First citizen of the information age

“The empires of the future are empires of the mind.”
– Winston Churchill [1]

By Kenneth O. Jobson, Dean Hartley and Steve Martin

Mother Nature at her core is not about moving atoms around with energy but about information. Mother Nature is the first citizen of the information age. Information is nature’s coin of the realm.

Revolutionary: understanding how biologic complex adaptive systems gather, compute, store and communicate information.

In parallel with the current transformative revolutions in information processing and communication, as the world becomes flat [2] there is another revolution, a Kuhnian paradigm shift [3] at the dawn of the 21st century much as physics underwent in the beginning of the 20th century when quantum mechanics was added to Newtonian physics. That revolution is in our understanding of how biologic complex adaptive systems (CAS) gather, compute, store and communicate – from DNA to the human biopsychosocial levels – and in our use of this knowledge.

The most striking innovations often come from transdisciplinary mixing, and “domain recombinations” [4], that is, combining knowledge and structure across disparate domains [5]. The new tripartite macro states created by the rise of technology to levels of influence comparable to nature and society are comprehended best by including insight into the ecology of the most sophisticated complex adaptive systems seen in Mother Nature and how she deals with the corporate, societal and the technologic.

Evolution can be seen as a search strategy to gather and use information. Its methods involve aligning incentive and optimizing the mixture of cooperation and competition. Central orchestration is balanced with substantial distributed decision-making with various types of intelligence. Evolution has methods of pruning and disgorging the spent and obsolete up and down the scale from DNA to the psychosocial.

The current biologic systems are the ones that have faced dilemmas, paradigm shifts, Gaussian and Mandelbrotian variance [6] and survived. Biologic systems routinely process immense quantities of data via multiple sensors, store information with suitable features of arrangement and flexibility, engage in bouts of random foraging, and balance substantial operational sub-unit operational freedom with hierarchical analytics and orchestration to survive, grow and, with need, transform at amazing speed. Nature’s complex adaptive systems evince self-organizational behaviors, capacity for contagion, and emergence across scales of time and social size. There is a deep commonality between these fundamental biologic systems and human group learning, influence and innovation whether charitable organizations, commerce, mass interpersonal persuasion (MIP) [7] or war.

The emergent genius of biologic systems connects primary, secondary and tertiary processing of information. Claude Shannon, the father of information theory, said, “Technical accuracy and semantic precision do not equate with effectiveness” [8]. Recent advances in understanding human biopsychosocial communication can be deployed to improve the effectiveness of communication. This development is salient from the conversation between two people to the massive scalable influence of social media nested in the digital cloud in the global commons (see Figure 1).

Figure 1: Shannon’s Loop is adapted from the diagram to illustrate bidirectional communication with processing by both original source and original destination. *Shannon, C. et al., “The Mathematical Theory of Communication,” The Bell System Technical Journal, July and October 1948.

Biologic systems have demonstrated iteratively inductive discovery [9] and creative emergence of new systems. New, successful systems form again and again and have prospered in a VUCA world (volatility, uncertainty, complexity and ambiguity; sometimes referred to as “VUCAA,” with the last “A” for accelerating) [10].

An adequate mass of functionality of knowledge from biologic systems now exists to inform corporate management, provide material for innovation and leadership training and foster transdisciplinary learning. This paper collects recent and salient discoveries, facts and aphorisms to assist by analogy and other cognitive “artifactual” methods in the service of commerce be it cooperative, competitive or both.

Four Exemplars

Exemplar A. Microstates: temporary confluences that inform

Microstates abound up and down the scale from the molecular to the global commons, but the brain’s use of microstates is particularly illustrative (Figure 2). Using functional imaging, one can see the brain approach a problem; it arrays temporary connections (microstates) across its semi-modular structure. Each array is unique to the problem and may, with its multiple channels of communication, construct and connect to external microstates.

Figure 2: Microstates are temporary confluences that inform. They abound in nature, up and down the scale, and are central in all complex adaptive systems.

When an important issue arises, the brain does not look at a chart and assign the issue a specific physical location. It pulls together microstates of all relevant and useful experiences, relationships, ideas, concepts, etc., and then begins to parse through them for relevancy to the issue at hand, urgency, threat level, etc. This assembled microstate with its distributed decision-making begins to assess and decide. The process is repeated untold times creating different microstates based on the nature of the matter to be dealt with. Success requires that the subunits be “smart,” appropriately chosen and often locally initiated, that the communication be effective, and that information sharing is established. These microstates are contextualized in higher order analytics. The question is, “Where do the talents both internal and external reside, and how do they come together to address this issue?” The clear understanding is that, once that is done, for each unique microstate the information is shared, and that microstate is dissolved and others created.

The implication here is obvious but dramatic: Do not automatically rely on the organization chart for serious purpose of innovation or when facing novel dilemmas. In a world where organizations get addicted to fixed patterns of information flow, structure and business processes, sometimes it is not the big that eats the small but the insightful, creative and flexible that eats the fixed or rigid.

Exemplar B. Innovation Supremacy: Earth’s supreme innovator

These examples are from Mother Nature’s innovative toolbox of modern “information business” concepts:

1. Massive connectionist systems: The connections between subunits are multiple and multi-modal. For instance, the average neuron in the neocortex is connected to 20,000 other neurons.
2. “Collectiveness,” i.e. fostering group efforts with sufficient alignment of interest, for example: for the mutual benefit of humans and their microbe fellow travelers there are more organisms living in us and on us than the number of our own human cells, if we count the bacteria and virus and fungi load.
3. Failure tolerance: natural systems iteratively foster massive numbers of trials with environmental feedback.
4. Focus on the “trans” of transdomain: creating multiple insights in multiple venues toward envisioning the possibility of new combinations. This allows nature to discover what Stuart Kauffman describes as the “adjacent possible” in evolution, to wit, new discovery and innovation [9].
5. Mixing youth with experience: all ecosystems.
6. Mixing semi-random foraging with algorithmic rule-based systems: standard in biologic social systems.
7. Microstates abound within and are often connected to entities outside of the organisms.
8. Mixing the genetic, the epigenetic and the environmental influences (genetic – substantially fixed information; epigenetic system – that is foundationally genetic but altered by the environment): standard biologic systems approach.
9. Reticulists: entities that foster connections and collaborations abound.
10. Aggregators: entities that add information and knowledge to the connected entities.
11. Incentive alignment: fosters cooperation among subunits some of which outside entities.
12. Conflict modifiers: present to prevent dissociative and maladaptive communications.
13. Sufficient subset operational freedom with local decision-making: fosters learning and subunit decision-making. These subunits pass the new learning up the executive structure. These smart subunits contribute to smart, larger groups. In 2009, it was published at the Santa Fe Institute that a smart group, i.e., one that brings emergent new learning and adds value of more than the sum of the members, has to have the proper mix of the independent and the interdependent [11]. This is also consonant with what was published in Science 2010 (Journal of American Academy of Science), that collective emergent intelligence “C” is influenced by both general intelligence “G” of each member and by the capacity to take turns and communicate well among members without dominance by more senior or assertive members [12]. Human cells continue to “learn” throughout their lives.
14. Systems to eliminate the non-productive and the spent, up and down the scale.
15. More information is transferred up the neurologic hierarchical axis than down.

Figure 3: Divisions of knowledge and its transfer. Source: Polanyi, M., “The Tacit Dimension,” University of Chicago Press, 2009 edition.

Exemplar C. Context Dependent

All biologic signals are context dependent, and we do not perceive or respond to the full complexity of the environment. No skill is as important in the current world of business than the capacity to know the context of human decision-making from the stunningly creative to the irrational or hubristic. First, the incoming signal may be limited by the problems inherent in conveying implicit and tacit knowledge. Second, there may be mitigation by the sender. Third, multiple channels of social signals are present and important, despite the seeming supremacy of speech.

The brain is more a pattern recognition device than a calculator. The brain has many biases [13] that have evolved for primitive survival and procreation. These biases are not ideally suited for the modern VUCAA world. We often use frugal installed heuristics instead of exhaustive search. Our biologic biases are many, e.g. our prejudice toward pattern completion. We categorize, simplify or narrate. After all a good story may aid alliance building or bring wisdom. It may also be simplistic or irrational. We reflexively compare things around us in relationship to others. Our initial opinion and our expectations bias us automatically. The pull and tug of the familiar, of what we already have or “know,” is a frequent default position. Variance in human temperament is great. We look out from our idiosyncratic position along a temperament continuum of comfort with or aversion to conflict; we seek novelty or are more averse to novelty. From our human perspective, we have difficulty knowing where we are in the Johari Window [14] (Figure 4).

Figure 4: The Johari Window provides an interesting perspective on human awareness and communication. Source: Luft, J. et al., “The Johari Window: A Graphical Model of Interpersonal Awareness,” proceedings of the Western Training Laboratory of Group Development, San Francisco, 1955.

Exemplar D. Human Communication

• We say more than we know (executive over-reach, hubris or ignorance).

• We know more than we say (the problem conveying tacit knowledge (Figure 3) and/or of mitigated speech).

• We often do not know that we do not know (agnosagnosia), and we do not know what we do not know. In other words, we do not know where we are in the Johari Window [14] (Figure 4).

• Biologic human speech is accompanied by at least two channels of social signals: prosody (pitch, tempo, pausing, emphasis, rhythm injected into speech) and what are being called “honest signals” at MIT Media Lab. Honest signals [15] are iterative social signals: i.e. speaker behavior such as changes in the amplitude and frequency of prosodic and gestural activities [15]. These social signals frame our words, giving salient information and dramatic influence on affiliative or dissociative responses of others, and on prioritizing and contextualizing. When speaking or writing, language-style matching conveys how much attention each pays to what the other says [16].

• Human’s use of narration (storytelling) has great potential for influence, by conveying wisdom or by reinforcing the brain’s biases, including pattern completion.

• Each of us has somewhat different vocabularies, privacies of reference and one might say different idiolects [17]. The amazing thing is not that we miscommunicate using human speech (only developed in the past 50,000-100,000 years), but that we can communicate at all [17].
Mother Nature is yielding her secrets. The use of this knowledge furnishes the “adjacent possible” for trans-domain mixing to create and innovate for great advantage.

Kenneth O. Jobson, M.D. (kojobson@usit.net), clinical psychiatry and psychopharmacology, Knoxville, Tenn., is chairman of the board of the International Psychopharmacology Algorithm Project (www.IPAP.org) and a member of the clinical faculty at the University of Tennessee at Memphis.

Dean Hartley (DSHartley3@comcast.net) is principal, Hartley Consulting, which provides operations research support to military, medical and commercial organizations.

Steve A. Martin, Ph.D. is president of Martin-Frankel Associates, management consultants headquartered in Winston Salem, N.C. Martin focuses on strategy, teamwork and executive coaching.

References

1. Churchill, W., speech at Harvard University, Sept. 6, 1943.
2. Friedman, T., “The World is Flat,” release 3.0, Picador/Farror, Straus and Giroux, New York, 2007.
3. Kuhn, T., “The Structure of Scientific Revolutions,” University of Chicago Press, 1962.
4. Alberts, B., “The Art of Translation,” Science, Vol. 326, p. 2,005, Oct. 9, 2009.
5. Apic, G., et al., “Domain Recommunication: A Workhorse for Evolutionary Innovation,” Science Signaling, Vol. 3, Issues, pp. 138-141, Sept. 2010.
6. Taleb, N., “The Black Swan: The Impact Of The Highly Improbable,” Random House Publishing, New York, 2007.
7. Fogg, B.J., “Mass Interpersonal Persuasion: An Early View of a Phenomenon,” Persuasion Lab, Stanford University, delivered at the Persuasive Technology Conference, 2009.
8. Shannon, C., et al., “The Mathematical Theory of Communication,” The Bell System Technical Journal, July and October 1948.
9. Johnson, S., “Where Good Ideas Come From: The Natural History of Innovation,” Riverhead Books, New York, 2010 (the ideas of Stuart Kauffman).
10. Johanson, B. (of the Institute for the Future), “Get There Early: Using Foresight to Provoke Strategy and Innovation,” Berrett-Koehler Publishers, San Francisco, 2007.
11. Steeley, T.D., Santa Fe Institute Bulletin, “Building Smart Groups,” 2009.
12. Woolley, A.W., “Evidence for a Collective Intelligence: Factor in the Performance of Human Groups,” Science, Vol. 330, No. 6,004, pp. 686-688 Oct. 2010.
13. Ariely, D., “Predictably Irrational: The Hidden Forces That Shape Our Decisions,” (revised and expanded edition), Harper Collins Publishers, 2009.
14. Luft, J., et al., “The Johari Window: A Graphic Model of Interpersonal Awareness,” Proceedings of the Western Training Laboratory of Group Development, San Francisco, 1955.
15. Pentland, A., “Honest Signals: How They Shape Our World,” MIT Press, 2008.
16. Pennebaker, J, et al., “Journal of Personality and Social Psychology,” Vol. 99, No. 3, pp. 549 -571, 2010.
17. Steiner, G., “Errata,” Yale University Press, 1997.
18. Nowak, M A., “Five Rules for the Evolution of Cooperation,” Science, Vol. 314, No. 5,805, pp. 1,560-1,563, Dec. 8, 2006.
19. Polanyi, M., “The Tacit Dimension,” University of Chicago Press, 2009 edition.