Tom

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Tomáš Sabol Ekonómia pohlady z
interdisciplinárnych brehov

• Tomas.Sabol_at_tuke.sk

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Obsah

• Non traditional economics
• Specifics of information knowledge
• Complexity and Complex adaptive systems
• Intelligence, Reflexivity, Bounded rationality
• Everything 2.0
• Inspiration coming from biology evolution
• Related concepts (chaos, graphs, Gödel, ...)
• Najlahšie je rozprávat o tom, o com vieme málo,
  resp. skoro nic.
• Pocul som to od pár múdrych ludí

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Naozaj?

• Bertrand Russell dropped his interest in
  economics after half a year's study because he
  thought it was too simple. Max Planck dropped his
  involvement with economics because he thought it
  was too difficult.
• In 1990 Colander and Klamer asked students how
  important having a "thorough knowledge of the
  economy" was to succeeding as a economist. 3
  percent thought it very important, and 68
  thought it unimportant. Important was "Being
  smart in the sense of being good at problem
  solving" and "excellence in mathematics."
• W. Brian Arthur Cognition The Black Box of
  Economics

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• I have always believed that the complexity of the
  problems facing mankind is growing faster than
  our ability to solve them.
• Doug Engelbart

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Ako sa stat inovatívnym?

• What is it that enables Google to be so
  innovative?
• We tell our engineering population, which is
  roughly 50 of all Googlers, to work 70 of their
  time on their core job, 20 of their time on
  projects that are loosely connected with their
  core job (so if they work on search, then maybe
  20 of their time looking at the fringes of
  search), and 10 of their time thinking about
  whatever they want to think about. No meetings.
  No emails. Nothing. You spend a day a fortnight
  thinking big thoughts.
• Vice-president of Google .

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Behavioral economic behavioral finance

• A separate branch of economic and financial
  analysis, which applies scientific research on
  human and social, cognitive and emotional factors
  to better understand economic decisions by
  consumers, borrowers, investors, and how they
  affect market prices, returns and the allocation
  of resources
• Theoretical basis for technical analysis
• Concerned with the bounds of rationality

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Information Economics (or Economics of
Information)

• Studies how information affects an economy and
  economic decisions
• Information (cf. knowledge) has special
  characteristics
• Easy to create, but hard to trust
• Easy to spread, but hard to control
• Influences many decisions
• Non-exclusion - consuming information does not
  exclude someone else from also consuming it (but
  artificial exclusion constructs)
• Almost zero marginal cost - once the first copy
  exists, it costs (almost) nothing to make a
  second copy

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Information Economics (or Economics of
Information)

• Information market does not exhibit high degrees
  of transparency. That is, to evaluate the
  information the information must be known, so you
  have to invest in learning it to evaluate it
• Information asymmetry - study of decisions in
  transactions where one party has more or better
  information than the other, creates an imbalance
  in power in transactions
• The value of knowledge by its use (and
  enhancement by the users feedback) increases
  (the value of traditional assets by their use
  decreases)
• This (compared with other types of goods)
  complicate bying/selling models many standard
  economic theories, new valuation techniques
  needed etc.

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Knowledge Economy vs Traditional economy

• The economics are not of scarcity, but rather of
  abundance. Unlike most resources that become
  depleted when used, information and knowledge can
  be shared, and actually grow through application.
• The effect of location is either
• Diminished in some economic activities using
  appropriate technology methods, virtual
  marketplaces virtual organizations offer
  benefits of speed, agility, 24/7, global reach
• or, on the contrary, reinforced in some other
  economic fields, by the creation of business
  clusters around centres of knowledge
  universities, research centres.
• Laws, barriers, taxes etc are difficult to apply
  solely on a national basis. Knowledge
  information "leak" to where demand is highest and
  the barriers lowest.
• Knowledge enhanced products or services can
  command price premiums over comparable products
  with low embedded knowledge or knowledge
  intensity.

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Knowledge Economy vs Traditional economy

• Pricing and value depends heavily on context. The
  same information or knowledge can have vastly
  different value to different people, or even to
  the same person at different times.
• Knowledge when locked into systems or processes
  has higher inherent value than when it can "walk
  out of the door" in people's heads.
• See Tacit versus Codified knowledge
• Human capital (competencies) - a key component of
  value, yet few companies report competency levels
  in annual reports ( cf. company valuation)
• Communication - fundamental to knowledge flows.
  Social structures, cultural context and other
  factors influencing social relations are of
  fundamental importance

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Economy of Knowledge

• Growth of knowledge - complex evolutionary
  process
• Adam Smith, Austrian school of economists
• Production and management of knowledge in the
  frame of economic constraints
• Knowledge-based economy the use of knowledge
  technologies (knowledge engineering, knowledge
  management) to produce economic benefits
• Rules practices that determined success in
  industrial economy need rewriting in an
  interconnected, globalized economy where
  knowledge resources (know-how, expertise) are as
  critical as other economic resources
• at the level of firms industries in terms of
  knowledge management
• at the level of public policy as knowledge policy
• Knowledge the most important asset

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Network Economy

• Products and services are created and value is
  added through social networks operating on large
  or global scales
• New bussines models needed
• Economies of scale stem from the size of the
  network - not the enterprise
• open system is preferable to a closed system
• see also Systems theory

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Econophysics

• Interdisciplinary research field, applying
  theories and methods originally developed by
  physicists in order to solve problems in
  economics - including uncertainty, stochastic
  processes, nonlinear dynamics
• statistical finance - application to the
  financial markets
• Many of the more interesting phenomena in
  financial markets fundamentally depend on
  heterogeneous agents and far-from-equilibrium
  situations (cf. Ilya Prigogine)
• Physics models applied in economics percolation
  models, chaotic models (developed to study
  cardiac arrest), models with self-organizing
  criticality, models developed for earthquake
  prediction, mathematical theory of complexity and
  information theory (Claude Shannon, Murray
  Gell-Mann, )

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Econophysics

• Quantum economy - a quantum economic model of a
  finite economic system that consists of an
  economic subsystem with a certain number of
  buyers and sellers (economy agents) and its
  external environment (institutions) with certain
  interactions between economy agents, and between
  the economy agents and institutions
• Analogies between finance theory diffusion
  theory (the Black-Scholes equation for option
  pricing is a diffusion-advection equation)

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Complexity

• Something with many parts in intricate
  arrangement
• Often tied to the concept of a system a set
  of parts or elements, which have relationships
  among them differentiated from relationships
  with other elements outside the relational regime
• Many definitions tend to assume that complexity
  expresses a condition of numerous elements in a
  system and numerous forms of relationships among
  the elements
• Intricate inter-relationships that arise from the
  interaction of agents, which are able to adapt in
  and evolve with a changing environment
• Complexity of a particular system is the degree
  of difficulty in predicting the properties of the
  system if the properties of the systems parts
  are given

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Complexity
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Complexity

• Complexity includes ideas such as complex
  adaptive systems, self-organisation,
  co-evolution, agent based computer models, chaos,
  bifurcations, networks, emergence, fractals
• Complex systems constructed so that they are on
  the boundary between order and chaos are those
  best able to adapt by mutation and selection.
  Chaos is a subset of complexity an example so
  called butterfly effect the idea is that a
  butterfly in Rio can change the weather in
  Chicago. An infinitesimal change in initial
  conditions leads to divergent pathways in the
  evolution of the system. Complex systems have
  evolved which may have learned to balance
  divergence and convergence, so that they're
  poised between chaos and order

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Complex Systems

• A scientific field which studies the common
  properties of systems that are considered
  fundamentally complex
• A new approach to science that studies how
  relationships between parts give rise to the
  collective behaviors of a system and how the
  system interacts and forms relationships with its
  environment
• A broad term encompassing a research approach to
  problems in economics, anthropology, artificial
  life, chemistry, computer science, evolutionary
  computation, earthquake prediction, meteorology,
  molecular biology, neuroscience, physics,
  psychology, sociology

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Complex systems

• One of Hayek's main contributions to early
  complexity theory is his distinction between the
  human capacity to predict the behaviour of simple
  systems and its capacity to predict the behaviour
  of complex systems through modeling. He believed
  that economics and the sciences of complex
  phenomena in general, which in his view included
  biology, psychology, and so on, could not be
  modeled after the sciences that deal with
  essentially simple phenomena like physics.

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Complexity in pictures
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Complexity in pictures
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Complex Adaptive Systems (CAS)

• A CAS is a complex, self-similar collection of
  interacting adaptive agents. The study of CAS
  focuses on complex, emergent and macroscopic
  properties of the system
• Examples of complex adaptive systems include the
  stock market, social insect and ant colonies, the
  biosphere and the ecosystem, the brain and the
  immune system, the cell and the developing
  embryo, manufacturing businesses and any human
  social group-based endeavour in a cultural and
  social system such as political parties or
  communities. There are close relationships
  between the field of CAS and artificial life. In
  both areas the principles emergence and
  self-organization are very important.

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Complex Adaptive Systems

• A Complex Adaptive System (CAS) is a dynamic
  network of many agents (which may represent
  cells, species, individuals, firms, nations)
  acting in parallel, constantly acting and
  reacting to what the other agents are doing. The
  control of a CAS tends to be highly dispersed and
  decentralized. If there is to be any coherent
  behavior in the system, it has to arise from
  competition and cooperation among the agents
  themselves. The overall behavior of the system is
  the result of a huge number of decisions made
  every moment by many individual agents.

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Complexity in Economics

• Economic system is dynamically complex if its
  deterministic endogenous processes do not lead it
  asymptotically to a fixed point, a limit cycle,
  or an explosion
• Some might argue that endogenous limit cycles
  also constitute complexity, but we shall view
  them as merely nearly complex
• All systems that fit this definition have some
  degree of nonlinearity within them, however
  limited or arbitrary
• Note There are nonlinear systems that are not
  complex, such as a standard exponential growth
  model

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Limit Cycle
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Complexity Economics

• Application of complexity science to the problems
  of economics
• One of the four C's of a new paradigm surfacing
  in the field of economics Cybernetics,
  Catastrophe, Chaos, Complexity
• Rejects traditional assumptions that imply that
  the economy is a closed system that eventually
  reaches an equilibrium.
• Views economies as open complex adaptive systems
  with endogenous evolution
• Complexity economics rejects many aspects of
  traditional economic theory (mathematical models
  formulated in an analogy with early models of
  thermodynamics - based on the first law of
  thermodynamics, equilibrium)

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Complexity Economics

• Claims that traditional economic models never
  adapted to the latter discovery, remain
  incomplete models of reality, and that mainstream
  economists are yet to introduce information
  entropy to their models
• Information entropy ("information uncertainty) -
  important concepts of organization and disorder,
  viewed as basic state parameters, in
  describing/simulating the evolution of complex
  (including economic) systems
• Economic systems - no more considered as
  "naturally" inclined to achieve equilibrium
  states. On the contrary, economic systems - like
  most complex and self-organized systems - are
  intrinsically evolutionary systems, which tend to
  develop, prevailingly toward levels of higher
  internal organization though the possibility of
  involution processes - or even of catastrophic
  events - remains immanent

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Complexity Economics (1/2)

• No Global Controller no global entity controls
  interactions. Controls are provided by mechanisms
  of competition coordination between agents.
  Economic actions are mediated by legal
  institutions, assigned roles, shifting
  associations. No universal competitor a single
  agent that can exploit all opportunities in the
  economy
• Continual Adaptation Behaviors, actions,
  strategies, and products are revised continually
  as the individual agents accumulate experience
  the system constantly adapts.
• Cross-cutting Hierarchical Organization economy
  has many levels of organization and interaction.
  Units at any given level behaviors, actions,
  strategies, products typically serve as "building
  blocks" for constructing units at the next higher
  level. The overall organization is more than
  hierarchical, with many sorts of tangling
  interactions (associations, channels of
  communication) across levels.

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Complexity Economics (2/2)

• Dispersed Interaction What happens in the
  economy is determined by the interaction of many
  dispersed, possibly heterogeneous, agents acting
  in parallel. The action of any given agent
  depends upon the anticipated actions of a limited
  number of other agents and on the aggregate state
  these agents co-create.
• Perpetual Novelty Niches These are continually
  created by new markets, new technologies, new
  behaviors, new institutions. The very act of
  filling a niche may provide new niches. The
  result is ongoing, perpetual novelty.
• Out-of-Equilibrium Dynamics Because new niches,
  new potentials, new possibilities, are
  continually created, the economy operates far
  from any optimum or global equilibrium.
  Improvements are always possible and indeed occur
  regularly.

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Complexity Economics (1/3)
Complexity Economics Traditional Economics
Agents Modelled individually use inductive rules of thumb to make decisions have incomplete information are subject to errors and biases learn to adapt over time heterogeneous agents Modelled collectively use complex deductive calculations to make decisions have complete information make no errors and have no biases have no need for learning or adaptation (are already perfect), mostly homogeneous agents
Networks Explicitly model bi-lateral interactions between individual agents networks of relationships change over time Assume agents only interact indirectly through market mechanisms (e.g. auctions)
Emergence No distinction between micro/macro economics macro patterns are emergent result of micro level behaviours and interactions. Micro-and macroeconomics remain separate disciplines
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Complexity Economics (2/3)
Complexity Economics Traditional Economics
Evolution The evolutionary process of differentiation, selection and amplification provides the system with novelty and is responsible for its growth in order and complexity No mechanism for endogenously creating novelty, or growth in order and complexity
Technology Technology fluid, endogenous to the system Technology as given or selected on economic basis
Preferences Formulation of preferences becomes central individuals not necessarily selfish Preferences given Individuals selfish
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Complexity Economics (3/3)
Complexity Economics Traditional Economics
Origins from Physical Sciences Based on Biology (structure, pattern, self-organized, life cycle) Based on 19th century physics (equilibrium, stability, deterministic dynamics)
Elements Patterns and Possibilities Price and Quantity

• Complex systems emerge and maintain on the edge
  of chaos - the narrow domain between frozen
  constancy and chaotic turbulence

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Evolutionary theory Economics

• Connections Evolutionary theory ? Economics
• One of the fundamental problems in economics -
  Bounded rationality
• How can agents who are not infinitely rational
  and do not have infinite computational resources
  get along in their worlds?
• There is an optimizing principle about precisely
  how intelligent such agents ought to be. If they
  are either too intelligent or too stupid - the
  system does not evolve well.

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Evolutionary Economy

• Heterodox school of economic thought that is
  inspired by evolutionary biology
• Much like mainstream economics, it stresses
  complex interdependencies, competition, growth,
  structural change, and resource constraints but
  differs in the approaches which are used to
  analyze these phenomena
• Paul Krugman What Economists Can Learn From
  Evolutionary Theorists
• Economics is the study of phenomena that can be
  understood as emerging from the interactions
  among intelligent, self-interested individuals

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Evolutionary Economy

• Paul Krugman
• Economics is about what individuals do
• The individuals are self-interested
• The individuals are intelligent
• We are concerned with the interaction of such
  individuals
• Whats different in comparison to the biological
  evolution? (BTW there is some difference)
• Evolutionary theory about the interaction of
  self-interested individuals

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Agent-based Computational Economics

• ACE simulates and models economies as evolving
  systems of autonomous interacting agents
• Growing Economies from the bottom-up
• Multi-agent system - a system composed of
  multiple interacting intelligent agents, can be
  used to solve problems, which are difficult or
  impossible for an individual agent or monolithic
  system to solve.
• Examples online trading, disaster response,
  modelling social structures

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Agent-based Computational Economics

• Altreva Adaptive Modeler - Building agent-based
  market simulation models for price forecasting of
  real-world stocks and other securities. A
  software application for creating financial
  market simulation models for the purpose of
  forecasting prices of real world market traded
  stocks or other securities or assets.

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Economics with heterogenous interacting agents

• Collaborate, compete and share
• Collective behaviour of a population of
  interacting individuals often exhibits surprising
  properties, which can hardly be anticipated on
  the basis of the micro-economic interaction
• Predictions of the game theory, however, are
  often contradicted by empirical and experimental
  research already in simple cases (the prisoners
  dilemma, the ultimatum game)
• Doubts of the game theory validity in cases where
  individuals face a more complex strategic
  problem, involving a large number of other
  agents, uncertainty and limited information

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Non-equilibrium Economy

• Deals with processes that exhibit
  self-reinforcing causation, as opposed to
  standard neoclassical equilibrium economics
• Represented by modern researchers in the fields
  of evolutionary-institutional economics, Post
  Keynesian economics, Ecological Economics,
  development and growth economics
• "The Foundations of Non-Equilibrium Economics
  The Principle of Circular Cumulative Causation"
  (2009), Routledge

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Attention Economy

• Approach to the management of information that
  treats human attention as a scarce commodity, and
  applies economic theory to solve various
  information management problems
• Attention is focused mental engagement on a
  particular item of information. Items come into
  our awareness, we attend to a particular item,
  and then we decide whether to act (Davenport
  Beck 2001)
• A wealth of information creates a poverty of
  attention and a need to allocate that attention
  efficiently among the overabundance of
  information sources that might consume it (Simon
  1971)
• Social attention
• Dedicating too much attention to social
  interactions ? "social interaction overload"

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Attention Economy

• Coined by T. Davenport
• Understanding and managing attention is now the
  single most important determinant of business
  success."
• Thomas H. Davenport and John C. Beck, The
  Attention Economy Understanding the New Currency
  of Business (Boston Harvard Business School
  Press, 2001).

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Attention Economy
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Collective Intelligence

• A shared or group intelligence that emerges from
  the collaboration competition of many
  individuals
• The capacity of human communities to evolve
  towards higher order complexity and harmony,
  through such innovation mechanisms as
  differentiation integration, competition,
  collaboration
• Appears in a wide variety of forms of consensus
  decision making in bacteria, animals, humans,
  computer networks
• Networking enabled by Web 2.0 (Enterprise 2.0),
• cf. group think and individual cognitive bias
• Collective Intelligence networks Prediction
  Markets
• enormously efficient means to harbor and codify
  vast landscapes of information and bring them to
  bear on the most difficult problems -
  productivity, innovation and business performance

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Swarm Intelligence (SI)

• SI describes collective behavior of
  decentralized, self-organized systems, natural or
  artificial. SI systems - typically made up of a
  population of simple agents or boids interacting
  locally with one another and with their
  environment. The agents follow very simple rules,
  and although there is no centralized control
  structure dictating how individual agents should
  behave, local, and to a certain degree random,
  interactions between such agents lead to the
  emergence of "intelligent" global behavior,
  unknown to the individual agents. Examples of SI
  ant colonies, bird flocking, animal herding,
  bacterial growth,

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Wikinomics

• How Mass Collaboration Changes Everything, Don
  Tapscott and Anthony D. Williams
• Four ideas Openness, Peering, Sharing, Acting
  Globally
• Instead of an organized business body brought
  into being specifically for a unique function,
  mass collaboration relies on free individual
  agents to come together and cooperate to improve
  a given operation or solve a problem
  (Crowdsourcing)
• Coase's Law A firm will tend to expand until the
  cost of organizing an extra transaction within
  the firm become equal to the costs of carrying
  out the same transaction on the open market
• Inversion of Coase's Law A firm will tend to
  expand until the cost of carrying out an extra
  transaction on the open market become equal to
  the costs of organizing the same transaction
  within the firm

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Other economics

• Neuroeconomics
• combines neuroscience, economics psychology to
  study how people make decisions
• looks at the role of the brain when we evaluate
  decisions, categorize risks and rewards, and
  interact with each other
• Service Economics
• Service Oriented Economy

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Reflexivita (George Soros)

• Pomocou tohto princípu sa dívam na trhy. ... To,
  že trhy sú flexibilné platí, ale len do istej
  miery. Neviditelná ruka trhu nie je neomylná, nie
  vždy. ... Za normálnych okolností hladia trhy na
  realitu s miernym podozrením. Ale obcas sa stane,
  že nálady trhov sa šíria po špirále, bez
  sebakontroly, mohutnejú až do seba-deštrukcnej
  sily vtedy nastávajú bubliny.
• Po prvé, financné trhy nereflektujú presne
  existujúcu situáciu, poskytujú obraz, ktorý je
  istým spôsobom zaujatý (biased) alebo
  skreslený. Po druhé, skreslené názory úcastníkov
  trhu, ktoré sa prejavujú v trhových cenách, môžu
  za istých podmienok ovplyvnit fundamenty, ktoré
  by mali trhové ceny reflektovat ...

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Reflexivita (George Soros)

• Trhy obycajne samy korigujú svoje chyby, ale
  obcas do nich preklzne nesprávne
  pochopenie/interpretácia, ktorá je schopná
  upevnit trend, ktorý už existuje v skutocnosti, a
  tým upevnit samu seba. Takéto sebaupevnujúce
  procesy môžu odtlacit trhy daleko od stavu
  rovnováhy. ... (tento proces) môže pokracovat
  dovtedy, kým nesprávna interpretácia zacne byt
  tak ocividná, že jej nesprávnost všetci pochopia
  ...
• Túto obojstrannú spätnú, cyklickú spätnú väzbu
  medzi trhom, cenami a podcenenou realitou volám
  reflexivita.
• Reflexivity circular, bidirectional
  relationships between cause and effect, both the
  cause and the effect affect one another in a
  situation that renders both functions causes and
  effects
• Observations or actions of observers in the
  social system affect the very situations they are
  observing

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Bounded Rationality (Herbert Simon)

• Rationality of individuals is limited by the
  information they have, the cognitive limitations
  of their minds, and the finite amount of time
  they have to make decisions
• Since decision-makers lack the ability and
  resources to arrive at the optimal solution, they
  apply their rationality only after having
  greatly simplified the choices available
• Economic agents employ the use of heuristics to
  make decisions rather than a strict rigid rule of
  optimization
• They do this because of the complexity of the
  situation, and their inability to process and
  compute the expected utility of every alternative
  action
• In contrast with the concept of rationality as
  optimization

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Bounded rationality (Herbert Simon)

• Decision-maker is a satisficer (one seeking a
  satisfactory solution) rather than optimizer
• Perfectly rational decisions are often not
  feasible in practice due to the finite
  computational resources available for making them
• Most people are only partly rational, and are
  emotional/irrational in the remaining part of
  their actions
• Economics is also about scarcity of our
  computational resources!

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Related topics

• Systems theory - an interdisciplinary theory
  about the nature of complex systems, a framework
  by which one can investigate and/or describe any
  group of objects that work together to produce
  some result. First originated in biology in the
  1920s out of the need to explain the
  interrelatedness of organisms in ecosystems
  (Ludwig von Bertalanffy)
• Scientific modelling is the process of generating
  abstract, conceptual, graphical and/or
  mathematical models
• Memetics - theoretical and empirical science that
  studies the replication, spread and evolution of
  memes
• Meme an information pattern held in an
  individual's memory, which is capable of being
  copied to another individual's memory / a
  cognitive or behavioral pattern that can be
  transmitted from one individual to another one /
  contagious ideas, all competing for a share of
  our mind

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Related topics

• Chaos theory - an area of inquiry studying the
  behavior of dynamical systems that are highly
  sensitive to initial conditions - the butterfly
  effect - small differences in initial conditions
  yield widely diverging outcomes for chaotic
  systems, rendering long-term prediction
  impossible in general
• Applied in biology, computer science, economics,
  finance, physics, politics, population dynamics,
  psychology, ...
• Second order cybernetics (cybernetics of
  cybernetics)
• Investigates cybernetics with awareness that the
  investigators are part of the system
• Importance of self-referentiality,
  self-organizing, the subject-object problem
• To construct a model of the mind ? a brain is
  required to write a theory of a brain

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Related topics

• Ilya Prigogine - dissipative structures and their
  role in thermodynamic systems far from
  equilibrium
• Dissipative structures - led to pioneering
  research in self-organizing systems, as well as
  philosophic inquiries into the formation of
  complexity on biological entities
• Organisms are unstable systems existing far from
  thermodynamic equilibrium, due to sensitivity to
  initial conditions, unstable systems can only be
  explained statistically

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Related topics

• Autopoesis - "auto (self)-creation" - expresses a
  fundamental dialectic between structure and
  function
• Introduced by Humberto Maturana and Francisco
  Varela
• An autopoietic machine is a machine organized
  (defined as a unity) as a network of processes of
  production (transformation and destruction) of
  components which
• i) through their interactions and transformations
  continuously regenerate and realize the network
  of processes (relations) that produced them and
• ii) constitute it (the machine) as a concrete
  unity in space in which they (the components)
  exist by specifying the topological domain of its
  realization as such a network

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Related topics

• Dispersed knowledge (in economics) - information
  that is dispersed throughout the marketplace, and
  is not in the hands of any single agent. All
  agents in the market have imperfect knowledge
  however, they all have a good indicator of
  everyone else's knowledge and intentions, and
  that is the price
• Price signals are one possible solution to the
  economic calculation problem.
• popular especially among Austrian School
  economists such as Friedrich Hayek

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Related topics

• Evolution of knowledge (cf. evolutionary
  epistemology) as a part of the cultural evolution
  can be modelled through the same basic principles
  of variation and selection that underly
  biological evolution. Shift from genes as units
  of biological information to memes (a new type of
  units of cultural information)
• ? Richard Dawkins
• A bifurcation occurs when a small smooth change
  made to the parameter values (the bifurcation
  parameters) of a system causes a sudden
  'qualitative' or topological change in its
  behaviour

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Bifurcation diagram
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Related topics

• Crowdsourcing - the act of taking tasks
  traditionally performed by an employee or
  contractor, and outsourcing them to a group
  (crowd) of people or community in the form of an
  open call
• Distributed problem-solving and production model
  (to develop a new technology, carry out a design
  task etc.)
• Social software - a range of SW systems that
  allow users to interact and share data MySpace,
  Facebook, Flickr, Linked-In, YouTube
• Enterprise social software (a major component of
  Enterprise 2.0), comprises social software as
  used in "enterprise" (business/commercial)
  contexts
• Enterprise 2.0 - provides business managers with
  access to the right information at the right time
  through a web of inter-connected applications,
  services and devices. Enterprise 2.0 makes
  accessible the collective intelligence of many,
  translating to a huge competitive advantage in
  the form of increased innovation, productivity
  and agility

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Enterprise 1.0 vs. Enterprise 2.0
Enterprise 1.0 Enterprise 2.0
Hierarchy Flat Organization
Friction Ease of Organization Flow
Bureaucracy Agility
Inflexibility Flexibility
IT-driven technology / Lack of user control User-driven technology
Top down Bottom up
Centralized Distributed
Teams are in one building / one time zone Teams are global
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Enterprise 1.0 vs. Enterprise 2.0
Enterprise 1.0 Enterprise 2.0
Silos and boundaries Fuzzy boundaries, open borders
Need to know Transparency
Information systems are structured and dictated Information systems are emergent
Taxonomies Folksonomies
Overly complex Simple
Closed/ proprietary standards Open
Scheduled Open
Long time-to-market cycles Short time-to-market cycles
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61
Related topics

• Small World Network graph in which most nodes
  are not neighbours of one another, but most nodes
  can be reached from every other by a small number
  of hops or steps
• Small-world network characteristics priemerná
  vzdialenost medzi 2 uzlami siete Internet (10),
  Web (19), social networks - ludia (6, AKA six
  degrees of separation, Stanley Milgram), neuróny
  v mozgu (14), ...
• Bezškálová topológia s (niekolkými) dominantnými
  centrami, t.j. zdatní bohatnú
• mocninový zákon N(k) 1 / k?
• k konektivita uzla (pocet spojení daného uzla)
• N(k) pocet uzlov siete s konektivitou k
• ? exponent konektivity
• Štruktúra a vývoj sietí sa nedajú od seba oddelit
  
• Topológia vs. Stabilita a Robustnost komplexných
  sietí - závisí od ?

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Related topics

• Gödel's first incompleteness theorem - Any
  effectively generated theory, capable of
  expressing elementary arithmetic, cannot be both
  consistent and complete. In particular, for any
  consistent, effectively generated formal theory
  that proves certain basic arithmetic truths,
  there is an arithmetical statement that is true,
  but not provable in the theory.
• (Gödel's Second Incompleteness Theorem. In any
  consistent (axiomatizable) theory the consistency
  of the system is not provable in the system.)
• Alan Turing - undecidable problems (e.g. halting
  problem) ? no total computable function

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FuturICT Project

• http//www.futurict.ethz.ch/
• With our knowledge of the universe, we have sent
  men to the moon.
• We know microscopic details of objects around us
  and within us.
• And yet we know relatively little about how our
  society works and how it reacts to changes
  brought upon it.
• Humankind is now facing serious crises for which
  we must develop new ways to tackle the global
  challenges of humanity in the 21st century.
• It is thus timely to create an ICT Flagship to
  explore social life on Earth, and everything it
  relates to, in the same way that we have spent
  the last century or more understanding our
  physical world.
• This proposal sketches out visionary scientific
  endeavours, forming an ambitious concept that
  allows us to answer a whole range of challenging
  questions. Integrating the European engineering,
  natural, and social science communities ...
• Budget 1 billion EUR

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FuturICT Project Goals

• Develop novel ICT systems combining the best of
  human and computational abilities to support the
  understanding, integrative design, and management
  of complex systems,
• Apply these to model techno-social and economic,
  transport, environmental and other global
  systems,
• Create instruments to support the
  self-organization, decision-making and governance
  in politics, business, industry, and academia,
  with the aim to foster societal goals (e.g.
  robust techno-social and sustainable economic
  systems),
• Develop principles and tools facilitating
  emergence of high quality processes, products and
  institutions in techno-social networks.
• Multi-agent simulations of large systems (e.g.
  whole earth simulation, which may involve up to
  10 billion agents)
• Multi-agent simulations considering human
  cognitive psychological processes (e.g.
  personality, memory, strategic decision-making,
  emotions, creativity etc.)

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FuturICT Project

• Realistic Theory of Economic Systems
• Develop a realistic economic theory to give more
  reliable advise to decision-makers
• Go beyond the paradigms of the Homo Economicus
  (the perfect egoist), efficient markets,
  equilibrium models, and representative agent
  models (mean-field models)
• Develop agent-based models of boundedly rational
  behavior (e.g. limited cognitive capacities,
  behavioral biases and emotional aspects)
• Consider randomness, extreme events,
  heterogeneity, non-linearity, emergence, and
  complexity to yield a greater descriptive and
  predictive model validity
• Make models consistent with empirical and
  experimental data
• Work out the mathematical connection between
  microscopic and macroscopic economic theories

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Conclusions

• Trend - narastanie zložitosti / networking
  rastie pocet prepojení
• Globalizácia, interdisciplinarita,
  deterministický chaos
• Existujú medze zložitosti?
• Narastá gap medzi zložitým systémo a našim
  modelom tohto systému?
• Systémy obsahujúce kognitívne entity
• Self-reference, self-reflective, self-adaptation,
  self-organisation, self-awareness, consciousness,
  self-reproduction, ...
• Meta-modelling
• Reflexivity (Soros)
• Neúplnost poznania (Popper, ...)
• Princíp neurcitosti v poznaní (nástroj vs predmet
  poznania)
• Hypotéza obmedzenej racionality (bounded
  rationality)
• Pracujeme s neúplnymi modelmi

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Conclusions

• Economy of intangibles
• Špecifiká nehmotných aktív (informácie, znalosti,
  ...)
• Neúplnost nášho poznania
• Hypotéza obmedzenej racionality - H. Simon
• Matematická neúplnost systému Godel,
• Neúplný model zložitého systému
• Individual cognitive bias, group think
• Top-down vs. Bottom-up popisy/modely
• Agent-based modelling, emergencia
• Ekonómia veda o nerovnovážnych, dynamických
  systémoch
• Complex adaptive system M. Gell-Mann, J.
  Holland, S. Kauffman
• Je ekonomika systém, ktorý je nezávislý od našich
  predstáv, ocakávaní, modelov, teórií tohto
  systému?
• self-reflektivita

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Conclusions

• Siete
• Hypotéza malého sveta
• Bez-škálové grafy (scale-free graphs)
  robustnost
• Crowdsourcing, open innovation, ... - kedy je dav
  múdrejší ako jednotlivec a kedy je to viditelne
  naopak?
• Je inteligencia balansovanie na hrane chaosu a
  usporiadanosti?
• Co implikuje skutocnost, že ekonómia je
  spolocenská veda?
• ...
• V 60-tych rokoch 20. storocia vela pojmov
  a inšpirácií do spolocenských vied (psychológia,
  sociológia, ekonómia, ...) prichádzalo
  z fyzikálnych disciplín, v súcasnosti inšpirácia
  (resp. spôsob nazerania na systém) prichádza
  z biológie pojmy ako ekológia, (ko-)evolúcia
  (ako gradualistický proces), ...

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Zdroje

• http//en.wikipedia.org/wiki/Information_economy
• http//en.wikipedia.org/wiki/Complexity
• http//www.complexity-society.com/
• Journal Studies in Non-linear Dynamics
  Econometrics, http//www.bepress.com/snde/
• http//www.econ.iastate.edu/tesfatsi/ace.htm
• http//www.econ.iastate.edu/tesfatsi/ace.htm
• http//en.wikipedia.org/wiki/Comparison_of_agent-b
  ased_modeling_software
• http//en.wikipedia.org/wiki/Adaptive_Modeler -
  SW for creating financial market simulation
  models for the purpose of forecasting prices of
  real world market traded stocks, other
  securities, assets
• http//en.wikipedia.org/wiki/Complex_adaptive_syst
  em
• http//en.wikipedia.org/wiki/Service_economy
• http//pespmc1.vub.ac.be/

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Zdroje

• Memetika, http//pespmc1.vub.ac.be/memes.html,
  http//www.memecentral.com/
• Bifurcation theory, http//en.wikipedia.org/wiki/B
  ifurcation_theory
• JAMEL (Java Agent-based MacroEconomic Laboratory)
  - building agent-based macroeconomic simulations
• JASA (Java Auction Simulator API) - Computational
  economics Agent based computational economics
• http//en.wikipedia.org/wiki/Comparison_of_agent-b
  ased_modeling_software
• Growing Economies from the Bottom Up,
  http//www.econ.iastate.edu/tesfatsi/ace.htm
• http//en.wikipedia.org/wiki/Knowledge_economy
• http//en.wikipedia.org/wiki/Network_Economy
• Journal Review of Network Economy,
  http//www.bepress.com/rne/vol8/iss4/1/?sending10
  825
• http//en.wikipedia.org/wiki/Evolutionary_economic
  s
• Journal of Evolutionary Economics

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Zdroje

• http//en.wikipedia.org/wiki/Non-equilibrium_econo
  mics
• http//en.wikipedia.org/wiki/Quantum_economy
• http//en.wikipedia.org/wiki/Bounded_rationality
• http//en.wikipedia.org/wiki/Herbert_Simon
• http//en.wikipedia.org/wiki/Collective_intelligen
  ce
• http//en.wikipedia.org/wiki/Groupthink
• http//en.wikipedia.org/wiki/List_of_cognitive_bia
  ses
• http//en.wikipedia.org/wiki/Neuroeconomics
• http//en.wikipedia.org/wiki/Behavioral_economics
• http//en.wikipedia.org/wiki/Wikinomics
• http//en.wikipedia.org/wiki/Complexity_economics
• http//en.wikipedia.org/wiki/Crowdsourcing
• http//en.wikipedia.org/wiki/Social_software
• http//en.wikipedia.org/wiki/Autopoiesis

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Zdroje

• http//www.e2conf.com/about/what-is-enterprise2.0.
  php
• http//en.wikipedia.org/wiki/Crowdsourcing
• http//en.wikipedia.org/wiki/Mathematical_model
• http//en.wikipedia.org/wiki/Social_software
• http//en.wikipedia.org/wiki/Multi-agent_system
• http//en.wikipedia.org/wiki/Small-world_network
• http//en.wikipedia.org/wiki/Prediction_markets
• http//en.wikipedia.org/wiki/GC3B6del27s_incomp
  leteness_theorems
• http//en.wikipedia.org/wiki/Chaos_theory
• http//en.wikipedia.org/wiki/Complex_systems
• http//en.wikipedia.org/wiki/Systems_theory
• http//en.wikipedia.org/wiki/Prigogine
• http//en.wikipedia.org/wiki/Dispersed_knowledge

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Intellectuals are not original thinkers, but
purveyors of second-hand ideas (F. Hayek)

• Ako vôbec môže niekto taký ako my - výsledok
  slepých zápasov evolúcie - dosiahnut akúkolvek
  formu neomylnosti?
• Preto musím vo vede stále pripustit, že sa môžem
  vo všetkom mýlit.
• To však znamená aj to, že sa môžem mýlit v tom,
  že sa vo všetkom mýlim.

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• Dakujem za pozornost a vytrvalost!
• Tomas.Sabol_at_tuke.sk

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