Category Archives: Philosophy of Science

Genuinely Creative Thought

2.2 The evolution of the mind: consciousness, creativity, psychological indeterminacy

If consciousness is accepted as real, it seems reasonable that one would allow for an active consciousness, for us to be aware of the experience of thinking and to engage in that experience. If we didn’t allow for engaged and active thought in consciousness, then consciousness would seem to be a passive “ghost in the machine” sort of consciousness. Siegel (2016) would appear to be in agreement with this notion insofar as he sees the mind as a conscious regulator of energy and information flow. But if we allow consciousness to be real in this manner, we allow the possibility of thoughts which exist for no reason other than “we” (the phenomenological “I” (Luijpen, 1969)) think them consciously and actively. The existence of such a thought does not itself break the principle of sufficient reason (Melamed and Lin, 2015), but the “I” thinking them might. That the “I” brings into being a conscious thought might be the terminus of a particular chain of causation. (Markey-Towler 2018, 8)

We call such thoughts to exist “genuinely creative thought”, they are thoughts which exist for no reason other than they are created by the phenomenological “I”. The capability to imagine new things is endowed by the conscious mind. This poses a difficulty for mathematical models which by their nature (consisting always of statements A ⇒ B) require the principle of sufficient reason to hold. Active conscious thought, insofar as it may be genuinely creative is indeterminate until it exists. However, that we might not be able to determine the existence of such thoughts before they are extant does not preclude us from representing them once their existence is determined. Koestler (1964) taught that all acts of creation are ultimately acts of “bisociation”, that is, of linking two things together in a manner hitherto not the case. Acts of creation, bisociations made by the conscious mind, are indeterminate before they exist, but once they exist they can be represented as relations Rhh’ between two objects of reality h,h’. We may think of such acts of creation as akin to the a priori synthetic statements of which Kant (1781) spoke. (Markey-Towler 2018, 8)

This is no matter of mere assertion. Roger Penrose (1989) holds, and it is difficult to dismiss him, that the famous theorems of Kurt Gödel imply something unique exists in the human consciousness. The human mind can “do” something no machine can. Gödel demonstrated that within certain logical systems there would be true statements which could not be so verified within the confines of the logical system but would require verification by the human consciousness. The consciousness realises connections in this case truth-values which cannot be realised by the machinations of mathematical logic alone. It creates. The human mind can therefore (since we have seen those connections made) create connections in the creation of mathematical systems irreducible to machination alone. There are certain connections which consciousness alone can make. (Markey-Towler 2018, 9)

The problem of conscious thought goes a little further though. New relations may be presented to the consciousness either by genuinely creative thought or otherwise, but they must be actually incorporated into the mind, Rhh’g(H)μ and take their place alongside others in the totality of thought g(H)μ. Being a matter of conscious thought by the phenomenological “I”, the acceptance or rejection of such relations is something we cannot determine until the “I” has determined the matter. As Cardinal Newman demonstrated in his Grammar of Assent (1870), connections may be presented to the phenomenological “I”, but they are merely presented to the “I” and therefore inert until the “I” assents to them accepts and incorporates them into that individual’s worldview. The question of assent to various connections presented to the “I” is an either/or question Newman recognises is ultimately free of the delimitations of reason and a matter for resolution by the “I” alone. (Markey-Towler 2018, 9)

There are thus two indeterminacies introduced to any psychological theory by the existence of consciousness:

1 Indeterminacy born of the possibility of imagining new relations Rhh’ in genuinely creative thought.
2 Indeterminacy born of the acceptance or rejection by conscious thought of any new relation Rhh’ and their incorporation or not into the mind μg(H). (Markey-Towler 2018, 9)

The reality of consciousness thus places a natural limit on the degree to which we can determine the processes of the mind, determine those thoughts which will exist prior to their existence. For psychology, this indeterminacy of future thought until its passage and observance is the (rough) equivalent of the indeterminacy introduced to the physical world by Heisenberg’s principle, the principle underlying the concept of the “wave function” upon which an indeterminate quantum mechanics operates (under certain interpretations (Kent, 2012; Popper, 1934, Ch.9)). (Markey-Towler 2018, 9-10)

2.3 Philosophical conclusions

We hold to the following philosophical notions in this work. The mind is that element of our being which experiences our place in the world and relation to it. We are conscious when we are aware of our place in and relation to the world. We hold to a mix of the “weak Artificial Intelligence” and mystic philosophies that mind is emergent from the brain and that mind, brain and body constitute the individual existing in a monist reality. The mind is a network structure μ = {H g(H)} expressing the connections g(H) the individual construes between the objects and events in the world H, an architecture within which and upon which the psychological process operates. The reality of consciousness introduces an indeterminacy into that architecture which imposes a limit on our ability to determine the psychological process. (Markey-Towler 2018, 10)

~ ~ ~

My own philosophical views differ from the assumptions underlying Markey-Towler. To say that “mind is emergent from the brain and that mind, brain and body constitute the individual existing in a monist reality,” is essentially a form of physical monism that claims mind “emerged” from matter, which really explains nothing. If the universe (and humans) are merely mechanisms and mind is reducible to matter we would never be able to be aware of our place in and relation to the universe nor would there ever be two differing philosophical interpretations of our place in the universe. The hard problem (mind-brain question) in neuroscience remains a debated and unsettled question. There are serious philosophical weaknesses in mechanistic materialism as a philosophical position, as is discussed in Quantum Mechanics and Human Values (Stapp 2007 and 2017).

Social Science as Sorcery

There are four chief obstacles to grasping truth, which hinder every man, however learned, and scarcely allow anyone to win a clear title to knowledge; namely, submission to faulty and unworthy authority, influence of custom, popular prejudice, and concealment of our own ignorance accompanied by an ostentatious display of our knowledge.

— Roger Bacon cited in Stanislav Andreski, Social Sciences as Sorcery

[W]hat we have to deal with in the study of society and culture, indicates its purely intellectual difficulties, and shows how much easier are physics, chemistry or even biology. Even this, however, is not the whole story: for imagine how sorry would be the plight of the natural scientist if the objects of his inquiry were in a habit of reacting to what he says about them: if the substances could read or hear what the chemist writes or says about them, and were likely to jump out of their containers and burn him if they did not like what they saw on the blackboard or in his notebook. And imagine the difficulty of testing the validity of chemical formulae if, by repeating them long enough or persuasively enough, the chemist could induce the substances to behave in accordance with them — with the danger, however, that they might decide to spite him by doing exactly the opposite. Under such circumstances our chemist would not only have a hard time trying to discover firm regularities in his objects’ behaviour but would have to be very guarded in what he said lest the substances take offense and attack him. His task would be even more hopeless if the chemicals could see through his tactics, organize themselves to guard their secrets, and devise counter-measures to his maneouvres — which would be parallel to what the student of human affairs has to face. (Andreski 1973, 20-21, in Social Sciences as Sorcery)

There is no reason to deny the existence of phenomena known to us only through introspection; and a number of philosophers have pointed out the impossibility of carrying out Carnap’s programme (accepted as a dogma by the behaviourists) of translating all statements about mental states into what he calls the physicalist language. I would go even further and agrue that physics itself cannot be expressed in the physicalist langauge alone because it is an empirical science only insofar as it includes an assertion that its theories are corroborated by the evidence of the senses; and we can assign no meaning to the latter term without entailing a concept of self…. Thus you cannot give an account of the evidential foundations of physics without hearing and uttering ‘I’. And what kind of meaning can you attach to this word without using the knowledge obtained through introspection; and without postulating the existence of other minds within which processes are taking place which are similar to those which you alone can observe? (Andreski 1973, 21-22, in Social Sciences as Sorcery)

At this point let me say a few words about the often debated question whether any of the social sciences is a ‘real’ science. As often happens with such debates the arguments for as well as against omit the obvious truth that the answer to this question will depend on what we mean by science. If we mean exact science like physics or chemistry, then neither economics nor psychology nor sociology nor any other kind of research into human conduct is a science [, which obviously includes economics]. But if we agree to affix this honorific label to any kind of systematic study which aims at providing careful descriptions, substantiated explanations and factually supported generalizations, then we can say that the above mentioned branches of learning are sciences — although the propriety of this appellation will depend on whether we decide on the basis of aspirations or actual performance, and whether we look at the average or at the highest achievements. (Andreski 1973, 22-23, in Social Sciences as Sorcery)

Though formidable enough, the methodological difficulties appear trivial in comparison with the fundamental obstacles to the development of an exact science of soceity which puts it on an entirely differnt plane from the natural sciences: namely the fact that human beings react to what is said about them. More than that of his colleagues in the natural sciences, the position of an ‘expert’ in the study of human behaviour resembles that of a sorcerer who can make the crops come up or the rain fall by uttering an incantation. And because the facts with which he deals are seldom veifiable, his customers are able to demand to be told what they like to hear, and will punish the court physicians for failing to cure them. Moreover, as people want to achieve their ends by influencing others, they will always try to cajole, bully or bribe the witch-doctor into using his powers for their benefit and uttering the needed incantation … or at least telling them something pleasing. And why should he resist threats and tempations when in his specialty it is so difficult to prove or disprove anything, that he can with impunity indulge his fancy, pander to his listeners’ loves and hates or even peddle conscious lies. His dilemma, however, stems from the difficulty of retracing his steps; because very soon he passes the point of no return after which it becomes too painful to confess that he has been taking advantage of the public’s gullibility. So, to allay his gnawing doubts, anxieties and guilt, he is compelled to take the line of least resistance by spinning more and more intricate webs of fiction and falsehood, while paying ever more ardent lip-service to the ideas of objectivity and the pursuit of truth. (Andreski 1973, 24, in Social Sciences as Sorcery)

So to examine the validity of the claim that these are highly useful branches of knowledge, let us ask what their contribution to mankind’s welfare is supposed to be. To judge by the cues from training courses and textbooks, the practical usefulness of psychology consists of helping people to find their niche in society, to adapt themselves to it painlessly, and to dwell therein contentedly and in harmony with their companions. [We can ask the same question about economics.] So, we should find that in countries, regions, institutions or sectors where services or psychologists [and economists] are widely used, families are more enduring, bonds between spouses, siblings, parents and children stronger and warmer, relations between colleagues more harmonious, the treatment of recipients of aid better, vandals, criminals and drug addicts fewer, than in places or groups which do not avail themselves of the psychologists’ skills. On this basis we could infer that the blessed country of harmony and peace is of course the United States; and that it ought to have been becoming more and more so during the last quarter of the century in step with the growth in numbers of sociologists, psychologists [, economists] and political scientists. (Andreski 1973, 26, in Social Sciences as Sorcery)

The self-fulfilling prophecy constitutes only one (and fairly narrow) manifestation of the much more general disposition of human beings to be influenced by what is said about them and their environment. On the individual plane everybody knows that one can make a person discontented by deploring the circumstances under which he lives, encourage his endeavour by praise, or discourage it by sarcasm…. [I]f we show that the idea that ‘honesty is the best policy’ is groundless we remove an important incentive to honesty. (Andreski 1973, 31, in Social Sciences as Sorcery)

Even such purely academic theories as interpretations of human nature have profound practical consequences if disseminated widely enough. If we impress upon people that science has discovered that human beings are motivated only by the desire for material advantage, they will tend to live up to this expectation, and we shall have undermined their readiness to moved by impersonal ideals. By propagating the opposite view we might succeed in producing a larger number of idealists, but also help cynical exploiters to find easy victims. This specific issue, incidentally, is of immense actual importance, because it seems that the moral disorientation and fanatic nihilism which afflict modern youth have been stimulated by the popular brands of sociology and psychology [and economics] with their bias for overlooking the more inspiring achievements and focusing on the dismal average or even the subnormal. When, fraudulently basking in the glory of the exact sciences, the psychologists [, theoretical economists, etc.,] refuse to study anything but the most mechanical forms of behavior often so mechanical that even rats have no chance to show their higher faculties and then present their mostly trivial findings as the true picture of the human mind, they prompt people to regard themselves and others as automata, devoid of responsibility or worth, which can hardly remain without effect upon the tenor of social life. (Andreski 1973, 33-34, in Social Sciences as Sorcery)

Abstrusiveness need not impair a doctrine’s aptness for inducing or fortifying certain attitudes, as it may in fact help to inspire awe and obedience by ‘blinding people with science’. (Andreski 1973, 35)

If the rank and file come to be convinced that the leaders are crooks, cowards or fools, their actions will differ radically from what would be, were they convinced that the leaders are dedicated men of great courage and intelligence. Conversely, the leaders’ behaviour will to some extent depend on the popular image of their office, which will determine whether the latter carries with it the dignity which they are expected to live up to, or whether they will have no reputation to preserve. (Andreski 1973, 36, in Social Sciences as Sorcery)

The difficulty of verifying assertions about human relations gives wide scope to ulterior motives, and provides immunity for the purveyors of false information. (Andreski 1973, 38, in Social Sciences as Sorcery)

If you listen to the practitioners of social and economic research talking informally, you will easily find that not only are they very well aware of the aforementioned [social status and economic gain] pressures, but also that they fully take them into account in making plans and arrangements about what to study, to write, or to say. This, however, happens on the everyday bread-and-butter level, while neither their pronouncements ex cathedra nor their publications ever mention that these pressures might make a difference to the trustworthiness of the results of social research, and to the prospects of its ever attaining the level of objectivity and reliability of the natural sciences. (Andreski 1973, 39, in Social Sciences as Sorcery)

To summarize: the propensity of human objects of inquiry to react to what is said about them creates three kinds of obstacles to the development of the social sciences. The first is of a methodological nature and consists of the difficulties surrounding the task of verifying propositions which can influence the happenings which they purport merely to describe or analyse. The second kind of impediment stems from the presures upon the direction of the inquiry and the dissemination of its results, motivated firstly by the awareness that what is said might influence what will happen; and secondly by the desire … to hear what pleases them. The disarray wrought by the operation of the two aforementioned factors prduces the third kind of impairment in the shape of ample opportunities for getting away with falsehoods and crypto-propaganda. (Andreski 1973, 39-40, in Social Sciences as Sorcery)

Once an activity becomes a profession — this is, a way of making a living — the dedicated amateurs tend to fall into second place, greatly outnumbered by the practitioners guided primarily (if not soley) by the normal motives of the market place — which commonly boil down to the desire to get the most at the least cost to themselves. In other words, as soon as it becomes apparent that there is money in it, the saleability of goods rather than their intrinsic excellence becomes the dominant criterion. (Andreski 1973, 43, in Social Sciences as Sorcery) [i.e., literature-only economics; see Payson 2017.]

If everything is wonderfully dovetailed and adjusted, then we should leave things alone. More insidiously than nineteenth century organicism, functionalism propagates a conservative ideology in the name of science; while, for those things its practitioners do not like, they have the aforementioned epithet ‘dysfunctional’, which enables them to insinuate a condemnation without openly saying so, and to enlist the authority of science for their ideologies or personal preferences. For if somebody says that something is good or bad, he might be asked: for what?, or for whom?, or why? So he might be obliged to take off the mask of objective omniscience and to reveal, firstly, his values and, secondly, the reasons for his assumptions about the likely consequences of various arrangements or courses of action; whereas by using ‘functional’ and ‘dysfunctional’ instead of ‘good’ and ‘bad’, a functionalist can hide behind a façade of objectivity and invoke the magic of science to back his crypto-propagandist insinuations. (Andreski 1973, 57-58, Social Science as Sorcery)

Anreski’s letter to editor

The article to which I referred in my letter supplied one or more of the innumerable instances of that ever-popular kind of explanation which consists of a tautological rephrasing which tells us nothing that we did not understand before. An explanation which Moliere ridiculed three hundred years ago in one of his plays, where one of the characters answers the question about why opium makes people sleep by saying that it is because of its soporific power. In historiography and social sciences this kind of explanation crops up again and again. Thus, to take an example of a great scholar who luckily did not confine himself to this, Werner Sombart attributed the development of capitalism to the spread of ‘the spirit of capitalism’, without telling us how we could find out that this spirit was spreading except by observing activities which add up to the process known as the development of capitalism. (Andreski 1973, 68, in Social Science as Sorcery)

The attraction of jargon and obfuscating convolutions can be fully explained by the normal striving of humans for emoluments and prestige at the least cost to themselves, the cost in question consisting of the mental effort and the danger of ‘sticking one’s neck out’ or ‘putting one’s foot in it’. In addition to eliminating such risks, as well as the need to learn much, nebulous verbosity opens a road to the most prestigious academic posts to people of small intelligence whose limitations would stand naked if they had to state what they have to say clearly and succinctly. Actually, the relationship between the character of a jargon-mongerer and the amount of his verbiage can be expressed in the formula below, which can be applied in the following manner. The first step is to assign intuitively estimated scores for an author’s ambition, designated by A, and to knowledge, designated by K (which must always be greater then 0, as nobody knows exactly nothing). A must also be positive because, if somebody’s literary ambition is nil, they he writes nothing, and there is nothing to apply our equation to. V stands for verbose jargon. Our equation is

Verbosity Formula

Why I? Because when the knowledge matches the ambition there is no verbiage. When knowledge exceeds the ambition V becomes negative; and negative verbiage amounts to conciseness. However, since there is a limit to conciseness, V can never become less than I; whereas there is not limit to verbiage, and so V increases indefinitely as ambition grows, while knowledge vanishes. (Andreski 1973, 82-83, Social Science as Sorcery)

Our formula cannot, of cours be treated as exact until measurable indices are devised for the variables, and then checked against empirical data. I do believe, however, that it is approximately true, and I invite readers to try it on the authors they read as well as on their colleagues, teachers or students. Its predictive and explanatory power is roughly the same as that of most theorems of mathematical economics. The many different kinds of people, ranging from an undergraduate who is trying to scrape through a dissertation without having learned anything, to a scholar with a fairly extensive knowledge but devoured by a craving for greatness. (Andreski 1973, 83, Social Science as Sorcery)

If you happen to be a student, you can apply the same test to your teachers who claim that what they are teaching you rests upon incontrovertible scientific foundations. See what they know about the natural sciences and mathematics and their philosophical foundations. Naturally, you cannot expect them to have a specialist knowledge of these fields; but if they are completely ignorant of these things, do not take seriously grandiloquent claims of the ultra-scientific character of their teachings. Furthermore, do not be impressed unduly by titles or positions. (Andreski 1973, 86, in Social Science as Sorcery)

As has often been said, measurement is the beginning of science (if we mean thereby exact science) because our ability to predict the behaviour of a phenomenon must remain very restricted until we can measure it. It does not follow, however, that no knowledge whatsoever is possible without measurement, nor that such knowledge cannot be worth having — which is precisely the conclusion which … many sociologists [and economists] have adopted in the mistaken belief that only thereby can they maintain the scientific character of their discipline. But the true scientific spirit consists of trying to obtain the nearest approximation to truth which is possible under the circumstances, and it is puerile to demand either perfect exactitude or nothing. those who refuse to deal with important and interesting problems simply because the relevant factors cannot be measured, condemn the social sciences to sterility, because we cannot get very far with the study of measurable variables if these depend on, and are closely interwoven with, immensurable factors of whose nature and operation we know nothing. A weakness of this kind diminishes the usefulness of economic theory … because it excludes from its universe of discourse immensurable but causally crucial factors … such as the balance of political power … or simply relegating them to the category of those things which are treated as ‘being equal’. (Andreski 1973, 123, in Social Science as Sorcery)

To substantiate their claims, the advocates of an exclusive concentration on quantification ought to demonstrate either that [political] corruption can be measured, or that it is a factor of no significance. The fist, … cannot be done, while to maintain that corrupt practices play no important part in social causation one must be either a hypocrite or a starry-eyed dreamer. (Andreski 1973, 124, in Social Science as Sorcery)

Even if the diagnosis offered on the foregoing pages is only partially correct, we have no grounds for expecting any great leap forward in the study of society which would replicate the rapid advances of the natural sciences. True, it is quite easy to conceive remedies against many of the ills stemming from the purely intellectual difficulties, which would work in a more perfect world. we could, for instance, insist that the economists should openly state the limitations and empirical reliability of their models, be prepared to take cultural (or, if you like, psychological and sociological [and the humanities, and literature, and religious studies, etc.]) factors into account, and desist from proffering advice on the basis of one-sided and coarsely materialistic statistics. We could demand that the psychologists should acquire some general culture, and acquaint themselves with the subtler products of the human mind before setting themselves up as experts on human nature. We could compel the sociologists to learn about history and philosophy, and the historians about the social sciences. Above all, we need a kind of intellectual puritanism which would regard money as a clear (even necessary) evil, and any manipulation of it as essentially polluting. Not that any great advantage would accrue if social scientists imitated monks and took vows of poverty; but, nonetheless, no steady advance will be possible without an ethical code which would forcefully condemn mercenary trimming as intellectual prostitution, and counter the natural human tendency not only to flatter and obey, but even to genuinely to adore those who control money or wield coercive power. The snag is that it is difficult to visualize who could enforce such requirements, and how. The difficulty here is the same as with finding the best form of government: we can readily agree with Plato that the best system would be that where the wisest and kindest rule, but nobody has so far been able to discover a practicable method for brining about such a state of affairs. (Andreski 1973, 231-232, in Social Science as Sorcery)

Some years before the First World War, a Parisian periodical asked some of the most prominent French figures in the various branches of what we would now call social sciences, and which were known at the time in France as les sciences morales, about what they regarded as the most essential method in their field. While other respondents sent back learned methodological disquisitions, Georges Sorel replied in one word: honesty. This lapidary answer has lost none of its relevance; but it is difficult to find any reasons for hoping that we shall ever have a society where absolute frankness would be the best policy for self-advancement. (Andreski 1973, 231-232, in Social Science as Sorcery)

Despite these irremovable obstacles, my own view on the prospects for the social sciences might be described as a desperate optimism. I say desperate because I do not see how our civilization could survive without important advances in our understanding of man and society. Having invented so many wonderous gadgets [e.g., nuclear weapons] which can be employed for its benefit only through the utmost use of reason, mankind has long ago passed the point of no return in this respect. No matter how valuable might be many ingredients of the old religious and moral traditions, the problem of how to reconcile human physical and spiritual needs with the environment created by technology, and how to assure mankind’s very survival, will not be solved by going back to the good old ways or dogmas. Consequently, I have no doubt that if the social sciences fall into a total and irremediable decadence, this will be a part of the general collapse of civilization, likely to be followed by an extinction of our species. No matter therefore how heavy are the odds against us, we should persist in trying to do our best, because the alternative is resignation in the face of an imminent catastrophe. (Andreski 1973, 232, in Social Science as Sorcery)

Provided some freedom of expression remains, we have reason to hope that no branch of learning will come to a complete standstill even when its main trunk succumbs to decay; because even during the ages of deepest ignorance and superstition, indomitable spirits with a natural bent for rational inquiry continued to crop up and add a brick or two to edifice of knowledge. What made their cerebrations more effective in the long run than the efforts of the vastly more numerous priests and mystagogues was the fact that the products of rational thought are cumulative, whereas mystic visions, fads, stunts and phantasmagorias not only add up to nothing, but even cancel one another out and merely sway minds to and fro, hither and thither. (Andreski 1973, 232-233, in Social Science as Sorcery)

Literature Only Economics vs. Practical Problem Solving Economics

This was a paper hard to read. It does not mean that the paper was badly written. The difficulty of the task that the author sought enforced him to write this difficult paper. After struggling a week in reading the paper, I am rather sympathetic with Delorme. In a sense, he was unfortunate, because he came to be interested in complexity problems by encountering two problems: (1) road safety problem and (2) the Regime of Interactions between the State and the Economy (RISE). I say “unfortunate,” because these are not good problems with which to start the general discussion on complexity in economics, as I will explain later. Of course, one cannot choose the first problems one encounters and we cannot blame the author on this point, but in my opinion the good starting problems are crucial to further development of the argument of complexity in economics.

Let us take the example of the beginning of modern physics. Do not think of Newton. It is a final accomplishment of the first phase of modern physics. There will be no many people who object that modern physics started by two (almost simultaneous) discoveries: (1) Kepler’s laws of orbital movements and (2) Galileo’s law of falling bodies and others. The case of Galilei can be explained by a gradual rise of the spirit of experiments. Kepler’s case is more interesting. One of crucial data for him was Tycho Brahe’s observations. He improved the accuracy of observation about 1 digit. Before Brahe for more than one thousand years, accuracy of astronomical observations was about 1 tenth of a degree (i.e. 6 minutes in angular unit system). Brahe improved this up to an accuracy of 1/2 minute to 1 minute. With this data, Kepler was confident that 8 minutes of error he detected in Copernican system was clear evidence that refutes Copernican and Ptolemaic systems. Kepler declared that these 8 minutes revolutionize whole astronomy. After many years of trials and errors, he came to discover that Mars follows an elliptic orbit. Newton’s great achievement was only possible because he knew these two results (of Galilei and Kepler). For example, Newton’s law of gravitation was not a simple result of induction or abduction. The law of square-inverse was a result of halflogical deduction from Kepler’s third law.

I cite this example, because this explains in which conditions a science can emerge. In the same vein, the economics of complexity (or more correctly economics) can be a good science when we find this good starting point. (Science should not be interpreted in a conventional meaning. I mean by science as a generic term for a good framework and system of knowledge). For example, imagine that solar system was composed of two binary stars and earth is orbiting with a substantial relative weight. It is easy to see that this system has to be solved as three-body problem and it would be very difficult for a Kepler to find any law of orbital movement. Then the history of modern physics would have been very different. This simple example shows us that any science is conditioned by complexity problems, or by tractable and intractable problem of the subject matter or objects we want to study.

The lesson we should draw form the history of modern physics is a science is most likely to start from more tractable problems and evolve to a state that can incorporate more complex and intractable phenomena. I am afraid that Delorme is forgetting this precious lesson. Isn’t he imagining that an economic science (and social science in general) can be well constructed if we gain a good philosophy and methodology of complex phenomena?

I do not object that many (or most) of economic phenomena are deeply complex ones. What I propose as a different approach is to climb the complexity hill by taking a more easy route or track than to attack directly the summit of complexity. Finding this track should be the main part of research program but I could not find any such arguments in Delorme’s paper. (Yoshinori Shiozawa, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 10/10/2017.)

1) My paper can be viewed as an exercise in problem solving in a context of empirical intractability in social science. It was triggered by the empirical discovery of complex phenomena raising questions that are not amenable to available tools of analysis, i.e., are intractable. Then the problem is to devise a model and tools of analysis enabling to cope with these questions. Then, unless someone comes with a complex system analysis or whatever tool that solves the problem at stake, a thing I would welcome, I can’t think of any other way to proceed than focusing on the very cognitive process of knowledge creation and portraying it as a reflective, open-ended, problem-first cognitive behavioral endeavour. It is an approach giving primacy both to looking and discovering rather than to assuming and deducing, and to complexity addressed in its own right rather than to complex systems in which complexity is often viewed tautologically as the behavior of complex systems. The outcome is a new tool of analysis named Deep Complexity in short. I believe that the availability of this tool provides a means to take more seriously the limitations of knowledge in a discipline like economics in which inconclusive and non demonstrative developments are not scarce when sizeable issues are involved.

2) Yoshinori Shiozawa raises the question of where to start from, from tractable problems or from the intractable? He advocates the former and suggests to “evolve to a state that can incorporate more complex and intractable phenomena”. But then, with what tools of analysis for intractable phenomena? And I would have never addressed intractability if I had not bumped into unresolved empirical obtacles. Non commutative complementarity is at work here: starting with the tractable in a discipline dominated by non conclusive and non demonstrative debates doesn’t create any incentive to explore thoroughly the intractable. It is even quite intimidating for those who engage in it. This sociology of the profession excludes de facto intractability from legitimate investigation. Then starting from the possibility of intractability incorporates establishing a dividing line and entails a procedural theorizing in which classical analysis can be developed for tractable problems when they are identified, otherwise the deep complexity tool is appropriate, before a substantive theorizing can be initiated. It is a counterintuitive process: complexification comes first, before a further necessary simplification or reduction. (Robert Delorme, (WEA Conference), 11/30/2017.)

In my first comment in this paper, I have promised to argue the track I propose. I could not satisfy my promise. Please read my second post for the general comments in discussion forum. I have given a short description on the working of an economy that can be as big as world economy. It explains how an economy works. The working of economy (not economics) is simple but general equilibrium theory disfigured it. The track I propose for economics is to start form these simple observations

As I have wrote in my first post, modern science started from Galileo Galilei’s physics and Johaness Kepler’s astronomy. We should not imagine that we can solve a really difficult problem (Delorme’s deep complexity) in a simple way. It is not a wise way to try to attack deep complexity unless we have succeeded to develop a sufficient apparatus by which to treat it. (Yoshinori Shiozawa, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 11/30/2017.)

Dear Dr Shiozawa, it seems that we are not addressing the same objects of inquiry. Yours seems to stand at an abstract level of modern science in general. Mine is much less ambitious: it is grounded in research on how to deal with particular, empirically experienced problems in real economic and social life, that appear intractable, and subject to scientific practice. Deep Complexity is the tool that is manufactured to address this particular problem. It may have wider implications in social science. but that is another story. (Robert Delorme, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 11/30/2017.)

You are attacking concrete social problems. I am rather a general theorist. That may be the reason of our differences of stance toward your problem.

Our situation reminds me the history of medicine. This is one of the oldest science and yet as the organism is highly complex system, many therapies remained symptomatic. Even though, they were to some extent useful and practical. I do not deny this fact. However, modern medicine is now changing its features, because biophysical theories and discoveries are changing medical research. Researchers are investigating the molecular level mechanism why a disease emerges. Using this knowledge, they can now design drugs at the molecular level. Without having a real science, this is not possible.

[Note Shiozawa’s implicit claim that previous medical science was not real science, but became real with the advent of molecular biology. No doubt molecular biology has opened up new domains of knowledge, but of course it is simply ludicrous to claim medicine wasn’t real science prior to molecular biology, as many perfectly valid scientific discoveries prior to and/or discovered without molecular biology are available to prove this assertion simply false. As Delorme states plainly below, this is scientism, not to mention an abysmal attempt to use revisionist history for purely rhetorical purposes. For more examples of Shiozawa’s scientism and sophistry see Semantic Negligence and for a description of literature-only economics see Payson 2017. For a good description of the kind of scientism Shiozawa is parroting see Pilkington 2016. To use one of Shiozawa’s favorite authors for go-to appeals to authority (unfortunately his memory doesn’t serve him well as Andreski contradicts his claim on RWER), see Stanislav Andreski’s Social Sciences as Sorcery (1973, 22-23).]

Economics is still in the age of pre-Copernican stage. It would be hard to find a truth mechanism why one of your examples occurs. I understand your intention, if you want say by the word of “deep complexity” a set of problems that are still beyond our ability of cognition or analysis. We may take a method very different from the regular science and probably similar to symptomatology and diagnostics. If you have argue in this way, it would have made a great contribution to our forum on complexities in economics. This is what I wanted to argue as the third aspect of complexity, i.e. complexity that conditions the development of economics as science.

To accumulate symptomatic and diagnostic knowledge in economics is quite important but most neglected part of the present day economics. (Yoshinori Shiozawa, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 12/1/2017, italics added.)

It is interesting to learn that, as an economist and social scientist, I must be in a “pre-Copernican” stage. Although what this means is not totally clear to me, I take it as revealing that our presuppositions about scientific practice differ. You claim to know what is the most appropriate way of investigating the subject I address, and that this way is the methods and tools of natural science. I claim to have devised a way which works, without knowing if it is the most appropriate, a thing whose decidability would seem to be quite problematic. And the way I have devised meets the conditions of a reflective epistemology of scientific practice, in natural science as well as in social science. Your presupposition is that the application of the methods of natural science is the yardstick for social science. This is scientism.

My presupposition is that there may be a difference between them, and that one cannot think of an appropriate method in social science without having first investigated and formulated the problem that is presented by the subject. As a “general theorist”, your position is enjoyable. May I recall what Keynes told Harrod: “Do not be reluctant to soil your hands”. I am ready to welcome any effective alternative provided it works on the object of inquiry that is at stake. It is sad that you don’t bring such an alternative. As Herb Simon wrote, ”You can’t beat something with nothing”. I borrow from your own sentence that “if you had argued this way, it would have made a great contribution to our forum…” (Robert Delorme, A Cognitive Behavioral Modelling for Coping with Intractable Complex Phenomena in Economics and Social Science. In Economic Philosophy: Complexity in Economics (WEA Conference), 12/1/2017, italics added.)

Greedy Reductionism and Statistical Shadows

Biological evolution is, as has often been noted, both fact and theory. It is a fact that all extant organisms came to exist in their current forms through a process of descent with modification from ancestral forms. The overwhelming evidence for this empirical claim was recognized relatively soon after Darwin published On the Origin of Species in 1859, and support for it has grown to the point where it is as well established as any historical claim might be. In this sense, biological evolution is no more a theory than it is a “theory” that Napoleon Bonaparte commanded the French army in the late eighteenth century. Of course, the details of how extant and extinct organisms are related to one another, and of what descended from what and when, are still being worked out, and will probably never be known in their entirety. The same is true of the details of Napoleon’s life and military campaigns. However, this lack of complete knowledge certainly does not alter the fundamental nature of the claims made, either by historians or by evolutionary biologists. (Pigliucci et al. 2006: 1)

On the other hand, evolutionary biology is also a rich patchwork of theories seeking to explain the patterns observed in the changes in populations of organisms over time. These theories range in scope form “natural selection,” which is evoked extensively at many different levels, to finer-grained explanations involving particular mechanisms (e.g., reproductive isolation induced by geographic barriers leading to speciation events). (Pigliucci et al. 2006: 1)

(….) There are a number of different ways in which these questions have been addressed, and a number of different accounts of these areas of evolutionary biology. These different accounts, we will maintain, are not always compatible, either with one another or with other accepted practices in evolutionary biology. (Pigliucci et al. 2006: 1)

(….) Because we will be making some potentially controversial claims throughout this volume, it is crucial for the reader to understand two basic ideas underlying most of what we say, as well as exactly what we think are some implications of our views for the general theory of evolutionary quantitative genetics, which we discuss repeatedly in critical fashion. (Pigliucci et al. 2006: 2)

(….) The first central idea we wish to put forth as part of the framework of this book will be readily familiar to biologists, although some of its consequences may not be. The idea can be expressed by the use of a metaphor proposed by Bill Shipley (2000) …. the shadow theater popular in Southeast Asia. In one form, the wayang golek of Bali and other parts of Indonesia, three-dimensional wooden puppets are used to project two-dimensional shadows on a screen, where the action is presented to the spectator. Shipley’s idea is that quantitative biologists find themselves very much in the position of wayang golek’s spectators: we have access to only the “statistical shadows” projected by a set of underlying causal factors. Unlike the wayang golek’s patrons, however, biologists want to peek around the screen and infer the position of the light source as well as the actual three-dimensional shapes of the puppets. This, of course, is the familiar problem of the relationship between causation and correlation, and, as any undergraduate science major soon learns, correlation is not causation (although a popular joke among scientists is that the two are nevertheless often correlated). (Pigliucci et al. 2006: 2)

The loose relationship between causation and correlation has two consequences that are crucial…. On the one hand, there is the problem that, strictly speaking, it makes no sense to attempt to infer mechanisms directly from patterns…. On the other hand, as Shipley elegantly show in his book, there is an alternative route that gets (most of) the job done, albeit in a more circuitous route and painful way. What one can do is to produce a series of alternative hypotheses about the causal pathways underlying a given set of observations; these hypotheses can then be used to “project” the expected statistical shadows, which can be compared with the observed one. If the projected and actual shadows do not match, one can discard the corresponding causal hypothesis and move on to the next one; if the two shadows do match (within statistical margins of error, of course), then one had identified at least one causal explanation compatible with the observations. As any philosopher or scientist worth her salt knows, of course, this cannot be the end of the process, for more than one causal model may be compatible with the observations, which means that one needs additional observations or refinements of the causal models to be able to discard more wrong explanations and continue to narrow the field. A crucial point here is that the causal models to be tested against the observed statistical shadow can be suggested by the observations themselves, especially if coupled with further knowledge about the system under study (such as details of the ecology, developmental biology, genetics, or past evolutionary history of the populations in question). But the statistical shadows cannot be used as direct supporting evidence for any particular causal model. (Pigliucci et al. 2006: 4)

The second central idea … has been best articulated by John Dupré (1993), and it deals with the proper way to think about reductionism. The term “reductionism” has a complex history, and it evokes strong feelings in both scientists and philosophers (often, though not always, with scientists hailing reductionism as fundamental to the success of science and some philosophers dismissing it as a hopeless epistemic dream). Dupré introduces a useful distinction that acknowledges the power of reductionism in science while at the same time sharply curtailing its scope. His idea is summarized … as two possible scenarios: In one case, reductionism allows one to explain and predict higher-level phenomena (say, development in living organisms) entirely in terms of lower-level processes (say, genetic switches throughout development). In the most extreme case, one can also infer the details of the lower-level processes from the higher-level patterns produced (something we have just seen is highly unlikely in the case of any complex biological phenomenon because of Shipley’s “statistical shadow” effect). This form of “greedy” reductionism … is bound to fail in most (though not all) cases for two reasons. The first is that the relationships between levels of manifestation of reality (e.g., genetic machinery vs. development, or population genetics vs. evolutionary pathways) are many-to-many (again, as pointed out above in our discussion of the shadow theater). The second is the genuine existence of “emergent properties” (i.e., properties of higher-level phenomena that arise from the nonadditive interaction among lower-level processes). It is, for example, currently impossible to predict the physicochemical properties of water from the simple properties of individual atoms of hydrogen and oxygen, or, for that matter, from the properties of H20 molecules and the smattering of necessary impurities. (Pigliucci et al. 2006: 4-5)

Story Telling in Economics

A Question I Once Raised During a Conference

Many years ago, when I was attending a session at an economics conference, I heard a presentation by a professor about the relationship between economic growth and technology change. In his presentation he purported to show a high correlation between the number of new patients (registered with the US Patent and Trademark Office) and economic growth. This enabled him to conclude that there was a causal relationship between technological change (as reflected by patent counts) and economic growth. This finding, by the way, is the kind that is very often hailed by organizations that offer research grants to economic professors and to other scientists. This is because findings serve as evidence for the “social benefits of R&D” which these organizations can, and often do, use to drum up political support for their organizations. It is also highly appealing to many people—admittedly, myself included—who love science and loving thinking about how beneficial scientific and technological advancement can be when it is properly and responsibly managed. So I realized that the paper being presented would be music to many people’s ears, and that it would help him receive praise, perhaps a publication, and perhaps even grant money, for his research. (Payson 2017, 3)

Given my own background on the topic … I had a question about his stated findings, which I politely asked during the question-and-answer session. In asking my question I mentioned that I was familiar with a well-known change in patent laws that occurred at the beginning of the time span that he was analyzing. As many who are familiar with patents know, the vast majority of patents that are issued have no real value and are not in fact used by the company that holds the patent. What generally occurs is that a company acquires a very valuable patent and also createes dozens of other patents that are “close” (in their subject matter) to that valuable one. The reason for their doing this is to protect their valuable patent so that no company can produce a similar patent that competes with theirs. The change in patent laws, which I just referred to, had made it easier for companies to acquire similar patents to ones that already existed, which essentially created a need for companies issuing important patents to “surround” their main patent by more of these other unused “protective patents.” (Payson 2017, 3)

So, in my question to the presenter, I asked whether it might simply be possible that the increase in registered patents that his study observed was attributable to that change in patent laws, which was apparently occurring at the same time that GDP was growing fairly well. GDP was growing at that time due to a general upturn in the economy in which employment was on the rise and inflaction had been brought under control. In other words, perhaps it was simpl a coincidental that both patent counts and real GDP were rising during the same period, but there was no causal relationship between the two. I asked him, essentially, if he thought that such a coincidence might be an alternative explanation for why patents and GDP were rising at the same time. (Payson 2017, 3-4)

The presenter’s reaction, especially in terms of his facial expression, reflected a typical response that I must have seen hundreds of times in my 35 years as an economist. Upon hearing my question he condescendingly smiled from ear-to-ear, while constraining himself from laughing, and he replied in an artificially diplomatic and sarcastic tone, “Oh I know all that [about the patent law change.] But … that’s not my story“—the story that he wanted to tell—and he was thoroughly amused that someone in the audience would be naïve enough to actually think about whether his findings were scientifically valid. Scientific validity of one’s findings is not only rarely discussed during paper presentations at economics conferences, but when it is, it is, more often than not, a source of amusement by the presenters of the papers and their audiences than an actual concern that might lead to improving people’s work. (Payson 2017, 4)

The Profession’s Genuine Arrogance toward Concerns about Scientific Integrity

(….) [M]any academic economists respond with smug, arrogant dismissial or laughter when the topic of scientific integrity or professional ethics is brought before them. It might be surprising to those who are less familiar with the profession that such arrogance and frivolity is as observable as much among some of the most prominent economics professors as among those who are not prominent. In the documentary Inside Job, one can observe this kind of arrogance directly among high-ranking professors as they were being interviewed. (Payson 2017, 4)

As another example, Deirdre McCloskey, a former member of the board of directors of the American Economic Association (AEA) (which consists only of highly ranked professors), has told of how she was there when the board broke into laughter when a letter was read aloud at one of their meetings. The letter was someone who was simply asking whether the AEA would consider adopting a code of ethics for economists. (Payson 2017, 4)

Many economics professors do not laugh or make arrogant statements, but express conceit in an entirely different way, such as feeling sorry for those who are even thinking about scientific integrity or professional ethics—thinking to themselves how pathetically stupid, naïve, or childishly innocent those people must be. There is, in fact a substantial literature on the more scholarly problem of arrogance in the academic economics profession. This literature was written entirely by “insiders”—highly prominent professors themselves, some even Nobel laureates. (Payson 2017, 4-5)

(….) In the absence of the commitment to contributing to useful knowledge, the behavior of the work of academic economists have been dominated by two other major forces: (1) the mathematical games that are played for the sake of getting published and acquiring grant money, and (2) cronyism within the profession, which, in combination with the mathematical game playing, has dominated the reward system and incentive system of the profession. (Payson 2017, 10)

[T]o examine the validity of the claim that these are highly useful branches of knowledge [e.g., economics], let us ask what their contribution to mankind’s welfare is supposed to be. To judge by the cues from training courses and textbooks, the practical usefulness … consists of helping people to find their niche in society, to adapt themselves to it painlessly, and to dwell therein contentedly and in harmony with their companions. (Andreski 1973, 26, in Social Sciences as Sorcery)

Andreski 1973, 26, in Social Sciences as Sorcery

Literature-Only Discourse and the Pretense of Scientific Merit

Regardless of all the various arguments made against most theoretical economics, “defenders of the faith” will continue to espouse the party line. That is, they will say that, regardless of the bad and unproductive habits of theoretical economics, good things—namely, genuine and extremely valuable discoveries in economic theory—do fall out of the chaos. They will continue to argue that these valuable discoveries, even though they may be rare, ultimately justify the chaos and the inefficiencies of the system. To get past this convenient, blind faith, I will argue that it is possible for us to identify what characteristics of most top-ranked, theoretical literature actually do prevent it from contributing to valuable knowledge. In this way, we may be able to filter it out from this point on, without removing any of the top-ranked literature that is truly valuable. (Payson 2017, 51)

Defining the Filter

Let us consider a subset of all published papers in economics that meet all of the following three criteria. If it meets any one of the criteria, the paper may still be considered as an acceptable contribution to useful knowledge. (Payson 2017, 51)

Criterion 1: The paper uses a model that has no “real application.” Along these lines, if the paper presents a model for the purpose of being persuasive on a particular policy position, but presents no real evidence in support of that position (and is only a model that essentially “rediscovers its assumptions”) then it would still meet this criterion of having no real application. (Payson 2017, 51)

Criterion 2: The paper relies on assumptions or data that cannot be verified, or the situation exists in which alternative assumptions or data can be reasonably found that would yield entirely different, conflicting results (as in the McCloskey’s A-Prime, C-Prime Theorem). (Payson 2017, 51-52)

Criterion 3: The methodology of the paper would only be understood, valued, and genuinely studied by a very small group of other economists with advanced expertise in that highly specific topic. (Payson 2017, 52)

Let us call a paper that meets all of these criteria a “literature-only paper”—its purpose is only for the career advancement of the author and for the production of literature to be read and actually understood by a very small audience. Similarly, let us call the work done by economists to produce literature-only papers “literature-only work” or “literature-only discourse.” To be clear, this chapter does not discuss top-ranked literature in general—only literature-only papers that meet all (every one) of the above-mentioned criteria. (Payson 2017, 52)

(….) The only thing that truly constitutes “scientific merit”—indeed, the only thing that really matters in science—is an honest and successful effort to learn how the world actually works—not an effort to create impressive systems of mathematical equations that only very smart and very educated people can proudly decipher. Many graduate students in economics, especially those with little interest or experience in natural science, are ignorant of this. They then go on to become economics professors where they remain ignorant, and pass on their ignorance to their graduate students, the cycle repeats with each generation. (Payson 2017, 52)

In response to this accusation, many theoretical economists will argue that, from looking at the work itself, we have no basis for distinguishing between valid, scientific economic theory, and invalid, unscientific economic theory. Nevertheless, I would like to propose a very simple test could enable us to make this distinction: We look at the assumptions made in the analysis, and ask, “Can an alternative set of equally defensible assumptions be made that will lead to very different conclusions?” If the answer is “Yes,” then conclusions of the research in question have no degree of certainty—implying that the research has not contributed to our understanding of how the real world works. If those conclusions are then used to provide a false understanding of how the real world works, then this is simply a deception, which may be harmful in various respects. (Payson 2017, 52-53)

Let us call economic theory that falls under this category “unscientific economic theory” to bring home the point that science plays no role in justifying the existence of such self-serving conceptual games…. So why has the problem not been solved? The answer is that this solution or anything like it, cannot be heard by unscientific theoretical economists—it falls on deaf ears. (Payson 2017, 53)

Selling New Terminology and Supposedly New Concepts

(….) In many cases new terminology is offered in literature-only discourse as the basis for a new theoretical model that appears to capture an important concept. In general, the important concept is already known and understood under different names. Nevertheless, when a prominent theoretical economist presents a new term that they promote as a “new concept,” and at the same time present a very elaborate and sophisticated model to supposedly “explain” the concept in mathematical terms, it may appear, especially to naïve observers, that their research has truly discovered something important. Many may have trouble distinguishing in their own minds the value of the new terminology from the value of the arbitrary assumptions that were used to create a sophisticated model to explain it. (Payson 2017, 60)

Prematurity in Scientific Discovery

Scientists and historians can cite many cases of scientific and technological claims, hypotheses, and proposals that, viewed in retrospect, have apparently taken an unaccountably long time to be recognized, endorsed, or integrated into accepted knowledge and practice. Indeed, some have had to await independent formulation. (Hook 2002, 3)

(….) One may classify at least five grounds on which scientific claims or hypotheses—even those later achieving widespread recognition or endorsement—may be rejected at first offering. In addition to prematurity …, investigators may reject or choose to not follow up on a scientific report or hypothesis because (1) they are unaware of it, (2) having reviewed it, they judge it to be of no immediate relevance to their current work and therefore ignore it, (3) they harbor inappropriate prejudice against some aspect of the claim or its proponent, or (4) it appears to clash directly with their observation or experience. (Hook 2002, 4)

(….) Less readily overcome obstruction may stem from strong social forces—religious, ideological, political, and economic—that lead to challenge, rejection, or suppression. In practice, the only remedy may be to seek expression and circulation of the unrecognized, inhibited, or suppression ideas, proposals, and interventions in areas and social climates where the prohibitive factors do not reign. But in principle, in an enlightened society one may suggest some goals, some general social solutions to overcome the barriers. As obvious as they may be, I believe it worthwhile to list some of them: limitation of economic suppression of new inventions or useful technology, encouragement of ideological tolerance, opposition to implacable doctrinaire social forces, and most important tactically, attempts to disconnect the apparent implications of scientific discoveries from the feared ideological consequences. (Hook 2002, 6)

Factors related to but distinct from more global social forces concern resistance at the individual level. New scientific and technical discoveries may threaten not one’s economic welfare or ideological persuasion but rather the “psychic capital” invested in current scientific views—some involving one’s own work—challenged implicitly or explicitly by a new report. Of course the longer one has held views and invested energy in them, the more reluctant one may be to alter them. This inevitably results in conceptual inertia that some have associated with aging. And ranker reasons than those produced by hardening of cerebral arteries or of scientific beliefs may arise from prejudices of culture, nation, gender, ethnicity, or race. (Hook 2002, 6-7)

All these sources of resistance to discovery originate in what some have termed the “externalist” factors influencing science.[13] And for all the above factors, one may, in principle, suggest some types of science policies to address them. For instance, the review of work by referees without knowledge of its authors, as currently practiced by some journals, clearly diminishes effects of some types of prejudices that inappropriately inhibit publication. Editors close scrutiny of reviewers’ judgements may enable them to distinguish opinions based on wounded psychic capital from legitimate methodological objections. (Hook 2002, 7)

[13] For those not familiar with the term, it refers to factors extrinsic to the putative value-free application of the scientific method. Economic and/or social factors influencing scientific inquiry are externalist. This is opposed to an “internalist approach,” which focuses on those aspects of scientific inquiry seen traditionally as free of values except for the search for truth. The image most scientists have of the ideal working of science is of course the latter. Concern with issues of acceptance of a theory based on replication, falsification, and so on may be regarded as primarily internalist, and concern with those of class and economic factors as primarily externalist. But as has been pointed out on many occasions, it is really not possible to separate those absolutely. See, for example, Nagel 1950, esp. p. 22.

A Universal Science of Man?

The medieval Roman Catholic priesthood conducted its religious preaching and other discussions in Latin, a language no more understandable to ordinary people then are than the mathematical and statistical formulations of economists today. Latin served as a universal language that had the great practical advantage of allowing easy communication within a priestly class transcending national boundaries across Europe. Yet that was not the full story. The use of Latin also separated the priesthood from the ordinary people, one of a number of devices through which the Roman Catholic Church maintained such a separation in the medieval era. It all served to convey an aura of majesty and religious authority—as does the Supreme Court in the United States, still sitting in priestly robes. In employing an arcane language of mathematics and statistics, Samuelson and fellow economists today seek a similar authority in society.

Economics as Religion: From Samuelson to Chicago and Beyond by Robert H. Nelson

This is a book about economics. But it is also a book about human limitations and the difficulty of gaining true insight into the world around us. There is, in truth, no way of separating these two things from one other. To try to discuss economics without understanding the difficulty of applying it to the real world is to consign oneself to dealing with pure makings of our own imaginations. Much of economics at the time of writing is of this sort, although it is unclear such modes of thought should be called ‘economics’ and whether future generations will see them as such. There is every chance that the backward-looking eye of posterity will see much of what today’s economic departments produce in the same way as we now see phrenology: a highly technical, but ultimately ridiculous pseudoscience constructed rather unconsciously to serve the political needs of the era. In the era when men claiming to be scientists felt the skull for bumps and used this to determine a man’s character and his disposition, the political discourse of the day needed a justification for the racial superiority of the white man; today our present political discourse needs a Panglossian doctrine that promotes general ignorance, a technocratic language that can be deployed to cover up certain political aspects of govenmance and tells us that so long as we trust in those in charge everything will work itself out in the long-run. (Pilkington 2016, 1-2)

But the personal motivations of the individual economist today is not primarily political—although it may well be secondarily political, whether that politics turns right or left—the primary motivation of the individual economist today is in search to answers to questions that they can barely forumulate. These men and women, perhaps more than any other, are chasing a shadow that has been taunting mankind since the early days of the Enlightenment. This is the shadow of the mathesis universalis, the Universal Science expressed in the abstract language of mathematics. They want to capture Man’s essence and understand what he will do today, tomorrow and the day after that. To some of us more humble human beings that fell once upon a time onto this strange path, this may seem altogether too much to ask of our capacities for knowledge…. Is it a nobel cause, this Universal Science of Man? Some might say that if it were not so fanciful, it might be. Others might say that it has roots in extreme totalitarian thinking and were it ever taken truly seriously, it would lead to a tyranny with those who espouse it conveniently at the helm. These are moral and political questions that will not be explored in too much detail in the present book. (Pilkington 2016, 2)

What we seek to do here is more humble again. There is a sense today, nearly six years after an economic catastrophe that few still understand and only a few saw coming, that there is something rotten in economics. Something stinks and people are less inclined than ever to trust the funny little man standing next to the blackboard with his equations and his seemingly otherworldly answers to every social and economic problem that one can imagine. This is a healthy feeling and we as a society should promote and embrace it. A similar movement began over half a millennia ago questioning the men of mystery who dictated how people should live their lives from ivory towers; it was called the Reformation and it changed the world…. We are not so much interested in the practices of the economists themselves, as to whether they engage in simony, in nepotism and—could it ever be thought?—the sale of indulgences to those countries that had or were in the process of committing grave sins. Rather we are interested in how we gotten to where we are and how we can fix it. (Pilkington 2016, 2-3)

The roots of the problems with contemporary economics run very deep indeed. In order to comprehend them, we must run the gamut from political motivation to questions of philosophy and methodology to the foundations of the underlying structure itself. When these roots have been exposed, we can then begin the process of digging them up so we can plant a new tree. In doing this, we do not hope to provide all the answers but merely a firm grounding, a shrub that can, given time, grow into something far more robust. (Pilkington 2016, 3)

Down with Mathematics?

(….) Economics needs more people who distrust mathematics when applying thought to the social and economic world, not less. Indeed, … the major problems with economics today arose out of the mathematization of the discipline, especially as it proceeded after the Second World War. Mathematics become to economics what Latin was to the stagnant priest-caste that Luther and other reformers attacked during the Reformation: a means not to clarify, but to obscure through intellectual intimidation. It ensured that the common man could not read the Bible and had to consult the priest and, perhaps, pay him alms. (Pilkington 2016, 3)

(….) [M]athematics can, in certain very limited circumstances, be an opportune way of focusing the debate. It can give us a rather clear and precise conception of what we are talking about. Some aspects—by no means all aspects—of macroeconomics are quantifiable. Investments, profits, the interest rate—we can look the statistics for these things up and use this information to promote economic understanding. That these are quantifiable also means that, to a limited extent, we can conceive of them in mathematical form. It cannot be stressed enough, however, the limited extent to which this is the case. There are always … non-quantifiable elements that play absolutely key roles in how the economy works. (Pilkington 2016, 3-4)

(….) The mathematisation of the discipline was perhaps the crucial turning point when economics began to become something entirely other to the study of the actual economy. It started in the late nineteenth century, but at the time many of those who pioneered the approach became ever more distrustful of doing so. They began to think that it would only lead to obscurity of argument and an inability to communicate properly either with other people or with the real world. Formulae would become synonymous with truth and the interrelation between ideas would become foggy and unclear. A false sense of clarity in the form of pristine equations would be substituted for clarity of thought. Alfred Marshall, a pioneer of mathematics in economics who nevertheless always hid it in footnotes, wrote of his distress in his later years in a letter to his friend. (Pilkington 2016, 4)

[I had] a growing feeling in the later years of my work at the subject that a good mathematical theorem dealing with economic hypotheses was very unlikely to be good economics: and I went more and more on the rules—(1) Use mathematics as a shorthand language, rather than an engine of inquiry. (2) Keep to them till you have done. (3) Translate into English. (4) Then illustrate by examples that are important in real life. (5) Burn the mathematics. (6) If you can’t succeed in (4), burn (3). This last I did often. (Pigou ed. 1966 [1906], pp. 427-428)

The controversy around mathematics appears to have broken out in full force surrounding the issue of econometric estimation in the late 1930s and early 1940s. Econometric estimation … is the practice of putting economic theories into mathematical form and then using them to make predictions based on available statistics…. [I]t is a desperately silly practice. Those who championed the econometric and mathematical approach were men whose names are not known today by anyone who is not deeply interested in the field. The were men like Jan Tinbergen, Oskar Lange, Jacob Marschak and Ragnar Frisch (Louçā 2007). Most of these men were social engineers of one form or another; all of them left-wing and some of them communist. The mood of the time, one reflected in the tendency to try to model the economy itself, was that society and the economy should be planned by men in lab coats. By this they often meant not simply broad government intervention but something more like micro-management of the institutions that people inhabit day-to-day from the top down. Despite the fact that many mathematical economic models today seem outwardly to be concerned with ‘free markets’, they all share this streak, especially in how they conceive that people (should?) act. (Pilkington 2016, 4-5)

Most of the economists at the time were vehemently opposed to this. This was not a particularly left-wing or right-wing issue. On the left, John Maynard Keynes was horrified by what he was seeing develop, while, on the right, Friedrich von Hayek was warning that this was not the way forward. But it was probably Keynes who was the most coherent belligerent of the new approach. This is because before he began to write books on economics, Keynes had worked on the philosophy of probability theory, and probability theory was becoming a key component of the mathematical approach (Keynes 1921). Keynes’ extensive investigations into probability theory allowed him to perceive to what extent mathematical formalism could be applied for understanding society and the economy. He found that it was extremely limited in its ability to illuminate social problems. Keynes was not against statistics or anything like that—he was an early champion and expert—but he was very, very cautious about people who claimed that just because economics produces statistics these can be used in the same as numerical observations form experiments were used in the hard sciences. He was also keenly aware that cetain tendencies towards mathematisation lead to a fogging of the mind. In a more diplomatic letter to one of the new mathematical economists (Keynes, as shall see … could be scathing about these new approaches), he wrote: (Pilkington 2016, 5-6)

Mathematical economics is such risky stuff as compared with nonmathematical economics, because one is deprived of one’s intuition on the one hand, yet there are all kinds of unexpressed unavowed assumptions on the other. Thus I never put much trust in it unless it falls in with my own intuitions; and I am therefore grateful for an author who makes it easier for me to apply this check without too much hard work. (Keynes cited in Louçā 2007, p. 186)

(….) Mathematics, like the high Latin of Luther’s time, is a language. It is a language that facilitates greater precision in some instances and greater obscurity in others. For most issues economic, it promotes obscurity. When a language is used to obscure, it is used as a weapon by those who speak it to repress the voices of those who do not. A good deal of the history of the relationship between mathematics and the other social sciences in the latter half of the twentieth century can be read under this light. If there is anything that this book seeks to do, it is to help people realise that this is not what economics need be or should be. Frankly, we need more of those who speak the languages of the humanities—of philosophy, sociology and psychology—than we do people who speak the language of the engineers but lack the pragmatic spirit of the engineer who can see clearly that his method cannot be deployed to understand those around him. (Pilkington 2016, 6)