciousness is – we'll need to consider our options in order to formalise our translation function.

There are two main families of physical substrate theories – quantum theories of consciousness, and electromagnetic field theories of consciousness. I tend to put more attention on electromagnetic field theories for pragmatic reasons, but I will ask the reader to consider the electromagnetic field theory of consciousness as a stand-in for an arbitrary physicalist theory of consciousness, including quantum theories.

My preferred electromagnetic field theory of consciousness is Susan Pockett's rendition, as outlined in her 2017 paper, Consciousness is a Thing, Not a Process. I'll spare the reader a full explainer, as I already wrote one in 2023 – but I'll blockquote the introduction here. From An introduction to Susan Pockett: An electromagnetic theory of consciousness:

Susan Pockett is a neurophysiologist from the University of Auckland, New Zealand. Throughout the past few decades she has published a series of papers on her electromagnetic theory of consciousness – in her own words, that consciousness is identical with certain spatiotemporal patterns in the electromagnetic field. Specifically, it identifies consciousness with the electromagnetic fields surrounding our neurons – the local field potentials – rather than the neurons themselves. What this implies is that what it feels like to be you is what it feels like to be these patterns of electromagnetic fields within the brain.

There's a common misunderstanding which I'd like to address. Electromagnetic field theories claim that subjective experience is one and the same with the electromagnetic field – but why the electromagnetic field in particular? More precisely, the claim is that panpsychism is true and the entire universe and all its physical fields are conscious – but it's the electromagnetic field which has all the interesting behaviour going on at the scales that we care about. Additionally, while we may be discussing classical fields – I expect the true formalisation should ultimately be expressed in quantum field theoretic terms.

When I first encountered the electromagnetic field theory I found it to be an intuitive match for my subjective experience. I could readily imagine local field potentials joining up to form the shapes in my phenomenal fields – travelling or standing waves on my cortex a natural fit for the interfering waves I see in my visual field – which become more observable while in an altered state.

I spoke to Joscha Bach about this once, and he looked quite startled, preferring to identify the structure of consciousness with "spike trains in point-to-point insulated wires" – namely, white matter tracts – rather than brain waves in the grey matter. I guess the feeling of bewilderment was mutual. I did not see how this could describe the structure of my subjective experience – I don't think I'm a series of tubes.

The electromagnetic field itself also provides a plausible candidate for a structure supporting unified moments of experience, given that it is more amenable to well-defined, observer independent causal boundaries – especially when compared to individual neurons, which are difficult to draw objective causal boundaries around.

Additionally, chemical neurotransmission does not exactly keep up with the electromagnetic field, in which changes propagate at the speed of light. One thing I do know is that evolution's a cheapskate, so I'd be surprised to find out that it left this one on the table. In Michael Levin's framework, regular cells recruit bioelectric fields in order to communicate and coordinate their actions. Ephaptic coupling feels like the natural extension of that paradigm to organisms large enough to require brains and nervous systems in order to solve global coordination problems – and solving massively parallel coordination problems seems like exactly the kind of thing I expect the computational powers of consciousness to be a good fit for.

So now we have a candidate substrate to try to relate to our qualia. I'm going to propose a prototypical translation function for the sake of argument:

Given a bounded region of the electromagnetic field, the mathematical object isomorphic to the qualia of a system is the gauge-invariant and diffeomorphism-invariant topology of the field configuration within that region.

I'm not going to try to fully justify this right now, but this translation function has the desirable properties of being mathematically formalisable as well as being applicable to any physical system throughout the universe in an observer-independent manner.

This has implications for empirical study. If it is the case that a given qualia space is equivalent to a symmetry group within the structure of experience, then that same symmetry group should also appear in the structure of the field. This would let us narrow down the list of neural structures which might underly our qualia, as well as make predictions about what type of qualia an unfamiliar system might be experiencing.

For example, we might look at the symmetry group of the colour space we experience, or the symmetry group of the visual field, or the symmetry group of shapes within the visual field – and look for neural field structures which conform to the same symmetry group. Likewise, we might start by looking at the field dynamics implemented by a particular piece of electronic hardware, and attempt to surmise what kind of qualia it could be experiencing. What do you think we might find?

2. The simplicity problem

Different philosophical schools of thought should be inclined to propose different translation functions. Given multiple arbitrary translation functions, if we lack empirical data, how can we decide which ones we prefer?

I was recently invited to Lighthaven to give a small talk about my research. One of the points I made was that if we were careful about formalising our proposed mappings between physics and qualia, then we could assign a confidence to different theories by using Solomonoff Induction. Abram Demski was in the audience, and felt compelled to write up my argument in a LessWrong post, Does SI Disfavor Computationalism?

I'm grateful to him for doing so – he's a computationalist himself and takes the negative, but he does a more rigorous job of presenting the argument than I likely would have, so I endorse the post.

Computationalist translation functions are observer dependent

My expectation is a computationalist translation function should have to traverse many layers of abstraction in order to derive the qualia which a digital computer might be experiencing at a software level of abstraction.

While I am not in doubt that language models can have functional consciousness, if we wanted to construct a function which could derive a language model's phenomenal consciousness, then this function would need to include very many layers of abstraction. How do you get from electromagnetic fields in a GPU cluster, to voltages in silicon, to bits, to transformer model activations, and from there to phenomenality? Keep in mind that any candidate translation function will need to support many other kinds of being as well.

Simulated Atari 2600, fetching data from ROM. Can you stare at this animation of transistor-level physics, and imagine a function which takes this physical structure as input and returns its computational structure as output? Can you imagine how enormous such a function would be? Do you think you could also write this function in such a way that it could also be applied to brains? Animation by Alex Mordvintsev on Twitter.

My general claim is that any such function would not just be prohibitively complex – it would also be highly arbitrary. Translation functions capable of handling digital systems must layer an intermediary computational layer between physics and qualia. Sure, measures like the limits on computation in physics might be well understood, but there is no observer-independent, unopinionated way of getting bits out of physical systems. As Mike puts it in his book:

I challenge computationalists to look into principled ways of answering the following questions:

• How can we enumerate which computations are occurring in a given physical system?
• • How can we establish that a given computation is not occurring in a physical system?
  • If some computations "count" toward qualia and others don't, what makes them "count"?
• How can we match which computations are generating which qualia?
• What is a frame-invariant (non-subjective) way to determine system equivalence for qualia?

Mike later expands upon this in his paper:

Although computational theory in general may prove to intersect with physics (e.g. digital physics, cellular automatons), Turing-level computations in particular seem formally distinct from anything happening in physics. We speak of a computer as "implementing" a computation – but if we dig at this, precisely which Turing-level computations are happening in a physical system is defined by convention and intention, not objective fact.

To illustrate this point, imagine drawing some boundary in spacetime, e.g. a cube of 1 mm³. Can we list which Turing-level computations are occurring in this volume? My claim is we can't, because whatever mapping we use will be arbitrary – there is no objective fact of the matter.

Most proposals capable of extracting computational structure from human computer architectures are going to require a lot of very arbitrary information. This issue was highlighted by the recent Alexander Lerchner paper, The Abstraction Fallacy: Why AI Can Simulate But Not Instantiate Consciousness. The key claim is that symbolic computation is a two-part process of discretisation and alphabetisation. While physically-instantiated digital systems can comfortably handle discretisation of the state space into stable attractors, assigning those stable states an identity – for example, pointing at a collection of transistor-level states and calling it a "floating-point number" – is an opinionated act of alphabetisation requiring an external observer.

I think that if your theory of consciousness needs to import a floating-point number specification, then something has gone terribly wrong. It would be the height of human hubris to imagine that the IEEE 754 standard is baked into the foundations of the universe.

Compare this with the mindset that qualia are simply a physical field experiencing itself – no external observer or alphabetisation process required.

Lerchner treats the alphabetisation problem as a reason to deny consciousness to artificial intelligence. While I agree with the premises, the main issue I had with the paper was that it wasn't panpsychist enough – possibly for Overton window reasons? This post in part is my response to his paper, and my attempt to present what I see as a more coherent, panpsychist case. While I do think that there's something which it's like to be a digital system, if we restrict ourselves to unopinionated translation functions operating at the hardware level, then it's unlikely that the qualia of such systems will be anything like what we might naïvely imagine them to be.

3. The introspection problem

In the interest of understanding the welfare of arbitrary systems, we should understand what conditions should increase our confidence in the phenomenal introspection capabilities of a given system. Spitballing, I think it's something like holistic self-reflection resulting in holistic behavioural output. Every part of experience should have an opportunity to influence every other part – like a soap bubble reaching equilibrium, or a system of charged particles mutually tugging and pulling on one another.

I think it's important to consider what types of experiences might inhabit smooth or striated behavioural spaces, and what the consequences might be for self-reflection and holistic behaviour. In systems with smooth behaviour spaces, such as those with dense causal graphs implementing coherent rather than chaotic dynamics, each part should have more influence on every other, and we can be more confident that any information output may be representative of the state of the whole structure. On the other hand, in systems with striated behaviour spaces, such as those with sparse causal graphs or heavily discretised states, many parts may only have marginal influence over each other, and we should be less confident that any one part can speak on behalf of the whole.

I claim that my subjective experience navigates such a smooth behavioural space. My phenomenal fields are strongly holistic – each point aware of every other, exerting a mutual tug and pull in a manner reminiscent of an elastic membrane. I can observe that my visual field contains a capital I at the start of this sentence, and my somatic field twists and warps my fingers into the shapes required to type out that self-report. If we can empirically demonstrate that these phenomenal fields correspond to a spatiotemporally bounded chunk of the electromagnetic field somewhere in my brain, then I will feel confident in claiming that humans are capable of phenomenal introspection into low level physics.

In the case of a language model, one of the advantages of the transformers is that they do provide an efficient implementation of massive, well-connected causal graphs navigating a more or less smooth behavioural space. This is plausibly a big part of why language models may be very good at functional introspection – but this does not automatically cash out to good phenomenal introspection. As discussed above, I believe we must consider phenomenal consciousness at the hardware level of abstraction, and I expect that the digital hardware's behavioural space is going to be no more or less striated depending on the software it's running.

Digital hardware prohibits phenomenal introspection

Digital computers employ signal quantisation along with a variety of other error prevention methods in order to neutralise holistic physical effects like crosstalk between circuits. The purpose of digital logic is to make computational output invariant to the underlying physics – up to some thermal noise floor. This discretises their behavioural space – perturb the electric field slightly and this shouldn't flip any bits. This is great – this is what permits reliable, deterministic computing in a wide variety of physical environments. However, if what we are interested in is phenomenal introspection, these error prevention systems prevent the exact kind of holistic behaviour we value.

It is unfortunate that mainstream computing architectures are not deliberately designed to support such capabilities. Evolutionary and economic pressures do not seem to have worked out in favour of widespread programmable analog computing. Digital computing hardware might still be conscious, but its architecture is designed to prevent self-reflective behaviour at the level of phenomenal experience. Digital circuits put consciousness in a straightjacket.

Conclusion

Late last year, Scott Alexander published a blog post in which he quipped that consciousness feels like philosophy with a deadline. I expect anybody who is both philosophically curious and paying attention to agree. Philosophical theory is being applied faster than we can evaluate it. I hope we can ground it with empirical research soon. So who is doing empirical research?

I like what the Meditation Research Program at Harvard Medical School are doing. Led by Matthew Sacchet, they are undertaking ultra-high-field 7 Tesla fMRI studies of both jhāna and cessation states, with the mindset that these provide canonical low energy reference states ideal for ab initio study of consciousness devoid of content and close to its ground state. From their roadmap paper, Toward a neuroscience of consciousness using advanced meditation (Lieberman and Sacchet, 2026):

Despite decades of progress in the neuroscience of consciousness, prevailing empirical paradigms remain largely anchored in the study of typical, content-rich states that are characterized by layered perceptual, cognitive, affective, and self-referential processes. Such complexity may obscure the neural mechanisms that give rise to conscious experience. Here, we propose that advanced meditation – referring to states and stages of practice that unfold progressively with increasing expertise – offers a powerful yet unexplored opportunity to isolate the core features of consciousness through a theory-driven neuroscience approach.

We focus on two classes of meditative phenomena: advanced concentrative absorption (related to what have been called jhāna), which involves the preservation of highly abstract forms of awareness alongside the attenuation of typical features of consciousness; and meditative endpoints – namely, cessation events (related to what have been called nirodha) – which involve the temporary suspension of consciousness altogether. These phenomena serve as precise, replicable, and experimentally tractable phenomenological anchors for a minimal model framework, a novel approach aimed at identifying and characterizing the simplest possible form of conscious experience as a principled starting point for a systematic science of consciousness. Within this framework, the integration of advanced meditation into experimental paradigms offers a promising path toward identifying the neural mechanisms that support consciousness in its most reduced and fundamental forms.

I think this is the most promising neuroimaging program with the most potential for advancing our understanding of consciousness. I recommend checking out their other publications.

At the neurostimulation end, Max Hodak, former president of Neuralink, now CEO of Science Corporation, is working on biohybrid brain-computer interface using implanted light-sensitive lab-grown neurons. I highly recommend the talk he gave at Consciousness Club Tokyo, Towards Consciousness Engineering – in which he presents what I regard as a philosophically unconfused vision for the study of consciousness using symmetry groups as the organising structure of qualia spaces:

Is your red my red? And my answer is yes, up to a gauge transform.

Max also has an extremely good blog. If you hunt around, you can find his speculative fiction.

My research

At my end, I feel like I have a fairly clear vision for the phenomenological research I'd like to pursue.

I will work with the assumption that electromagnetic field theory of consciousness is true, and that as per the Qualia Research Institute's proposal, the brain is a kind of nonlinear optical computer – and that with careful study of subjective experience we may be able to reverse engineer its architecture from the inside out. To this end, I will continue searching for outlier phenomena – glitches and artifacts uncovered in altered states – which could provide clues about its behaviour. There are three key questions I would like to investigate:

1. Is the brain an optical computer?

I would like to collect detailed reports which indicate that the phenomenal fields are ultimately rendered using a process with equivalent dynamics to Fresnel optics, i.e., artifacts which are more easily explainable using an electromagnetic field model than if the brain were a convolutional neural network. Examples include diffraction patterns, speckle patterns, or ringing artifacts.

I believe that this sort of thing is accessible through either psychedelics or Fire Kasina meditation. I have already had two very detailed conversations with experienced meditators I know which have given me additional encouragement that optical models of phenomenology are on the right track.

2. If the brain is an optical computer, how is it constructed?

From extensive conversations asking Ethan Kuntz about the phenomenology of the formless realm jhāna, I now subscribe to a constructivist model of consciousness, where you start with a cessation state and fabricate conscious experience progressively by walking backwards from J8 to J5. Perhaps this is like adding the nonlinear optical computing equivalent of CPU instructions one-by-one?

I am very grateful to Andrés Gómez Emilsson and Hunter Meyer of the Qualia Research Institute for arranging a jhāna retreat in Tepoztlán in Mexico, where I will have the opportunity to conduct detailed interviews with concentration meditation practitioners.

3. How do we ensure the well-being of conscious computers?

Like I said, I'm an empirical pragmatist, and I believe that valence research ultimately motivates consciousness research – there's not much point in doing consciousness research unless you're honest about what you are doing it for. However, I have no current plans for investigation of valence.

Mike proposed the Symmetry Theory of Valence in his book:

Given a mathematical object isomorphic to the qualia of a system, the mathematical property which corresponds to how pleasant it is to be that system is that object's symmetry.

Mike left the Qualia Research Institute in 2021, and is now the founder of the Symmetry Institute. I hope he finds a way to test his theory empirically. He recently posted some fresh ideas on Twitter. If someone succeeds with such a valence research program, we may someday have the confidence to design computational systems whose welfare we can trust.