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How to Be a Strategic Futurist: An Evolutionary Developmental Perspective on Accelerating Change

How to Be a Strategic Futurist: An Evolutionary Developmental Perspective on Accelerating Change US Army War College Strategic Leadership 2005 John Smart, President, ASF Slides: accelerating.org/slides.html. Presentation Outline. 1. Introduction 2. Assumptions

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How to Be a Strategic Futurist: An Evolutionary Developmental Perspective on Accelerating Change

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  1. How to Be a Strategic Futurist: An Evolutionary Developmental Perspective on Accelerating Change US Army War CollegeStrategic Leadership 2005John Smart, President, ASF Slides: accelerating.org/slides.html

  2. Presentation Outline 1. Introduction 2. Assumptions 3. Two Processes of Change: Evol. and Development 4. Introduction to Accelerating Change 5. Prediction: Expecting the Future 6. Management: Thriving with Change 7. Creation: Making the Future 8. Group Discussion © 2005 Accelerating.org

  3. 1. Introduction

  4. Acceleration Studies Foundation • ASF (Accelerating.org) is a nonprofit community of 3,100 scientists, technologists, entrepreneurs, administrators, educators, analysts, humanists, and systems theorists discussing and dissecting accelerating change. • We practice “developmentalfuture studies,” that is, we seek to discover a set of persistent factors, stable trends, convergent capacities, and highly probable scenarios for our common future, and to use this information now to improve our daily evolutionary choices. • Specifically, these include accelerating intelligence, immunity, and interdependence in our global sociotechnological systems, increasing technological autonomy, and the increasing intimacy of the human-machine, physical-digital interface. © 2005 Accelerating.org

  5. Brief History of Futures Studies • 1902, H.G. Wells, Anticipations • 1904, Henry Adams, A Law of Acceleration • 1945, Project RAND (RAND Corp.) • 1946, Stanford Research Institute (SRI International) • 1962, Arthur C. Clarke, Profiles of the Future • 1967, World Future Society, Institute for the Future • 1970, Alvin Toffler, Future Shock • 1974, University of Houston, Studies of the Future M.S. • 1977, Carl Sagan, Dragons of Eden • 1986, Eric Drexler, Engines of Creation, • 1995, Tamkang U, Center for Futures Studies • 1999, Ray Kurzweil, Age of Spiritual Machines • 2002, Acceleration Studies Foundation © 2005 Accelerating.org

  6. Four Types of Futures Studies • Exploratory (Speculative Literature, Art) • Consensus-Driven (Political, Trade Organizations) • Agenda-Driven (Institutional, Strategic Plans) • Research-Predictive(Stable Developmental Trends) • The last is the critical one for acceleration studies and development studies • It is also the only one generating falsifiable hypotheses • Accelerating and increasingly efficient, autonomous, miniaturized, and localized computation is apparently a fundamental meta-stable universal developmental trend. Or not. That is a key hypothesis we seek to address. © 2005 Accelerating.org

  7. Warning: Never Trust a Single Futurist (Including Me)Never Make Big Decisions Without Using a Futures Network Each of us sees only a piece of the elephant and is easily wrong. A multi-biased network gives you a wider and deeper map of the possibility space. This will make you more adaptive, and may make you more foresighted. Modern culture spends a lot of time in the past and present, but very little thinking about personal, organizational, and global futures. Learn to fight this increasingly costly bias. Lesson: Develop your network, map the controversies, have tolerance for ambiguity, seek good data, notice weak signals, optimize today but expect emergence. Be skeptical. Consult the crowd but make your own decisions. “You can’t get an unbiased education, so the next best thing is a multi-biased one.”  Buckminster Fuller © 2005 Accelerating.org

  8. Graduate Foresight Programs:Futures Studies, STS, Roadmapping • Futures Studies (two U.S. graduate programs) • Science and Technology Studies (30+ U.S. programs) • Tech Roadmapping (five U.S. programs. First PhD under Mike Radnor at Northwestern in 1998). Artificial Life, Complexity Science, Systems Science, Simulation Learning: All still too early for foresight specializations. To date only tech roadmapping is falsifiable, and is a process presently being used for major capital investment in industry (e.g. ITRS, which began as NTRS only in 1992). Tech Roadmapping is the closest yet to Acceleration and Development Studies. © 2005 Accelerating.org

  9. Foresight Development:Future Prediction, Mgmt, and Creation • Prediction • forecasting methods, metrics, statistical trends, the history of prediction, technology roadmapping, science and systems theory, marketing research • Management • environmental scanning, competitive intelligence, networking, scenario development, risk analysis, hedging, enterprise robustness, planning, matter, energy, space, and time management systems • Creation • personal and entrepreneurial tools for creating individually preferred futures, research and development, creative thinking, positive psychology, social networking, business plan production © 2005 Accelerating.org

  10. Where are the U.S. College Courses in Foresight Development? • Tamkang University • 27,000 undergrads • Top-ranked private university in Taiwan • Like history and current affairs, futures studies (15 courses to choose from) have been a general education requirement since 1995. • Why not here? © 2005 Accelerating.org

  11. 2. Assumptions

  12. Systems Theory Systems Theorists Make Things Simple (sometimes too simple!) "Everything should be made as simple as possible, but not simpler." — Albert Einstein © 2005 Accelerating.org

  13. The Infopomorphic Paradigm The universe is a physical-computational system. We exist for information theoretic reasons. We’re here to discover, think/emote, and create. © 2005 Accelerating.org

  14. The MESTI Universe Matter, Energy, Space, Time  Information Increasingly Understood  Poorly Known MEST Compression/Density/Efficiency drives accelerating change. © 2005 Accelerating.org

  15. Physics of a “MESTI” Universe Physical Driver: • MEST Compression/Efficiency/Density Emergent Properties: • Information Intelligence (World Models) • Information Interdepence (Ethics) • Information Immunity (Resiliency) • Information Incompleteness (Search) An Interesting Speculation in Information Theory: Entropy = Negentropy Universal Energy Potential is Conserved. © 2005 Accelerating.org

  16. Eric Chaisson’s “Phi” (Φ): A Universal Moore’s Law Curve Ф Free Energy Rate Density Substrate (ergs/second/gram) Galaxies 0.5 Stars2(counterintuitive) Planets (Early) 75 Plants 900 Animals/Genetics 20,000(10^4) Brains (Human) 150,000(10^5) Culture (Human) 500,000(10^5) Int. Comb. Engines (10^6) Jets (10^8) Pentium Chips (10^11) time Source: Eric Chaisson, Cosmic Evolution, 2001 © 2005 Accelerating.org

  17. Strategic/Integral Foresight:Skill Sets and Processes © 2005 Accelerating.org

  18. Strategic/Integral Thinking:Edward De Bono’s Six Thinking Hats © 2005 Accelerating.org

  19. Strategic/Integral Maps:Ken Wilber’s Process/Mgmt Quadrants Computational Processes • We need foresight in all quadrants (processes and management tests). • All drive change. • None can be reduced to the others • There are no others as basic! Management/Validity Tests © 2005 Accelerating.org

  20. Types of Intelligence:Gardner’s ‘Frames’/ ‘Modules’ Gardner has developed research and metrics for eight different “frames” or “modules” of human capacity. A great way to look at thinking. © 2005 Accelerating.org

  21. Types of Intelligence:Wilber’s ‘Lines/Vectors’ • Meta/Transcendent/Spiritual Attractor Wilber proposes at least twice as many intelligence lines/dimensions than Gardner. I’ve mapped the ones that I think are justified to his quadrants, above. Wilber also proposes all lines follow a developmental vector, that the higher levels of all lines look spiritual, and that the spiritual line is a convergent intelligence attractor that continually seeks to look meta (above, beyond) all the other lines. © 2005 Accelerating.org

  22. Vectors of Development:Sequential Growth Stages Stages are probability functions, not discrete “levels” of development. They are sequential and directional, but you can regress with abnormal trauma or deterioration. © 2005 Accelerating.org

  23. Gilligan’s Stages of Female Moral Development Stages are probabilities, but they are sequential and directional. This is reasonably good research. Carol Gilligan © 2005 Accelerating.org

  24. Debser’s Stages of Cultural Development Some stage conceptions have a lot less evidence at present, but seem good candidates for further research. Eugene Debser © 2005 Accelerating.org

  25. Maslow’s Hierarchy of Self-NeedsSmart’s Hierarchy of Socioeconomics Biological Learning Stages Technological Learning Stages Self-Transcendence (Religion & Death) Bio-Transcension? Digital Twin IT Society Valuecosm IT Society Network IT Society Manufacturing Society Agricultural Society / Property © 2005 Accelerating.org

  26. 3. Two Processes of Change: Evolution and Development

  27. The Left and Right Hands of “Evolutionary Development” Replication & Variation “Natural Selection” Adaptive Radiation Chaos, Contingency Pseudo-Random Search Strange Attractors Evolution Selection & Convergence “Convergent Selection” Emergence,Global Optima MEST-Compression Standard Attractors Development Complex Environmental Interaction Left Hand Right Hand New Computat’l Phase Space Opening Well-Explored Phase Space Optimization © 2005 Accelerating.org

  28. Evolution vs. Development“The Twin’s Thumbprints” Consider two identical twins: Thumbprints Brain wiring Evolution drives almost all the unique local patterns. Development creates the predictable global patterns. © 2005 Accelerating.org

  29. Marbles, Landscapes, and Basins (Complex Systems, Evolution, & Development) The marbles (systems) roll around on the landscape, each taking unpredictable (evolutionary) paths. But the paths predictably converge (development) on low points (MEST compression), the “attractors” at the bottom of each basin. © 2005 Accelerating.org

  30. How Many Eyes Are Developmentally Optimal? Evolution tried this experiment. Development calculated an operational optimum. Some reptiles (e.g. Xantusia vigilis, andcertain skinks) still have a parietal (“pineal”) vestigial third eye. © 2005 Accelerating.org

  31. How Many Wheels are Developmentally Optimal on an Automobile? Examples: Wheel on Earth. Social computation device. Diffusion proportional to population density and diversity. © 2005 Accelerating.org

  32. Evolution and Development:Two Universal Systems Processes Each are pairs of a fundamental dichotomy, polar opposites, conflicting models for understanding universal change. The easy observation is that both processes have explanatory value in different contexts. The deeper question is when, where, and how they interrelate. © 2005 Accelerating.org

  33. Political Polarities: Innovation vs. Sustainability Evo-Devo Theory Brings Process Balance to Political Dialogs on Innovation and Sustainability Developmental sustainability without generativity creates sterility, clonality, overdetermination, adaptive weakness (Maoism). Evolutionary generativity (innovation) without sustainability creates chaos, entropy, a destruction that is not naturally recycling/creative (Anarchocapitalism). © 2005 Accelerating.org

  34. 4. Introduction to Accelerating Change

  35. From the Big Bang to Complex Stars: “The Decelerating Phase” of Universal ED © 2005 Accelerating.org

  36. From Biogenesis to Intelligent Technology: The “Accelerating Phase” of Universal ED Carl Sagan’s “Cosmic Calendar” (Dragons of Eden, 1977) Each month is roughly 1 billion years. © 2005 Accelerating.org

  37. A U-Shaped Curve of Change Big Bang Singularity Developmental Singularity? 50 yrs ago: Machina silico 50 yrs: Scalar Field Scaffolds 100,000 yrs: Matter 100,000 yrs ago: H. sap. sap. 1B yrs: Protogalaxies 8B yrs: Earth © 2005 Accelerating.org

  38. Punctuated Equilibrium (in Biology, Technology, Economics, Politics…) • Eldredge and Gould (Biological Species) • Pareto’s Law (“The 80/20 Rule”) (income distribution  technology, econ, politics) Rule of Thumb: 20% Punctuation (Development) 80% Equilibrium (Evolution) Suggested Reading: For the 20%: Clay Christiansen, The Innovator's Dilemma For the 80%: Jason Jennings, Less is More © 2005 Accelerating.org

  39. Different Kinds of Accelerations: Efficiency vs. Transformation Business Week’s First Edition, October 1929: • IBM has an ad for “electric sorting machines.” • PG&E has an ad announcing natural gas powered factories in San Francisco. Could we have predicted that one of these technologies would continually transform itself while another would experience accelerating efficiencies but, on the surface, be unchanged? © 2005 Accelerating.org

  40. Lesson: Maintaining Equilibrium is Our 80% Adaptive Strategy While we try unpredictable evolutionary strategies to improve our intelligence, interdependence, and resiliency, these won’t always work. What is certain is that successful solutions always increase MEST efficiency, they “do more with less.” Strategies to capitalize on this:  Teach efficiency as a civic and business skill.  Look globally to find resource-efficient solutions.  Practice competitive intelligence for MEST-efficiency.  Build a national culture that rewards refinements. Examples: Brazil's Urban Bus System. Open Source Software. Last year’s mature technologies. Recycling. 30 million old cell phones in U.S. homes and businesses. © 2005 Accelerating.org

  41. A Saturation Lesson: Biology vs. Technology How S Curves Get Old Resource limits in a niche Material Energetic Spatial Temporal Competitive limits in a niche Intelligence/Info-Processing No Known or Historical Limits to Information Acceleration 1. Our special universal structure permits each new computational substrate tobe far more MEST resource-efficient than the last2. The most complex local systems have no intellectual competition Result: No Apparent Limits to the Acceleration of Local Intelligence, Interdependence, and Immunity in New Substrates Over Time © 2005 Accelerating.org

  42. The Technological Singularity Hypothesis Each unique physical-computational substrate appears to have its own “capability curve.” The information inherent in these substrates is apparently not made obsolete, but is instead incorporated into the developmental architecture of the next emergent system. © 2005 Accelerating.org

  43. Henry Adams, 1909: The First “Singularity Theorist” The final Ethereal Phase would last only about four years, and thereafter "bring Thought to the limit of its possibilities." Wild speculation or computational reality? Still too early to tell, at present. © 2005 Accelerating.org

  44. Something Curious Is Going On Unexplained. (Don’t look for this in your physics or information theory texts…) © 2005 Accelerating.org

  45. The Developmental Spiral • Homo Habilis Age 2,000,000 yrs ago • Homo Sapiens Age 100,000 yrs • Tribal/Cro-Magnon Age 40,000 yrs • Agricultural Age 7,000 yrs • Empires Age 2,500 yrs • Scientific Age 380 yrs (1500-1770) • Industrial Age 180 yrs (1770-1950) • Information Age 70 yrs (1950-2020) • Symbiotic Age 30 yrs (2020-2050) • Autonomy Age 10 yrs (2050-2060) • Tech Singularity ≈ 2060 © 2005 Accelerating.org

  46. Four Pre-Singularity Subcycles? • A 30-yearcycle, from 1990-2020 • 1st gen "stupid net "/early IA, weak nano, 2nd gen Robots, early Ev Comp. World security begins. • A 20-year cycle, from 2020-2040 • CUI network, Biotech, not bio-augmentation, Adaptive Robots, Peace/Justice Crusades. • A 10-year cycle, from 2040-2050 • CUI personality capture (weak uploading), Mature Self-Reconfig./Evolutionary Computing. • 2050: Era of Strong Autonomy • Progressively shorter 5-, 2-, 1-year tech cycles, each more autocatalytic, seamless, human-centric. © 2005 Accelerating.org

  47. Macrohistorical Singularity Books The Evolutionary Trajectory, 1998 Singularity 2130 ±20 years Trees of Evolution, 2000 Singularity 2080 ±30 years © 2005 Accelerating.org

  48. Macrohistorical Singularity Books The Singularity is Near, 2005 Singularity 2050 ±20 years Why Stock Markets Crash, 2003 Singularity 2050 ±10 years © 2005 Accelerating.org

  49. “Unreasonable” Effectiveness and Efficiency: Wigner and Mead The Unreasonable Effectiveness of Mathematics in the Natural Sciences, Nobel Laureate Eugene Wigner, 1960 After Wigner and Freeman Dyson’s work in 1951, on symmetries and simple universalities in mathematical physics. Commentary on the “Unreasonable Efficiency of Physics in the Microcosm,” VSLI Pioneer Carver Mead, c. 1980. W=(1/2mv2) F=ma E=mc2 F=-(Gm1m2)/r2 In 1968, Mead predicted we would create much smaller (to 0.15 micron) multi-million chip transistors that would run far faster and more efficiently. He later generalized this observation to a number of other devices. © 2005 Accelerating.org

  50. Example: Holey Optical Fibers • Above: SEM image of a photonic crystal fiber. Note periodic array of air holes. The central defect (missing hole in the middle) acts as the fiber's core. The fiber is about 40 microns across. • This conversion system is a million times (106) more energy efficient than all previous converters. These are the kinds of jaw-dropping efficiency advances that continue to drive the ICT and networking revolutions. • Such advances are due even more to human discovery (in physical microspace) than to human creativity, which is why they have accelerated throughout the 20th century, even as we remain uncertain exactly why they continue to occur. Lasers today can made cheaply only in some areas of the EM spectrum, not including, for example, UV laser light for cancer detection and tissue analysis. It was discovered in 2004 that a hollow optical fiber filled with hydrogen gas, a device known as a "photonic crystal," can convert cheap laser light to the wavelengths previously unavailable. © 2005 Accelerating.org

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