The Case Against Entrepreneurship As We Know It
Entrepreneurship is typically regarded as an individualistic activity that takes place in a free-market economy, usually in the context of for-profit businesses. This is an evolutionary worldview, although it is not always stated as such. Innovations are the cultural analogs of genetic mutations. Economic competition is analogous to ecological competition in the biological world. And the survival of the fittest company is assumed to benefit society as a whole.
Thinking about entrepreneurship as an evolutionary process isn’t wrong. In fact, the more we learn about cultural change of all sorts, the more it can be seen as both a product of genetic evolution and a fast-paced evolutionary process in its own right.1-3 However, a modern understanding of human cultural evolution reveals the conventional laissez-faire view of entrepreneurship as too simple. In the first place, the role of the individual entrepreneur is exaggerated.4 Just as it takes a village to raise a child, it takes a lot of cooperation to create and develop new solutions to life’s problems. In the second place, the role of free markets is exaggerated. What sells over the short term is not necessarily the same as what will benefit society as a whole. If this wasn’t clear before the coronavirus pandemic, it should be clear to everyone now.
If laissez-faire is a faulty model of entrepreneurship, what about its main alternative, centralized planning? This too is a faulty model because human social systems are too complex to be understood by a group of experts who are charged with formulating and implementing a grand plan. This is true even for a moderately sized corporation, where top-down change efforts are more likely to fail than to succeed, not to speak of a national or global economy.5
Is there a “Third Way” for entrepreneurship, which differs from both laissez-faire and centralized planning? The use of the term “Third Way” to define a new course of action, often (but not always) a middle course between socialism and capitalism, has a venerable history stretching back at least to Pope Pius XII in the late 19th century. Its use by the Tony Blair administration in the U.K. and the Bill Clinton administration in the USA during the 1990s is only the most recent chapter. I’m using the term in the same spirit while drawing on a new source of knowledge for solutions: not political or economic theory, but a combination of evolutionary and complex systems science. The Third Way is a managed process of cultural evolution with systemic goals in mind. This requires managing all three major ingredients of an evolutionary process: selection, variation, and replication.
Why must these three ingredients be managed? Otherwise, cultural evolution will still take place but will lead to outcomes that disrupt, rather than contribute to, societal goals. Evolution, whether genetic or cultural, doesn’t make everything nice. It frequently results in behaviors that benefit me but not you, us but not them, or for the short-term but not the long-term. Work is required to align cultural evolutionary processes to achieve large-scale and long-term societal goals, so that evolution can become the solution rather than the problem.
Let’s take a closer look at what it means to manage the three ingredients of a cultural evolutionary process in the order selection, variation, and replication.
The target of selection must be a systemic goal, such as a sustainable equitable economy or preventing global pandemics.
A root assumption of laissez-faire is that the pursuit of lower-level self-interest in a free market robustly benefits the common good. Modern evolutionary theory tells us that this is profoundly not the case.1 Therefore, for entrepreneurship to benefit society as a whole, the common good must be explicitly the target of selection and the disruptive pursuit of lower-level self-interest within the society must be suppressed. This is called a major evolutionary transition for genetic evolution and it is needed equally for cultural evolution.
As a concrete example, the traffic flow of a city is not optimized by individual drivers separately optimizing their driving behavior to get where they want to go. The optimization of the whole system must be the target of selection and must be aligned with the driving behavior of individuals. If this is true for traffic flow, then it is also true for a broader goal such as a sustainable equitable economy or preventing the spread of contagious diseases.
Variation must be oriented toward the target of selection.
Continuing the traffic-flow example, individual entrepreneurs trying to carve out financially lucrative economic niches for themselves will result in variation (different startups), but not variation oriented toward the solution of the targeted problem. In this regard, self-interested entrepreneurs are no more the solution than self-interested drivers. The creative efforts of entrepreneurs must be oriented toward the problem, such as a targeted initiative. Then candidate solutions must be compared in a way that takes the performance of the whole system into account and avoids the problem of unforeseen consequences. Only then is it possible to assess which creative solutions to implement and replicate in other locations. Once again, if this is true for a concrete objective such as optimizing traffic flow, it will be equally true for a broader objective, such as a sustainable equitable economy or adapting to the coronavirus pandemic.
As another concrete example that has been studied in detail,7 suppose that the assembly-line workers of an automobile plant need to keep a number of parts within easy reach. This means that the parts need to be in relatively small bins and replenished at frequent intervals. The parts are brought to the plant in large lots, so someone has to divide them into small lots and physically transport them to the assembly line. Less effort for the assembly-line worker requires more effort for the receiving and distribution departments. What’s the best way to manage this tradeoff to maximize overall productivity? Common sense based on experience and computer simulation models might narrow the field of possibilities, but ultimately it will be necessary to implement different arrangements and monitor the consequences for the assembly plant as a whole.
Systems engineers have known this for a long time without necessarily describing it in evolutionary terms.8 You can’t optimize a complex system by separately optimizing its parts, which would be the equivalent of laissez-faire. Neither can you optimize it with a set of equations that go untested against the real world, which would be the equivalent of centralized planning. The only alternative—the Third Way of systems engineering—is to make educated guesses and select those that increase the performance of the whole system.
Whole-system optimization is what takes place in nature when individuals or groups (such as social insect colonies) are selected as whole systems. For an automobile assembly plant, the productivity of the whole operation is the target of selection, variation is oriented toward the target, and all of it must be managed. In the absence of managing the cultural evolutionary process, cultural evolution will still take place, but in ways that compromise rather than enhance the performance of the whole system.
In this example, there are no conflicts of interest in the desire to make the best trade-off decisions, and the corporation has a high degree of control over its operations. Improving productivity is merely a complex optimization problem that requires a variation-and-selection procedure to solve. What if the objective is to turn a city into an entrepreneurial ecosystem that results in high quality of life for all of its citizens in a way that is also ecologically sustainable and protected against disease? This objective is more challenging. Achieving it is likely to be opposed by lower-level interests and there is less control over all phases of the operation. Nevertheless, the challenges of evolving an efficient automobile assembly plant and the challenge of evolving an equitable and sustainable city are not different in kind. In both cases, the target of selection is a whole social system. Laissez-faire and centralized planning are likely to fail, and the only alternative is to construct variation-and-selection procedures oriented toward hitting the target of selection.
Best practices cannot be replicated in a cookie-cutter fashion.
Reproduction is such an integral part of evolution in the biological world that we tend to take it for granted. Trying to sustain and replicate a best cultural practice, however, can be a humbling experience. The world is full of programs that work well but fail to persist or spread to other locations! Even with deliberate replication attempts, whatever results in optimal traffic flow in one city, or allocation of parts in one automobile assembly plant, will almost certainly need to be tweaked to work in another city or assembly plant, based on sensitivity to context. This is equivalent to local adaptation in the genetic evolution of nonhuman species, which often takes place at very fine spatial and temporal scales. Every system needs to be continually managing its own evolutionary process.
The Third Way of entrepreneurship revealed by a modern evolutionary/complexity perspective might seem so different from laissez-faire and centralized planning as to be almost unrecognizable. But this is not quite right. If the Third Way is the only thing that can work to culturally evolve whole social systems, it is the only thing that ever has worked. In other words, if we look at examples of entrepreneurship that ended up benefitting whole social systems, we will find that the three ingredients of variation, selection, and replication were managed, even if they were not understood or described in evolutionary terms. The whole system was the target of selection for at least some of the people orchestrating the process. Unplanned variation was monitored and new experiments were planned with the target of selection in mind. And attention was paid to the replication of best practices.
My qualifier “for at least some of the people orchestrating the process” requires a bit of unpacking. A modern evolutionary view suggests that it is necessary to operate in two capacities: as designers of social systems, and as participants in the social systems that we design.9 As designers, it is necessary to have the whole system in mind as the target of selection and to socially construct the ingredients of variation, selection, and replication. As participants, we can pursue our local interests and need not have the welfare of the whole system in mind.
For example, the creation of a three-digit telephone number (311) to report minor dysfunctions arose as a cultural mutation in the city of Baltimore in the 1970s.10 The original purpose was to avoid inappropriate calls to the 911 emergency service, but soon it was realized that 311 could be used as a kind of perceptual organ to gather information about dysfunctions, which could then be processed and addressed by various agencies. Words such as “eyes,” “ears,” and “pulse” signified that the city was being conceptualized as a single organism. A lot of work was required to construct the system and correct for biases, such as different frequencies of smartphone use in various demographic categories. More work was required to replicate 311 systems in other cities. All of this effort falls under the category of functioning as the designers of whole social systems. Once a 311 system is in place, however, acting as a participant merely requires punching three digits into our smartphone to report a dysfunction, such as a pothole in our street or failed trash pickup, which is in our own interest to address.
Even though the Third Way of entrepreneurship is new as a formally articulated framework based on a combination of evolutionary and complex systems science, there is a rich trove of examples of system-level entrepreneurship in the historical record and in the present. We need to appreciate and learn from these examples at the same time that we build a formal theoretical framework for system-level entrepreneurship in the future.
David Sloan Wilson is SUNY Distinguished Professor of Biology and Anthropology at Binghamton University and an Ethical Systems Collaborator. Follow him on Twitter @David_S_Wilson.
Reprinted with permission from The Evolution Institute.
Read the Evolution Institute’s full Third Way of Entrepreneurship series.
References
1. Wilson, D. S. (2015). Does Altruism Exist? Culture, Genes, and the Welfare of Others. New Haven, CT: Yale University Press.
2. Henrich, J. (2015). The Secret of Our Success: How culture is driving human evolution, domesticating our species, and making us smarter. Princeton: Princeton University Press.
3. Wilson, D. S. (2019). This View of Life: Completing the Darwinian Revolution. New York: Pantheon/Random House.
4. Hwang, V., & Horowitt, G. (2012). The Rainforest: The Secret to Building the Next Silicon Valley. Regenwald.
5. Colander, D., & Kupers, R. (2014). Complexity and the Art of Public Policy: Solving Society’s Problems from the Bottom Up. Princeton NJ: Princeton Univesity Press.
6. Wilson, D. S., & Kirman, A. (2016). Complexity and Evolution: Toward a New Synthesis for Economics. (D. S. Wilson & A. Kirman, Eds.). Cambridge Mass.: MIT Press.
7. Rother, M. (2009). Toyota Kata: Managing people for improvement, adaptiveness, and superior results. New York: McGraw Hill.
8. Wilson, D. S. (2018). Systems Engineering as Cultural Group Selection: A Conversation with Guru Madhavan. This View of Life. https://evolution-institute.org/systems-engineering-as-cultural-group-selection-a-conversation-with-guru-madhavan/
9. Wilson, D. S., & Gowdy, J. M. (2014). Human ultrasociality and the invisible hand: foundational developments in evolutionary science alter a foundational concept in economics. Journal of Bioeconomics, 17(1), 37–52. http://doi.org/10.1007/s10818-014-9192-x
10. O’Brien, D. T. (2019). The Urban Commons: How Data and Technology Can Rebuild Our Communities. Cambridge Mass.: Harvard University Press.
