This blog page follows https://journeau.net/2017/01/28/socialize-innovation-and-knowledge/ and Innovation, Welfare and Democracy, Part I, where we observe and discuss the societal conditions of emergence of disruptive, new knowledge, production and dissemination processes, able to overcome the natural inertia of established structures and streams.
The growth of welfare imply conditions, for which we seek a quite physical equivalent and mathematical model, enabling enduring derivations from the “circular flow”, as expressed by Schumpeter, which may not only erase profits but even shrink the related (such as autarkic) economic welfare.
In this approach the subsequent question of ‘sharing’ the cake is not considered as a preamble or even an axiom but as a variable, if not even a subordinate aspect since sharing a not growing, or relatively or even absolutely shrinking ‘cake’, may be seen as of little interest after the premises above. Let’s emphasize that in a global economy a local one may apparently grow although it shrinks relatively to others or possibly preserves its share of the general welfare by eating some of its reserves or potential.
In previous blog page we discussed Kurz [1] focus, in its 4th section, on “The ‘natural course of things’ vs. the ‘circular flow‘”, presented as Schumpeter’s “counterfactual reasoning, because it contemplates an economic system in which there is no change whatsoever” while “…’new combinations’, innovations, continually invade the actual economy and make the system grow and undergo structural transformations.”
And yet the “natural course” appears not so natural, not so easy, because societies tend, in a more natural quest for optimal complexity, toward power and welfare, to get unnecessary structure, which then ‘naturally’ resists change so that innovations only effectively grow and disseminate in rare, if any, most agile societies, only from where they acquire the power to disturb less adaptive and undergo their “structural transformations” the value generated, which may be low since Kurz adds that “in the circular flow, Schumpeter contended, there will be neither profits nor interest“.
Profits and interests as traces of the disruption in the flow may then imply what Kurz concludes about “Schumpeter between Walras and Marx“, after Mas-Colell, i.e. that “the relationship between the two ratios [wage to rate-of-profits versus labor/capital] can have any shape whatsoever“.
The second article on which we here focus, by Egidi [2], leaps with Schumpeter and through Langlois from the need of an economy to innovate, cf. above, to the role of the entrepreneur, and from there to the characterization of the knowledge, or even cognition, and other conditions and factors enabling enough entrepreneurial innovation process.
Egidi scrutinizes the implications drawn by Schumpeter and other authors about the individual role of the entrepreneur and cognitive process, which are then considered in the perspective of the generalization – otherwise called socialization – of cognition, with the limits of ‘conscious rationality’ versus advertising and persuasion, in or onto Society.
The scheme discussed here seeks one step further, i.e. from Egidi’s analysis into a more structured and potentially predictive hence refutable model of such cognitive behavior.
It will go through three parts: a summary about the need for better models of cognition from its “components”, with a more precise model of this ‘conscious rationality’, a presentation of the model and a general conclusion about next steps and about consequences for democracy.
Our model, in progress, shows and quantifies the gap between the “slow growth’ law” about which [3] cites Bennett [4] to claim that “an evolutionary system T(t) cannot have its logical depth LD(T(t)) that grows suddenly“. Our model of fast growth depicts the entrepreneur’s impact while slow growth applies to societies, although obviously with a rate that accelerates in this early 21st century as compared to previous decades.
This model about the extent of the complexity [5] leap here involved, as compared to other definitions of complexity, allows a comprehensive complexity ladder, in which the relative complexity depths of individuals versus the societies might be compared.
We will as an example quantify the relative complexities of Simon’s chess and other game players, involved by Egidi, as compared to Deacon’s “teleodynamic systems” – whom emphasizes the “higher order intrinsic constraint (that) prevents the disruption of the synergy between the component morphodynamic processes that determines its unity” [6] – and to diverse attempts at formalizing intuition, from its role at the roots of some constructivism in mathematics to Goldwasser’s et al. [7] observation that “each formalization (..) cannot entirely capture our original and intuitive notions, exactly because they are intuitive” when introducing the model of Interactive Proof-Systems in more than one way seminal to ours.
Egidi’s analysis of “the Cognitive roots of Schumpeter’s picture of democracy”
Egidi starts with recalling some comments of Langlois’ comment of Schumpeter’s about the condition of the entrepreneurial leap out of the “circular flow” where “there is nothing fundamentally new” but with “the impossibility of surveying exhaustively all the effects and counter-effects of the projected enterprise”. This importance of this last remark will be emphasized below as it means that, therefore, neither competitors – that may want to kill it in the bud – nor even provisional supporters ranging from shareholders and the public environment, will have this capacity as opposed to the Entrepreneur, however single he or she may be, to an extent that remains to be proven and/or better, quantified.
We will have to conclude that in effect the both of them are not only unable to “survey” but also that, as a result, they will reveal to be the main threat to the survival and to the success of innovative ventures, an observation that has led some Societies to allow protections as opposed to some others.
His best extract of Langlois on Schumpeter follows with the observation that the “success… depends upon intuition, the capacity of seeing things in a way which afterwards proves to be true, even though it cannot be established at the moment, and grasping the essential fact, discarding the unessential, even though one can give not account of the principles by which this is done” (Schumpeter (1934) 85)[2].
Let’s observe that this is very close to some kinds of scientific process, although this one aims at delivering a predictive model then scientifically valid, à la Popper, inasmuch as refutable.
We follow Egidi in his next paragraphs, dedicated to scrutinizing further, after Schumpeter, this capacity and process so important as to enable the Entrepreneur to make right decisions that much more powerful groups, such as established firms, may not.
Because of the apparently, ex-post rational entrepreneurial decisions, Schumpeter seems to widen the concept of rationality although Egidi points to the concepts of “creative response” and “discovery” where, to account for “no longer a process of optimization” – since disruptive – he introduces Herbert Simons and the analogy to the “chess playing activity” where “the winning strategy, which already exists, is not practically computable.”
Our provisional conclusion is that this computability issue indeed characterizes and underlies the ladder between the entrepreneurial “teleodynamic” quest versus a societal ‘slower growth’, and yet that the chess playing intractability is still nothing as compared to the quantity here at staked and to be scrutinized in next blog pages on this question.
[1] H. D. Kurz, Is there a “Ricardian Vice”? And what is its relationship with economic policy ad“vice”?, J Evol Econ. 2017; 27(1): 91–114. Published online 2016 Jul 9. doi: 10.1007/s00191-016-0468-2, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5253719/
[2] M. Egidi, Schumpeter’s picture of economic and political institutions in the light of a cognitive approach to human behavior, J Evol Econ. 2017; 27(1): 139–159, Published online 2015 Sep 4. doi: 10.1007/s00191-015-0421-9, www.ncbi.nlm.nih.gov/pmc/articles/PMC5253716
[3] J-P Delahaye & C. Vidal, Organized Complexity: is Big History a Big Computation, https://arxiv.org/abs/1609.07111
[4] Bennett, C.H. 1988. Logical Depth and Physical Complexity. In The Universal Turing Machine: A Half-Century Survey, edited by R. Herken, 227–57. Oxford University Press.
http://www.research.ibm.com/people/b/bennetc/UTMX.pdf
[5] P. Journeau, Comprehensive Complex Universe
[6] T. Deacon & S. Koutroufinis, Complexity and Dynamical Depth, www.mdpi.com/2078-2489/5/3/404/pdf
[7] S. Goldwasser, S. Micali & C. Rackoff, The knowledge Complexity of Interactive Proof-Systems, ACM, 1985, https://groups.csail.mit.edu/cis/pubs/shafi/1985-stoc.pdf
Comprehensive Universe 