HEURISTIC ECONOMIC MANAGEMENT & NEW INTUITIVE ECONOMICS
The Heuristic and Intuitive Management of Economic Complexity:
Researching into the scientific study of problem-solving programs that we don’t yet know how to write can be perceived as a vital and decisive challenge in human intellectual history. Our subject of heuristic economics is practically oriented, but we will not succeed without advancing the methodical thought of the economics discipline and management profession. Human intelligence implies the conspicuous character of the intellectual ability to reason logically, but social practice is a witness that the majority of human agents performs so poor at it. The social science of economics is a progressing body of knowledge and learning, but the sole application of pure logic seems not to be an intelligent tool to mimic economic action. The most advanced automatic theorem provers are interesting because of the methodical ways they discover theorems and proofs, not for the logic they do contain; logic is used to confirm results, but the process of discovery is intuitive; even in mathematics, progress is not made by logic. Human brains are built of neurons, i.e. living cells which do not approximate the determinism of, for example, electronics; the hippocampus is built of layers of neurons, and its function and structure is much more like that of a connection machine than a von Neumann one. Simply and empirically speaking, on the large scale, people basically do not behave logical.
A.Ghosal, ( 2001), Heuristic economics-its cybernetic undertone, Kybernetes, Vol.30Iss.9/10, pp.1118-1125 ( search at: www.emeraldinsight.com ) prepared the cybernetic argument for the scope of economic heuristics ; the systemic intuitionism of economic action is subject to heuristic search strategies (visit: intelligence.worldofcomputing.net/aisearch/heuristic-search.html ); in addition, it is decisive to understand an algorithm as a standard heuristic procedure to re-search via the sequence of formula, equation or calculation. Recently (2008), a paper on - Using Heuristics in Economic Decision Making –documents irrational decisions regarding money, violating the very axioms of the rational decision making model (zsem.academia.edu/AndrijanaMusura ) . As of July 2011, we can observe the battle between complexity (www.ted.com/talks/kevin_slavin_how_algorithms_shape_our_world.html ) and regulation ( www.iosco.org/library/pubdocs/pdf/IOSCOPD354.pdf ). In any case, what we can primarily perceive are the real economic results of a mathematized ideology of economism. At: star.tau.ac.il/~eshel/, it is possible to learn more about the econophysics of the behavior of –Stock Market and Epilepsy; the project under the supervision of Prof. Eshel Ben-Jacob clearly documents the pathological patterns of the economic monetary system. Empirically, economic theory and data do not fit together; the artificial exactness of the experimental laboratory or hermeneutic sophistication do not matter; we discover and detect an eminent bias in the empirical sequence of perception, observation and measurement of economic data ( www.math.mcgill.ca/vetta/CS764.dir/judgement.pdf ) ,in the tradition of D. Kahneman & A. Tversky ( Judgement under Uncertainty: Heuristics and Biases ). The scientific research process of economic theory and data and the heuristic interplay of theoretical induction and empirical deduction must be revisited; in the Popperian sense, the abstract reduction does not work or from the Polyanite view, the
concrete strategy of-how to solve it- is unknown. However, all human problem-solving occurs under the economic conditions of limited knowledge and time; economic learning processes were always required to generate new knowledge and to cognitively adapt our human behavior to changing conditions.
The Simonian heuristics for scientific discovery ( www.isle.org/~papers/has.essay.pdf ) is deeply connected to the Arrowian economic implications of learning by doing ( home.cc.manitoba.ca/~jiang2/arrow%201962%20res.pdf ) ; in addition, it is vital to keep in mind the Hayekian role of competition as a discovery procedure( visit:mises.org/journals/qjae/pdf/qjae5_3_3.pdf ). Nonetheless, Israel Kirzner is not getting tired to clarify the economic value of the alert and creative entrepreneur for societal progress (www.ifn.se/Wfiles/wp/wp760.pdf). Furthermore, eminent psychologist G. Gigerenzer and economics Nobel laureate R. Selten are presenting us an adaptive toolbox of bounded rationality (visit: dieoff.org/_Biology/Bounded Rationalty_TheAdaptiveToolbox.pdf). It is the cognitive challenge of our time to study these many puzzling isolated results and to put them into a practical and holistic framework of appropriate economic action, i.e. to reorganize the body of economic knowledge accordingly – the economic parameters of productivity, investment, money and innovation are rapidly changing and our mental response is insufficient as the chain of value creation in our technological information age transforms in Polanyian manner ( visit: en.wikipedia.org/wiki/The_Great_Transformation_(book)
The insightful understanding has to be gained that economics is not a branch of applied mathematics or physics; mathematics is initially non-linguistic and a creation of the human mind. The perception, observation and measurement of a move of time is the origin and nature of mathematical reality and activity, with time being the only a priori condition, i.e. the existence of infinite sequences is not fixed in advance, but generated by free choice and chance on a time continuum. Human language is then used to exchange the mathematical ideas of methodical measurement; truth and falsity are temporal, the truth-value of discovered facts is governed by temporality. The mental constructions of the mathematical method are not timeless, infinite and independent abstractions of finite human beings who communicate eternal truth. All logical axioms do rest on prior human intuitions, concerning time, negation and provability; only what can be methodically shown to be provable can be justifiably asserted; there are certain limits to test the properties of infinite sets. The further advancement of economics is therefore bound to catching cognitively up with the research facts of what we would call methodical mathematics or mathematical methodology, i.e. constructive mathematics should be studied and applied in economic decision making ( visit: en.wikipedia.org/wiki/Mathematical_constructionism /and/ Measure_theory ). This is the only way to ending the mathematical and methodical mischief in economic science and to profiting really from the research & development in computation techniques; a progressive integration of economics, heuristics and artificial intelligence is at the core of futuristic economic thought. The Druckerian paradigm to communicate economic and
management data from the arena of social complexity into the organization of the market society is the key for successful coping with the transformation of the value creation chain in knowledge societies. The real life risk emerges from the inertia of mental routines that do not perceive the movement and development of new productive means in human economic activity. One example is the exponential commercialization of machine learning for speech recognition, computer vision, bio-monitoring, robotic control, intelligent automation and research data processing ( since 1985 ); however, this is only the tip of an iceberg, without intending to create a Titanic vision: we are daily experiencing a lasting economic and monetary illusion that can easily result in a total social-economic collapse. The tools of our knowledge management do not hold pace with the velocity of temporal acceleration, i.e. we are facing a truly historical period of socio-economic problemsolving, calling for heuristic management and intuitive economics. Methodically, we should follow the open, networked and reinvented science approach of Prof. M. Nielsen ( www.ustream.tv/recorded/2685625), with its emphasis on self-emerging and heuristic discovery ; this creative species of new scientific research is definitely more able to cope evolutionary with the rapid socio-tech-know-logical transformation of the advanced and advancing market societies.
Conclusio:
1: The applied scope of heuristic economics is intuitive management via methodical mathematics; during the 20th century, management evolved as the most important social function for economic value creation in closed industrial factory systems;
2: Human economic behavior/activity operates like a connectionist machine and pure logic accounts for about 20 per cent of economic decision making; today, socio-economic complexity is caused by open information production systems;
3: All human economic action happens under subjective finite temporality and is thus object to counting and measuring, reflecting a certain technical and ethical level;
4: A creative integration of artificial intelligence, heuristics and economics will lead to the reinvention of the management discipline, i.e. facilitating the communication with complexity which cannot be controlled but only understood; a very important tool is the constructive mathematical method;
5: The decisive economic parameters of productivity, investment, money and innovation are calling for a progressive and insightful understanding from the viewpoint of techknow-logy;
6: The methodical mischief in economic science and monetary policy is caused by a false application of the mathematical method in treating economics as a branch of applied physics, leading to a disconnection of economic reality and accounting;
7: The new economic science will make use of the heuristic and intuitive method, in the computational and mathematical sense, thus reinventing economic discovery via human ingenuity.
Keywords: new economics, meta-heuristics, methodical intuition, monetary investment, innovative production, reinventing discovery, connectionism, complexity.
Abstract: In this decade, we will witness the rise of heuristic economics and intuitive management via methodical mathematics. The current economic and monetary mischief is rooted in a false understanding of the economic discipline and management profession that derives from the wrong application of the mathematical method in decision making. New economics will be a meta-heuristic discipline in which all past knowledge algorithms will be professionally reinvented via creative discovery.
Stephen I. Ternyik, economist/educator, Techno-Logos, Inc. StephenJehucal@web.de www.jesherjehucal.beepworld.de
Literature:
S.Ternyik, Economics as Heuristics & New Economics, e.book, 2011, amazon, itunes.apple S.Ternyik, Socio-eco-nomics of Innovation, www.issuu.com/jehucal/docs/socio
Links:
www.worldeconomicsassociation.org
okfn.org
webhost.ua.ac.be/eume