Chapter 11. Evo Devo Foresight: Unpredictable and Predictable Futures

2. Developmental Factors

B. Cycles, Curves, Models, and Laws

Cycles, also known as pendulums, are a particularly simple and ubiquitous relationship between two variables. Think of the seasonal cycle, the business cycle, the hype cycle, the drama cycle, the Kuznets cycle, the plutocratic-democratic cycle, and the materialism-idealism-conflict (MIC) social cycle. Many of these are discussed in Chapter 6 (Models). Whenever we can find them, cycles are important predictable constraints on the future. Some cycles are chaotic, or irregularly irregular. That means we really can’t tell when the cycle will reverse itself. Others are only partly chaotic, meaning that the longer a system is at one extreme of the cycle (for example, plutocracy), the higher the probability that conditions will soon conspire to move it back toward the other extreme (hello democracy!). Groups like the Cycles Research Institute, the Foundation for the Study of Cycles, and many others are dedicated to a better understanding of this classic developmental factor.

Curves are a more complex set of possible relationships that emerge in forecasting. Once we have some data relating two or more variables over time, we can ask if that relationship fits any of the classic families of curves that we find in complex systems. We discussed several of those in Chapter 6. Could it be an S-curve? A power law (performance) curve? A Kuznets curve? A Life Cycle curve? A J-curve? A U curve? Something else? If it looks like it may fit a certain type of curve, we can then ask why that might be, and how long the curve might continue to apply. The categorization of a curve can gives us some indication of its causal factors, and help us with another developmental factor, models.

Models are another classic way to conceptually constrain and predict the behavior of a system. Again, we covered a starter set of important models in Chapter 6. We also introduced a few universal models, including exponential foresight (Chapter 7) and evo devo foresight (this chapter), and some related submodels. All models are incomplete and wrong in part, but the better ones uncover causal variables and relationships that help us better understand and simulate the system in question.

Futurist’s Pierre Wack’s predictable dominant tendencies(“tendances lourdes”, in French), are models that trying to be candidates for forces, constraints, or laws that affect classes of complex systems. Just as there are laws of physics, chemistry, and biology, we know there are laws, or at least, statistically dominant tendencies, of societies, economies, technologies. But until they are accepted by the scientific community as laws, they are just models.

Well-characterized and widely-accepted systems laws, persistent relationships, rules, or laws that apply to classes of complex systems, are particularly rare. Systems theory is that branch of philosophy, which we have tried to practice in this chapter, that studies systems in general, and looks for common patterns and principles that apply to all systems of a particular class or type. Many laws can be guessed at for any system, with varying levels of evidence. It’s always worth investigating the systems literature for these, and asking how they relate to systems laws that have been recognized, for the universe as a system.

Many of our scientific laws of physics, and a few of chemistry and biology can be derived from the known forces, but most of our laws are empirically (experimentally) observed. As we climb further up the systems hierarchy to human society and economy, and later to self-improving technology, we generally ignore forces, and talk instead of systems laws that act in broad ways across the system as a whole. The higher we go up the hierarchy, the less these laws are theoretically derived, and the more they are experimentally observed. Our scientific and practical knowledge becomes less deductive and mathematically precise, and more inductive and descriptive. Yet the more developmental relationships we can uncover, the more prescriptive our science can become.

Besides physics and chemistry, all other academic disciplines, like ecology (“Cope’s rule”, “Bergmann’s rule,” “Foster’s rule”), sociology (“law of least effort” and “law of time-minimization”), economics (“law of supply and demand”), statistics (“law of large numbers”, “regression to the mean”), and many others have collected their own starter lists of apparent laws. A good systems thinker will try to understand as many of these as possible, and to study examples of how they interact, to understand the “dominant tendencies” one might expect to constrain the nature and future of any system, in any environment. This kind of foresight can be incredibly powerful, as it has such generality of application, but it is today more art than science.

We have argued that the growth of adaptive collective complexity, computation, or intelligence in the universe, using both evolutionary and developmental processes, is at least a fundamental “dominant tendency” or rule of our local environment, and is likely a universal law. I look forward to seeing this hypothesis better critiqued and tested in coming years. The evo devo universe model may or may not eventually produce a series of widely accepted laws. I am hopeful that it will. But even if it does not, that doesn’t mean that there are not universal (or if you like, cosmological) systems laws out there, waiting patiently for futurists to understand. Systems theorists believe that the better we understand laws in any complex system, the better we can appreciate them in the universe as a system.

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Chapter 3. Career Options – Great Ways to Be a Foresight Leader

## Chapter 3: Career Options Great Ways to Be a Foresight Leader

Chapter 4. Models – Foundations for Organizational Foresight
Chapter 5. The Do Loop – The Eight Skills of Adaptive Foresight
Chapter 6. Methods and Frameworks – Building Adaptive Foresight Skills

## Chapter 6: Methods and Frameworks Building Adaptive Foresight Skills

Chapter 7. Acceleration – Guiding Our Extraordinary Future

## Chapter 7: Acceleration Guiding Our Extraordinary Future (In Process)

II. Global Progress: 5 Goals, 10 Values, Many Trends

Innovation: Our Abundant Future
Intelligence: Our Augmented Future
Interdependence: Our Civil Future
Immunity: Our Protected Future
Sustainability: Our Rebalanced Future

III. Universal Accelerating Change

Great Race to Inner Space: Our Surprising Future
Entropy&Information: We’re Running Down & Up
The Puzzle of Meaning: We Have No Einstein Yet
Trees, Funnels & Landscapes: Intro to Evo Devo
Big Picture Change: Five Scales of Accelerating ED
Transcension Hypothesis: Where Acceleratn Ends?
IDABDAK: Social Response to Accel & Developmnt
We’re On a Runaway Train: Being Accelaware

IV. Evo Devo and Exponential Foresight

Seeing It All: Accel., Diverg, Adapt, Convrg, Decel.
Natural (I4S) Innovation: The Evolutionary Drive
Natural (I4S) Intelligence: The Human-AI Partnership
Natural (I4S) Morality: Why Empathy and Ethics Rule
Natural (I4S) Security: Strength from Disruption
Natural (I4S) Sustainability: The Developmental Drive
S-Curves: Managing the Four Constituencies
Pain to Gain: Traversing the Three Kuznets Phases
Hype to Reality: Beyond Hype Cycles to Reality Checks
Exponentials Database: Measuring Accelerations
TINA Trends: Societal Evolutionary Development
Managing Change: STEEPCOP Events, Probs, Ideas
A Great Shift: A Survival to a Sentient Economy

V. Evo Devo and Exponential Activism

Building Protopias: Five Goals of Social Progress
Normative Foresight: Ten Values of Society
Top & STEEPCOP Acceleratns: Positive & Negative
Dystopias, Risks, and Failure States
Three Levels of Activism: People, Tech & Universe
A Great Opportunity: Exponential Empowerment

Chapter 8. Your Digital Self – The Human Face of the Coming Singularity

## Chapter 8: Your Digital Self The Human Face of the Coming Singularity (In Process)

Digital Society: Data, Mediation, and Agents
Personal AIs: Advancing the Five Goals
PAI Innovation: Abundance and Diversity
PAI Intelligence: Bio-Inspired AI
PAI Morality: Selection and Groupnets
PAI Security: Safe Learning Agents
PAI Sustainability: Science and Balance
The Human Face of the Coming Singularity

II. PAI Protopias & Dystopias in 8 Domains

1. Personal Agents: News, Ent., Education
2. Social Agents: Relat. and Social Justice
3. Political Agents :  Activism & Represent.
4. Economic Agents:  Retail, Finance, Entrep
5. Builder Agents :  Work, Innov. & Science
6. Environ. Agents : Pop. and Sustainability
7. Health Agents :  Health, Wellness, Death
8. Security Agents :  Def., Crime, Corrections

III. PAI Activism & Exponential Empowerment

Next Government: PAIs, Groupnets, Democ.
Next Economy: Creat. Destr. & Basic Income
What Will Your PAI Contribution Be?

Chapter 10. Startup Ideas – Great Product & Service Challenges for Entrepreneurs

## Chapter 10: Startup Ideas Great Product and Service Challenges for Entrepreneurs (In Process)

Air Deliveries and Air Taxis: Finally Solving Urban Gridlock
Ballistic Shields and Gun Control: Protecting Us All from Lone Shooters
Bioinspiration Wiki: Biomimetics and Bio-Inspired Design
Brain Preservation Services: Memory and Mortality Redefined
Competition in Govt Services: Less Corruption, More Innovation
Computer Adaptive Education (CAE): Better Learning and Training
Conversational Deep Learning Devsuites: Millions of AI Coders
Digital Tables: Telepresence, Games, Entertainment & Education
Dynaships: Sustainable Low-Speed Cargo Shipping
Electromagnetic Suspension: Nausea-Free Working & Reading in Cars
Epigenetic Health Tests: Cellular Aging, Bad Diet, Body Abuse Feedback
Fireline Explosives and Ember Drones: Next-Gen Fire Control
Global English: Empowering the Next Generation of Global Youth
Greenbots: Drone Seeders and Robotic Waterers for Mass Regreening
High-Density Housing and Zoning: Making Our Cities Affordable Again
Highway Enclosures and Trail Networks: Green and Quiet Urban Space
Inflatable Packaging: Faster and Greener Shipping and Returns
Internet of Families: Connecting People Over Things
Kidcams: Next-Gen Security for Child Safety and Empowerment
Kidpods: Indoor & Outdoor Parent-Assistive Toyboxes
Microdesalination: Democratizing Sustainable Fresh Water Production
Noise Monitors: Documenting and Reducing Noise Pollution
Oceanside Baths: Sustainable Year Round Beach Enjoyment
Open Blood Scanners: DIY Citizen Health Care Sensor Tech
Open Streaming Radio: User-Centered Audio Creation and Rating
Open Streaming Video: User-Centered Video Creation and Rating
Open Values Filters: Social Rankers, Arg. Mappers, and Consensus Finders
Pet Empowerment: Next-Gen Rights and Abilities for Our Domestic Animals
Safe Closets: Fire-, Earthquake-, and Intruder-Proof Retreat Spaces
Safe Cars: Reducing Our Insane 1.3M Annual Auto Deaths Today
Safe Motorcycles: Lane Splitting in Gridlock Without Risk of Death
Shared Value Insurance: User-Centered Risk Reduction Services
Sleeperbuses and Microhotels: Demonetized Intercity Travel
Space-Based Solar Power: Stratellite Powering and Weather Management
Stratellites: Next-Gen Urban Broadband, Transparency, and Security
Touch DNA: Next-Gen Home Security and Crime Deterrence
View Towers: Improving Urban Walkability, Inspiration, and Community

Appendix 1. Peer Advice – Building a Successful Foresight Practice

## Appendix 1: Peer Advice Building a Successful Foresight Practice

Appendix 2. Leaders – Exemplary Foresight Practitioners and Organizations
Appendix 3. Resources – Media and Tools for Better Futures