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What is Complexity For?

You say simple, I say tomato. An intended inspirational talk about complexity March 2013

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What is Complexity For?

  1. 1. What is Complexity for? A primer By Francisco J. Jariego You say simple, I say tomato
  2. 2. We like simplicity
  3. 3. You have to work hard to get your thinking clean to make it simple
  4. 4. Pluralitasnon estponendasine necessitate William of Ockham (c. 1287 –1347)
  5. 5. Simple is a better compre(hen)ssionalgorithm “that's why the equations look so simple. Because they use mathematics we already have.” “The more and more symmetryyou have, the better you exhibit the simplicity and elegance of the theory.” “Life can emerge from physics and chemistry plus a lot of accidents” “On beauty and truth in physics” Murray Gell-Mann
  6. 6. …then why is complexity increasing?
  7. 7. Modern innovations make us feel dumber, because they add to the work our minds must do. The World Grows More Complex (NYT) Society has become more complex-and g loaded-as we have entered the information age and postindustrial economy. (…) The new workplace puts a premium on higher order thinking, learning, and information-processing skills (…) Daily life also seems to have become considerably more complex (Why G Matters) Our ancestors lived in a more dangerous but less risky environment. Because interdependence exposes everyone around the world in an unprecedented way, governing global risks is humanity’s great challenge. (The New Grammar of Power) Fifty years ago, our technologies, our organizations and our lives were less complicated than today Complexity tends to increase as functions and modifications are added to a system to break through limitations, handle exceptional circumstances, or adapt to a world itself more complex (Why Things Become More Complex) Societies become more complex as they try to solve problems. Complexity is a primary problem-solving strategy, which is often successful in the short-term, but cumulatively may become detrimental to sustainability (The Collapse of Complex Societies) Linda Gottfredson, physcology Javier Solana, David Innerarity, politics Brian W. Arthur, Economics Joseph Tainter, Anthropology and History
  8. 8. The growth of complexity is reflected in businesses’ goals. Todaycompanies, on average, set themselves six times as many performance requirements as they did in 1955. Back then, CEOs committed to four to seven performance imperatives; today they commit to 25 to 40. And many of those requirements appear to be in conflict: Companies want to satisfy their customers, who demand low prices and high quality. They seek to customize their offerings for specific markets and standardize them for the greatest operating return. They want to innovate and be efficient. To reconcile their many conflicting goals, managers redesign the organization’s structure, performance measures, and incentives, trying to align employees’ behaviourwith shifting external challenges. More layers get added, more procedures imposed… Yves Morieux IBM, 2010 CEO Study
  9. 9. Is complexity going to kill us? Complexity Time Collective G Social, Technical, Economic Complexity
  10. 10. Cracking the complexity Code Complexity is increasingly unavoidable in companies, but the answer is not to pare back and simplify at all costs. Executives should try instead to understand where complexity matters and how to build the right processes, skills and culture to manage it.When companies treat complexity as something they must overcome, they miss an opportunity. Embracing complexity on an institutional and individual level –not just a strategic one- can bring a competitive advantage. Companies that understand this concept will create more valuethan their rivals, become more resilient, and make it harder for others to replicatewhat they are doing In and of itself, this complexity is not a bad thing—it brings opportunities as well as challenges (“Cracking the complexity Code”, McKinsey Quarterly 2007-2)
  11. 11. Hacking the Planet VENKAT’s Ribbonfarm, Hacking the Non-Disposable Planet
  12. 12. Does It Have to Be Hard?
  13. 13. Einstein’s Razor Everything should be made as simple as possible, but no simpler
  14. 14. No Silver Bullet Software entities are more complex for their size than perhaps any other human construct… The complexity of software is an essential property, not an accidental one. Hence, descriptions of a software entity that abstract away its complexity often abstract away its essence. For three centuries, mathematics and the physical sciences made great strides by constructing simplified models of complex phenomena, deriving properties from the models, and verifying those properties by experiment. This paradigm worked because the complexities ignored in the models were not the essential properties of the phenomena. It does not work when the complexities are the essence
  15. 15. Economic complexity matters because it helps explain differences in the level of income of countries, and more important, because it predicts future economic growth. Economic complexity might not be simple to accomplish, but the countries that do achieve it, tend to reap important rewards. (The Atlas of Economic Complexity, Hausmann, Hidalgo, et. Al.) What is economic complexity?
  16. 16. The Economy as an Evolving Complex System Viewing the economy as a complex adaptive system provides us with a new set of tools, techniques, and theories for explaining economic phenomena. Wealthmust be a product of evolutionary processes. Just as biological evolution summoned complex organisms and ecosystems out of the primordial soup, economic evolution has taken humankind from a state of nature to the modern global economy, filling the world with order, complexity, and diversity along the way
  17. 17. Does evolution creates complexity?
  18. 18. …well… Sooner or later a new simplifying conception is discovered that cuts at the root idea behind the old system and replaces it. Copernicus’s dazzlingly simple astronomical system, based on a heliocentric universe, replaced the hopelessly complicated Ptolemaic system And so growing complexity is often followed by renewed simplicityin a slow back-and forth dance. Brian W. Arthur
  19. 19. … the material resources are ultimately limited so the singularity is never reached i.e. unlimited growth is unsustainable. This lack of sustainability triggers a transition to a phase leading to stagnation and collapse. … to sustain continued growth, major innovations or adaptations must arise at an accelerated rate, because the time between “crisis” shortens as population grows. Something that took 10,000 years 20,000 years ago to make a change, now takes 25 years. There’s a clock that’s getting faster and faster. And so you have to innovate faster and faster in order to avoid the collapse
  20. 20. What’s complexity?
  21. 21. …uhm… The label of complexity often performs much the same role as that of the name of a desirable residential area in Estate Agent's Advertisements. It is applied to many items beyond the original area but which are still somewhere in the vicinity (B. Edmonds, “What is Complexity?”)
  22. 22. The many measures of complexity •Information; •Entropy; •Algorithmic Complexity or Algorithmic Information Content; •Minimum Description Length; •Fisher Information; •RenyiEntropy; •Code Length (prefix-free, Huffman, Shannon-Fano, error- correcting, Hamming); •ChernoffInformation; •Dimension; •Fractal Dimension; •Lempel--ZivComplexity. •Computational Complexity; •Time Computational Complexity; •Space Computational Complexity; •Information--Based Complexity; •Logical Depth; •Thermodynamic Depth; •Cost; •Crypticity. a) Effective Complexity •Metric Entropy; Fractal Dimension; Excess Entropy; •Stochastic Complexity; •Sophistication; •Effective Measure Complexity; •True Measure Complexity; •Topological epsilon-machine size; •Conditional Information; •Conditional Algorithmic Information Content; •Schema length; •Ideal Complexity; •Hierarchical Complexity; •Tree subgraphdiversity; •Homogeneous Complexity; •Grammatical Complexity. b) Mutual Information: •Algorithmic Mutual Information; •Channel Capacity; •Correlation; •Stored Information; •Organization. How hard is it to describe? How hard is it to build? Degree of organization Seth Lloyd, “Measures of Complexity a non--exhaustive list”
  23. 23. The many disciplines of complexity
  24. 24. Where does complexity come from?
  25. 25. More is different Philip Warren Anderson Symmetry Broken Reductionist hypothesis does not by any means imply a "constructionist" one. The ability to reduce everything to simple fundamental laws does not imply the ability to start from those laws and reconstruct the universe. In the so called N --> ∞ limit of large systems, matter will undergo mathematically sharp singular "phase transitions"to states in which the microscopic symmetries are in a sense violated.
  26. 26. Path Dependence Sub-optimal Lock-in Paul David, "Clio and the Economics of QWERTY“, 1985
  27. 27. Resiliency A system in which natural levels of variationhave been reduced through command-and-control activities will be less resilient than an unaltered system when subsequently faced with external perturbations, either of a natural (storms, fires, floods) or human-induced (social or institutional) origin. We believe this principle applies beyond ecosystems and is particularly relevant at the intersection of ecological, social, and economic systems. C.S. Holling& G.K. Mefee, “Command and Control and the Pathology of Natural Resource Management”, 1995
  28. 28. Self Organized Criticality Per Bak, Chao Tang, and Kurt Wiesenfeld, “Self-Organized Criticality”, 1988 A simple cellular automaton was shown to produce several characteristic features observed in natural complexity: fractal geometry, 1/f noise and power laws, in a way that could be linked to critical-point phenomena.
  29. 29. Maximal adaptability Complexity can be generated as an emergent feature of extended systems with simple local interactions
  30. 30. Anti-fragility
  31. 31. Now, your call
  32. 32. complex systems break in complex ways —the increasing complexity of modern hardware and software has made it virtually impossible to identify the flaws and vulnerabilities in computer systems and ensure that they are secure and trustworthy PROFILES IN SCIENCE PETER G. NEUMANN Killing the Computer to Save It The third school of thought is popularized by Netflixand is basically an invitation to break things, because a system that is so fragile that one code upgrade brings it down clearly isn’t resilient enough. In many ways, Netflix takes the idea of building out an architecture that’s dependent on a genius IT professional’s version of delicate pieces and crazy glue and flips it on its head. Instead of a fragile model car, Netflix is building the Tonka (HAS) trucks of IT—ready to take a few glitches while continuing to serve up videos. (“Google’s Gmail Outage Is a Sign of Things to Come”, Dec 2012)