Bilateral Asymmetric Consilience and Networked Leadership

^(Million-dollar academic jargon right there, isn’t it?)

Much of the labor that is done in today’s digital economy is intellectual.  Economists point to intellectual capital, psychologists promote emotional intelligence, and management gurus flaunt terms like knowledge management and organizational learning (though, apparently not as much as they used to).  Certainly, work is still done and “stuff” is still produced, but technology, networked thinking, and machine learning are perpetually encroaching on the realm of work and labor.  This shift to acknowledging  “intellect as the key productive [economic] force” (Brennan, 2009) brings with it myriad questions about gaining knowledge, making sense of information, and gaining expert or referential power (Johnson, 2005) among workgroups and social networks.

Weinberger (2011) – in a nod to Marshall McLuhan via his profile of Jay Rosen’s long form/web form blog – proposed that the network itself is responsible for the emergence of new knowledge and new ways of thinking.  Just as literacy re-oriented humanity’s working memory and cognitive capacity, so too has the proliferation of the “ecology of temptation” (p. 117).  The net is limitless.  It has no edges.  Lines between experts and laypeople have been almost completely erased as content becomes more and more democratized.  We are forever bombarded by links to one more resource and it becomes difficult to determine where to stop (and sufficiently trust the information we’ve discovered).  This presents a challenge for workers, teams, and leaders, as we struggle to “filter forward” (p. 11) the information we need to do our jobs.

Danny Kahneman and Amos Tversky developed many ideas about the ways in which we take mental shortcuts in order to make sense of the information that overwhelms us on a regular basis.  The gaps in what we know about a given situation or problem are filled in by our brains by way of “heuristics and biases” (Tversky & Kahneman, 1974).  For example, we use “representativeness” (p. 1124) to make a judgement based on how well we believe something fits an existing category of things that we already know about.  We use what we (think we) know to make cognitive leaps, but these leaps aren’t always correct.  Uncertainty is amplified in the networked ecosystem, and, as we have in physical space, we must learn to deal with that missing information and figure out ways to find “stopping points” (Weinberger, 2011) and trusted information sources.

The new digital heuristic model is complicated by the fact that so much of our knowledge generation is social.  If, as media ecologists like Weinberger and Rosen suggest, knowledge is moving from paper and our heads to “the cloud,” our ability to make sense of complex information now relies heavily on what others know and what we know about others.  In an effort to shed some philosophical light on the topic, philosopher Steven Turner (2012) explores the notion of “double heuristics” and “social epistemology.” Turner suggests that “that individuals, each with their own heuristics, each with cognitive biases and limitations, are aggregated by a decision procedure, like voting, and this second order procedure produces its own heuristic, with its own cognitive biases and limitations” (p. 1). In this way, learning and sensemaking are inherently social; epistemology that’s ideally situated for the networked digital ecosystem.

Turner (2012) uses Michael Polanyi’s example of a group assembling a puzzle to demonstrate the collective heuristic. The optimal method of solving the puzzle (i.e., gaining new knowledge) would be a system in which “each helper will act on his own initiative, by responding to the latest achievements of the others, and the completion of their joint task will be greatly accelerated” (Polanyi, 1962).  This requires social interaction, but Turner (2012) argued that the true nature of knowledge here still comes form the individual.  There’s one piece that fits and only fits those adjacent to it, and that is the individuals’ contribution.  In contrast, he proposed the notion of “bilateral asymmetric consilience” (p. 11) as a means of generating knowledge that can only spring forth from the interaction of two knowing entities.  The example he uses is that of a doctor and patient.  Both have knowledge (bilateral) of the presenting symptoms, but in different ways (asymmetry).  Only when patient and doctor collaborate on identifying the disease does the answer emerge (consilience).  The doctor knows the frameworks in which such symptoms might exist (“expertise”), but the patient knows which are present for him.  Together, their interaction has produced and verified knowledge about the patient that could not have previously existed independently.

In his theory of Wirearchy, Husband (n.d.) stressed the importance of social interactions (networked) as a means of developing social norms and specifically power.  He asserted that “command-and-control” (para 4) hierarchy is losing ground to the more effective methods of “champion-and-channel” (para 5) leadership.  This echoes Turner’s (2012) discussion of planned science and the idea of top-down, individually biased leadership decision-making.  The command-and-control model leads to information bottlenecks that are not needed in organizations with evolved social-epistemology systems.  I believe that in such environments, a leader can assist in the development and distribution of heuristic learning.  We can develop systems in which “bilateral asymmetric consilience” might occur; generating knowledge (or hopefully wisdom) that no leader, no matter how specialized, could have ever predicted or planned for.  Experience and expertise will continue to hold value, I believe, but will shift to become tools in the facilitation of collective learning.



Brennan, T (2009). Intellectual labor. South Atlantic Quarterly, 108(2), 395-415.

Husband, J. (n.d.) What is wierarchy? Wirearchy [website].  Retrieved from

Johnson, C. E. (2005). Meeting the ethical challenges of leadership: Casting light or shadow. (5th ed.). Thousand Oaks, CA: Sage.

Polanyi, M. (1962). The republic of science.  Minerva, 38(1), 54–73

Turner, S. (2012). Double heuristics and collective knowledge: the case of expertise. Studies in Emergent Order, 5, 64-85

Tversky, A., and Kahneman, D. (1974). Judgement under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.

Weinberger, D. (2011). Too big to know: Rethinking knowledge now that the facts aren’t the facts, experts are everywhere, and the smartest person in the room is the room. New York: Basic Books

10 thoughts on “Bilateral Asymmetric Consilience and Networked Leadership

  1. James
    You capture a core concept with which we are all dealing when you mention the difficulty of determining where to stop or which content to trust. Great job illuminating our proclivity for filling in the gaps using our conscious and unconscious preconceptions and mental models. You note that uncertainty is amplified yet it seems that while some of us more scholarly types quest for substantiating facts and well researched support to determine truth, many others fill in the gap with whatever fact is stated loudest or is posed in the flashiest lights. Your closing thoughts highlight the role of experience and expertise in being tools to facilitate networked learning. Although possibly being your intent, I would propose that experience and expertise can also play that key role in parsing out the truth from the offense of alternate truth. In this aspect it seems they play more than the role of a tool. Those possessing experience and expertise seem to be a last bastion of reason. In tongue in cheek contrast to your academic title I offer the following “cartoon” on heuristics

    And what a great job crafting your supporting example for bilateral asymmetric consilence. I was taken by the reference to Polyani’s puzzle metaphor in discussing that a key reason why the collective is quicker to solve the problem is due to the fact that all group members are aware of the action each member is taking and if they were not aware then the group would not likely be any more efficient than the individual. Written well before today’s network, I think it’s fascinating to consider how it applies to the leader’s role today as one who needs to not only enable the connection but also ensure it is transparent and that everyone is fully engaged and tuning into what one another are doing. Intriguing article – thanks for sharing. ~Tricia

    1. Good morning, Tricia – thank you for your comments.
      That’s a great cartoon… highly informative, but clear and easy to understand. I’ve been fascinated with that topic of late, as I’m working my way through “The Undoing Project” by Michael Lewis, the author of “Moneyball.” It is truly astounding how many errors we make because of the shortcuts we take. The ramifications of the heuristics we most often use can be profound, especially now that most of us aren’t responding to threats of wild animals or foraging for food. I wonder if we will “grow out of” this behavior or if it will simply adapt to the digital ecosystem.

      I unfortunately agree with your point about some individuals allowing the gaps to be filled in for them. In your video clip, we encounter the game show dilemma… and I think that’s a great example of carefully planned influence being exerted over a vulnerable individual in a position to make a very big choice. They also raise the marketing and negotiation example, which is another carefully planned and executed manipulation of these heuristics.

      There could be a very powerful temptation for leaders to take advantage of such tactics. I hope that we can continue promoting the positive sides of collective knowledge and learning rather than exposing the nefarious.

      1. James,
        Glad you enjoyed the cartoon – your wonderfully intellectual approach brought out the trickster in me 🙂 I appreciate your emphasis on the importance of leaders looking to promote collective knowledge in a healthy, community enhancing way. I am currently a bit more worried than I would have been a year ago about manipulation of the vulnerable. I too will hope for the best. ~Tricia

  2. Definitely jargon, but not sure of the price! I might toss in a word developed by one of my old colleagues, Bill Pelz – Technoheutagogy: The science and art of creating technology-enhanced learner-directed learning environments.

    In both your cases, people are making decisions based on disparate information. Bill points to how online, self-directed learners can enhance their learning through technology.

    I see similar threads in leaders weaving disparate “knowledge” together in a wirearchy-type environment.

    1. Thanks for sharing this resource, Dr. Watwood! I’m excited to learn more about technoheutagogy. Here’s the link for others who might be interested as well:

      Dealing with disparate information, I think, is the key to leading in the digital space. Pulling together those suites of tools, knowledge management, and developing social business processes will open up those connections and allow for better learning.

  3. James,

    Fantastic post, and an award-winning title! I spent some time browsing the Tversky and Kahneman (1974) article, and appreciated their excellent explanation of mental shortcuts. The authors pointed out that most people cannot do math in their heads, especially probability. Unfortunately, even with readily available tools, only 1% of US bachelor’s degrees conferred are in math ( Math skills are becoming essential to a world of big data, statistics, and data visualization, to mention a few. Topping U.S. News & World Report’s list of best STEM jobs for 2017 is statistician, with mathematician close behind at number four ( Glassdoor’s discussion of work trends for 2017 highlights the growing competition for workers with quantitative skills, and data scientist holds Glassdoor’s number one “best job” spot ( My department is creating a mathematics degree, and I have my fingers crossed that there will be sufficient enrollments to support the program. My hope is that interest math knowledge will grow as the new digital heuristic model continues to be…well, digital.



    Tversky, A., and Kahneman, D. (1974). Judgement under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.

    1. CatOnKB – this is really eye-opening information!
      I certainly fall into the category of people who cannot do math in their heads 🙂
      I very much agree with you about the importance of developing math interest, enthusiasm, and proficiency. I hope that your department’s project goes well and that you can build a good program!

      I think there’s a lot to be said and done about the area of logic and creative thinking in math and science. How has that played into the design of the math program you’re working on? Something that jumps out to me about Tversky & Kahneman’s work is how much we don’t even know that we’re supposed to be thinking about… that even if the math makes sense, we’re still missing a whole chunk of the information or the background of the situation. I don’t think I’m being very clear on this, but I guess I’m trying to suggest that we need to be able to assess the situation in a way and THEN apply the correct analytical tools. Asking the right questions vs. getting the right answer?

      Thanks for jumping in on this – it’s a slant I will continue to mull over this weekend.

      1. James,

        Great insight about the need for math educators to assess the very framework of mathematics, and what it means to students as practitioners. In the paper “Learning to Think Mathematically: Problem Solving, Metacognition, and Sense-Making in Mathematics” (, Berkeley Professor Alan Schoenfeld shares this thought:

        “At one end of the spectrum, mathematical knowledge is seen as a body of facts and procedures dealing with quantities, magnitudes, and forms, and relationships among them; knowing mathematics is seen as having ‘mastered’ these facts and procedures. At the other end of the spectrum, mathematics is conceptualized as the ‘science of patterns,’ an (almost) empirical discipline closely akin to the sciences in its emphasis on pattern-seeking on the basis of empirical evidence…The author’s view is that the former perspective trivializes mathematics, that a curriculum based on mastering a corpus of mathematical facts and procedures is severely impoverished—in much the same way that an English curriculum would be considered impoverished if it focused largely, if not exclusively, on issues of grammar.” (p. 3)

        Schoenfeld makes a case that mathematics is an inherently social activity of engaging in a science of patterns. Unfortunately, many programs are designed with former perspective in mind. Thank you for a timely reminder that this is the perfect opportunity to create an exciting, dynamic, program that is so much more than numbers!


  4. Hi James,

    Great post! As I read it, I kept thinking about one word over and over again… trust. As you wrote, our individual limitations to knowledge and problem solving are obvious. We are influenced by any number of factors in our own understanding of a topic or issue. The social aspect is obvious, but also our backgrounds, our education, etc. The list goes on and on.

    Husband’s concept of wirearchy seems to rely on the concept of trust heavily. To allow the pieces of the puzzle to be filled in by others, we must let go of the idea that we can answer the question (whatever that question may be) solely by conducting our own research or relying on our education and understanding. We must recognize our biases and rely on others with different and diverse perspectives to hep solve the puzzles.

    The example you gave of the doctor and patient represents an area where it may be easy to rely on that outside knowledge. We recognize that our doctor is knowledgeable, educated, and experienced on the topic of our health. We can rely on that experienced individual to provide the correct information to answer our questions and fill in the puzzle pieces. However, how do we react when there is more uncertainty about the validity of the information we find or that is shared with us? If the individual or source providing that information is less known to us, what is our reaction? Do we fall back into a heuristic method of data collection and decision-making? Or, do we trust the uncertainty of gathering knowledge and information from others. I think that will be a pretty constant struggle for many, and particularly for those in leadership positions.

    I’d love to hear your thoughts on the issue.

    The Ayes Have It

    1. Thanks for the kind words… and the great questions.
      One thing that Turner (2012) talked about in the collective heuristic model is the notion of adjacency; the idea that we trust information because it has been filtered through a network of others who are reasonably close enough to validate it. “We thus have a considerable degree of overlapping between the areas over which a scientist can exercise a sound, critical judgment. And, of course, each scientist who is a member of a group of overlapping competences will also be a member of other groups of the same kind, so that the whole of science will be covered by chains and networks of overlapping neighbourhoods” (p. 9).

      To your point, this adjacency heuristic is great in a tightly controlled network like the scientific community, but becomes less so in a loose organizational (or public) network. I’m a believer in the power of the mob to facilitate the rise of the good information and the filtering out/back of the bad. That is, the power of democratic action and judgement. However, it’s also the reason that one of the most popular, democratically approved-of Reddit threads is a user’s collection of photos featuring all of the plumber’s butts he found at Comic Con. Yup.

      In that case, I think that Weinberger is spot on with the sentiment that the network itself is then the smartest thing in the network. BY evaluating the network we find ourselves operating in, we can determine how to proceed. Reddit is composed of a very particular subset of the internet population, and what that community finds “important” may not be representative of the larger sentiment.

      Great question, thanks!

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