ARGUMENT FOR A HOLISTIC CONCEPT OF CONSCIOUSNESS AND PERCEPTION THROUGH DATA SCIENCE

The nature of mind, consciousness, and perception and even the concept of “life” are ultimately philosophical and not scientific problems even for an analytic philosophy naturalized to science. These concepts are not ontological problems but epistemic and normative problems of what one ought or should believe or know about human behavior, for instance: 1) what is the difference between being conscious and being alive (arguably, a brain in a vat is alive, but is it conscious? A zombie is arguably conscious, but is it alive? Which can I kill morally, if either?).

Wittgenstein in his Philosophical Investigations at §281 warned: “… that only of a living human being and what resembles (behaves like) a living human being can one say: it has sensations; it sees; is blind; hears; is deaf; is conscious or unconscious”. All arguments that I have seen so far violate or ignore this warning by arbitrarily creating aesthetic concepts such as percepts, qualia, working memory, iconic memory, psychological states, and similar creations that are then converted into reductionist empirical concepts through experiments predetermined to confirm and enforce the arbitrarily created aesthetics. After presenting a general conceptual foundation of the problems at issue, I will analyze these aesthetic concepts, particularly the concept of qualia, as exemplifications of the fallacious nature of the brain/body duality. Consciousness and perception exist only holistically in the whole person or in the “living human being and what resembles (behaves like) a living human being” and not in any part of the whole.

II.   Being Naturalized to Science Does Not Require a Romantic View of Science.

“Don’t ape the natural sciences” is the physicists Alan Sokal and Jean Bricmont’s admonition in their book Fashionable Nonsense to post-modernist philosophy that could just as well be directed to analytic philosophy. However, part of the responsibility for such “aping” comes from their own and from scientists’ almost universe pontification: “most importantly, the aim of science is not only to predict but also to understand”. The aim of all human language not aimed at confusion is to provide understanding, regardless of whether it is the gibberish of Lewis Carroll’s Jabberwocky, the existential reality of Tolstoy’s War and Peace, “the gods of Homer”, The Beatitudes, Thucydides’ History of the Peloponnesian War, The Myth of Sisyphus, mathematics, or physics — any and all human language, even that of confusion, is in some way directed to achieving an understanding of what would make humans happy or at least create happiness in one’s life. What makes scientific language special and unique and that creates a desire to be naturalized to it as a means to achieve happiness is its predictive meaning:

   As an empiricist I continue to think of the conceptual scheme of science as a tool, ultimately, for predicting future experience in the light of past experience. Physical objects are conceptually imported into the situation as convenient intermediaries — not by definition in terms of experience, but simply as irreducible posits comparable, epistemologically, to the gods of Homer. Let me interject that for my part I do, qua lay physicist, believe in physical objects and not in Homer’s gods; and I consider it a scientific error to believe otherwise. But in point of epistemological footing the physical objects and the gods differ only in degree and not in kind. Both sorts of entities enter our conception only as cultural posits. The myth of physical objects is epistemologically superior to most in that it has proved more efficacious than other myths as a device for working a manageable structure into the flux of experience.

In science, concepts are created and revised “to maximize success in prediction: future coverage of true observation categoricals”. — both quotes by the philosopher Willard V.O. Quine.

An example of the omnipresence in philosophy of mind of philosophers falling into a romantic view of science that creates delusion and distorts their reasoning is David Chalmers’ “How can we construct a science of consciousness” in which he states that in a science of consciousness “[b]oth third-person data and first-person data need explanation”; as an example of the “explanation” needed, he refers to the “explanation of genetic phenomena” achieved when “Watson and Crick isolated a mechanism that would potentially perform this function: the DNA molecule …”. Sounds nice, but his example of “explanation” disproves his own argument. The reality is that biologists including Watson and Crick call their “explanation” consisting of an irreversible process in which DNA makes RNA makes protein a “Central Dogma of Molecular Biology” that was created for pragmatic reasons not for descriptive reasons; Watson and Crick called it dogma because like religious dogma it “was more central and more powerful” than a hypothesis, it was “a grand hypothesis that, however plausible, had little direct experimental support”. Through the Dogma, the concept of a gene that “[t]o the early geneticists … was an abstract entity” became a physical entity in a cause and effect deductive-homological explanation — the type of theory beloved by philosophers — filling the theoretic void existing in the workings of the probabilistic-statistical predictions generated by Mendelian genetics with its messy correlations lacking any cause and effect explanations and with their predictive truths phrased in probabilities that by definition are a means to deal with ignorance not knowledge.

Or did it? Almost immediately, “anomalous findings” appeared using the Dogma and “[m]ost biologists, when pushed, do agree that there is not enough information in any genome capable of mapping out the details by which morphological structure arise in organisms”. “As we all know, once cracked, that [genetic code] of life did not lead to a fundamental explanation of gene expression … . The code seemed to be merely an arbitrary correspondence table … ”. “To date, even with many studies of very large samples, the overall bulk control of the genetic control of … traits, as measured by heritability or familial aggregation, remains unexplained …”. Biologists complain that with acceptance of the Dogma, “biology’s holistic problems, which were not commensurate with the new molecular perspective, would remain relatively or completely undeveloped”; “[t]he consensus around the gene as ultimate control agent has had the additional effect of diminishing the concept of the organism in experimental biology”. Furthermore, epigenetics has challenged the Dogma by discovering evidence that environment can violate the irreversible attribute of the Dogma and even change inheritable traits directly, something that is supposed to be a genetic impossibility. In short, Chalmers’ exemplar DNA “explanation” is better described as a simplification of reality exceeding that of the simplification of Newton’s Laws but whose popularity is negating predictive progress in biology.

As a resolution for such complaints, biologists are calling for holistic replacements of the gene concept by a view that “organisms are systems” having Quine’s intertwined fabric of knowledge in which genes are treated as just a part of functioning networks even though “[b]y treating [gene] networks as causal units, however we risk simply replacing the old ‘gene for’ concepts with a new platonic entity — a ‘network for’ concept’”. Other options called for by biologists vary from: 1) a return to holistic “organismal biology” treating the holistic “organism” as more than a “collection of genes”; 2) to the other end of the option spectrum consisting of a simple instrumental “breeder’s goal of manipulating them [genes]”. In short, the more we learn about biology, the more complex it gets, and the further away we are from the “explanation” exalted by Chalmers as the goal of a science of mind and of any philosophy of mind naturalized to it. The exalted DNA “explanation” is quickly “becoming epistemologically vacuous” with genes defined or equated by some biologists as no more than the mathematical algorithms or computer subroutines used to correlate the massive amount of data for physical traits with the equally massive amount of data that makes up DNA.

None of this anarchic lack of explanation, confusion, contradicting theory, or theoretical or empirical messes bothers scientists especially experimental scientists; in fact, it is science as philosophers of science Karl Popper, Norwood Russel Hanson, Thomas Kuhn, Paul Feyerabend, Imre Lakatos, and many others have extensively written. Issues of explanation, though important to philosophers, “are not always discussed by biologists, who often feel they can move ahead in a de facto way without worrying about philosophy or terminology”. None of this lack of explanation adversely or otherwise affects the predictive meaning of the science of genetics that Chalmers wants explained. Its statistical analysis and probability lacking cause and effect explanation still works essentially in the same way as Mendel’s methodology of the 1860’s. “In 1911, Karl Pearson, inventor of the correlation coefficient, dismissed causation as ‘another fetish amidst the inscrutable arcana of even modern science’”. Bertrand Russell stated that “‘[t]he law of causality,’ he said with a flourish, ‘like much that passes muster among philosophers, is a relic of a bygone age, surviving, like the monarchy, only because it is erroneously supposed not to do harm’”. As early as 1909, at the beginning of his career, Albert Einstein was arguing for probabilistic theories to supercede causal explanations in physics; an opinion that he might have rejected mid-career but to which he arguably returned later in his career. As Quine’s student Catherine Z. Elgin has stated, any anarchy in science most certainly does “make the world safe for postmodernist claptrap” but uses its creativity to use not only truth but also falsehoods to achieve scientific knowledge consisting of predictive meaning through such language games in its methodology as “curve smoothing”; “ceteris paribus claims”; “idealizations”; “stylized facts”; “a fortiori arguments from limiting cases”; and even models made up of “fiction” to serve the epistemic meaning and goals of scientific truth (i.e., the ideal gas law).

A science of consciousness and perception as with genetics and most modern science does not need explanation to solve the problems it is trying to solve or to which it is trying to give predictive meaning — problems varying from Alzheimer’s Disease to Parkinson’s Disease and onto schizophrenia. Conceptualizing the vast amounts of data available on these diseases mathematically first through correlation without worrying about causation should be the first option; aesthetically pleasing explanations should be a later concern if at all. (I will give an example of such a science of consciousness further on in this essay). Ultimately, “[s]ince all models are wrong the scientist cannot obtain a ‘correct’ one by excessive elaboration. On the contrary following William of Occam he should seek an economical description of natural phenomena. Just as the ability to devise simple but evocative models is the signature of the great scientist so overelaboration and overparameterization are often the mark of mediocrity”.

If neuroscience and cognitive science do not need explanation, what do they need? Do they need philosophy to create the concepts of qualia, percepts, and similar?

III.   A Science of Consciousness

The scientific concept of “energy” had a humble beginning in Ancient Greek Philosophy as the abstract concept energeia useful for a meaning similar to our words of ‘activity’ and ‘operation’. Eventually, through the usefulness of this concept in correlating experimental results in thermodynamics, then mechanics, and then all of physics, its various progeny (potential, kinetic, chemical, electrical, thermal, and much more) are the substance of the universe. However, “‘It is important to realize that in physics today we have no knowledge of what energy is’, said Richard Feynman in his Lectures in the Sixties. ‘Nobody knows what energy really is’ can be read in Bergmann and Schaefer’s Experimental Physics, 1998”. Entropy has an even more humble or infamous beginning; it is essentially a name given to the unexplainable remainder occurring in thermodynamics equations. No one knows what entropy is, yet it is in anything that wants to call itself a science. Information science is illustrative:

   I thought of calling it “information”, but the word was overly used, so I decided to call it “uncertainty”. […] Von Neumann told me, “You should call it entropy, for two reasons. In the first place your uncertainty function has been used in statistical mechanics under that name, so it already has a name. In the second place, and more important, nobody knows what entropy really is, so in a debate you will always have the advantage.

  — Conversation between Claude Shannon and John von Neumann regarding what name to give to the attenuation in phone-line signals.

“Science is essentially an anarchic enterprise: theoretical anarchism is more humanitarian and more likely to encourage progress than its law-and-order alternatives”.

Recently, I submit, in a similar humble beginning, data science has unintentionally given us a realistic example of a science of consciousness. Data science was and is able to do so because it is not corrupted by any brain/body duality and thus is free to do its correlations not only on the whole person but on the whole of which we are conscious and that we perceive. More accurately, it has given us an example of a science of impaired consciousness, but it can serve as a model of what Chalmers and philosophy of mind should really be aiming at as a science of consciousness. In their paper “Psychomotor function measured via online activity predicts motor vehicle fatality risk”, three data scientists trying to create predictability for impairments of consciousness that result in vehicle accidents have empirically created a model of impaired perception capable of giving predictive meaning in a wide variety of situations. By using data science algorithms correlating 16 billion observations of typing speeds during the input of web search queries, they were able to find a strong correlation at the general population level between the speed and accuracy of typed web search queries and motor vehicle fatalities. Their model, as did the statistics and probability of genetics in relation to heredity, has created a wordgame determining when someone’s consciousness and perception are too impaired to drive and will lead to diagnostics for creating driving fitness tests and for non-intrusive driver monitoring that are independent and that work regardless of the cause of impairment of consciousness and perception: lack of sleep, alcohol, drugs, anxiety, depression, visual or audio distractions, and so forth. Impaired perception caused by alcohol alone causes about 10,000 motor vehicle accident fatalities a year. This type of model of impaired consciousness may not be pretty but no one should care as long as it works; we can worry about an “explanation” for its predictive value some other time. Science can do the same for other impaired consciousness including Alzheimer’s Disease, Parkinson’s Disease, schizophrenia, and similar by looking at the holistic whole of the person and their complete complex environment and not just the brain.