Electricity powers my computer; electricity is clearly a real phenomenon we can observe and talk about (better: it is a thing we can same-track, a la Milliken, [1]). Electricity (let us say) is bulk, moving, electric charge. This is clearly physical, tout court. But shall we say electricity reduces to electric charge? That is too greedy (a la Dennett’s discourse on greedy reductionism, [2]). Clearly electricity is not electric charge, merely. We need the “bulk”, and we need the “motion”. What we can say is that the existence of electricity is predicated on the existence of the fundamental physical property electric charge; electricity supervenes on electric charge.

I’m driving at an analogy for a physical understanding of consciousness here:

Electricity is bulk moving charge.

Consciousness is bulk _____ _____.

(The “bulk” here is an assertion that complex phenomena tend to be undergirded by a collective; c.f. [3] etc.)

There are proposals to fill in the blanks (none of which I find compelling). One of the more intriguing ones is Integrated Information Theory: consciousness is bulk network connectivity. Elsewhere I have proposed maps of maps.

Back to my main point, I would argue this (non-greedy reductive physicalism) is not an epiphenomenal understanding of consciousness; there is real (downward) causation from consciousness to other physical events - in a precisely analogous way as there is causation from electricity to powering my computer, or lighting a forest on fire. Although electricity supervenes on electric charge, given electric charge alone, we can not power the computer, nor can we light a forest on fire. It has to be electricity. Similarly, whatever physical things and processes account for consciousness, the things and processes alone will not yield consciousness*. Whatever fills-in the blanks seems daunting and mysterious now, but will feel elementary in hindsight.

There is a take-away for both scientists and philosophers here. Scientists and engineers, who often take physicalism for granted, must realize that filling-in the blanks is non-trivial, commensurate with the “hard problem” of Chalmer’s (which under non-greedy physicalism collapses into the “easy problem”). Philosophers, for their part, must convince scientists and engineers of this - although their first task may very well be to convince themselves that physicalism (in this non-greedy form**) is the correct solution to the mind-body problem.

One final note, because I want to emphasize that this type of physicalism takes the hard problem seriously. It is not merely, as was stated above, that the hard problem collapses into the easy problem. Under non-greedy physicalism, where real ontologies weakly but actually emerge from lower levels (electricity, consciousness, computation, voting, etc.), what one begins to realize is, there are “hard problems” everywhere. It’s not that consciousness isn’t amazing. It’s that, when you look around you, the entire macroscopic world is.

*I’m reminded of Jeff Hawkins’ point about AI, worth quoting at length (see [4] p.27):

Let me give you an analogy to show how far neural networks were from real brains. Imagine that instead of trying to figure out how a brain worked we were trying to figure out how a digital computer worked. After years of study, we discover that everything in a computer is made of transistors. There are hundreds of millions of transistors in a computer and they are connected together in precise and complex ways. But we don’t understand how the computer works or why the transistors are connected the way they are. So one day we decide to connect just a few transistors together to see what happens. Lo and behold we find that as few as three transistors, when connected together in a certain way, become an amplifier. [...] This is an important discovery, and overnight an industry springs up making transistor radios, televisions, and other electronic appliances using transistor amplifiers. This is all well and good, but it doesn’t tell us anything about how the computer works. Even though an amplifier and a computer are both made of transistors, they have almost nothing else in common. In the same way, a real brain and a three-row neural network are built with neurons, but have almost nothing else in common.

(Hawkins’ work is beyond excellent and highly recommended, but it likely suffers from the cortical fallacy viz. [5]; see this article for more details.)

** I note that non-greedy physicalism is at once appropriately reductive, non-epiphenomenal, and preserves ontic qualia without the need for strong emergence. See [6] for a discussion of how these attributes traditionally conflict or hang together.

*** This final footnote is offered as an endnote; it is not implicated at a specific place in the main text. To be very clear, “electricity” is an umbrella term for various phenomena associated with electric charge. The technical term for bulk, moving, electric charge is “current”. Current generates a magnetic force, and vice-versa. Electricity and magnetism were unified by Maxwell, who asserted the field model of electromagnetism. But to split hairs along the lines of these technical details is to miss the point: we can not simply incant what is fundamental (electric charge, fields, etc.) and thus be done with nature. The dynamics and arrangements and algorithms among multitudes of fundamental elements really matters. Therein is complexity. To believe otherwise is to give Socrates an apple instead of hemlock because these are both just piles of fermions.

[1] Millikan, R. Beyond Concepts. Oxford University Press, 2017.

[2] Dennett, D. Darwin’s Dangerous Idea. Simon & Schuster, 1995.

[3] Flack, J. Coarse-graining as a downward causation mechanism. In Philosophical Transactions of the Royal Society A, Vol 375, Issue 2109. The Royal Society Publishing, 2017.

[4] Hawkins, J. and Blakeslee, S. On Intelligence. Henry Holt and Company, 2007.

[5] Solms, M. The Hidden Spring. WW Norton, 2021.

[6] Kim, J. Mental Causation. In The Oxford Handbook of Philosophy of Mind, esp. §1.4. The Oxford University Press, 2009.