Dreams of unicorns, swans and singularity

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For twenty-five years now, technology markets have been chasing “Unicorns” and reaffirming their belief in “Black Swans.” Venture capitalist Aileen Lee coined the term Unicorn in her analysis of billion‑dollar startups, capturing what was then a small handful of companies that converted improbable beginnings into extraordinary scale.[1] Today, Unicorns seem to be everywhere with AI manufacturing them at a dizzying pace.  Black Swans, a term introduced by Nassim Nicholas Taleb to describe extreme, unpredictable events with disproportionate impact, has since been embraced by investors like Vinod Khosla to characterize the rare, transformative outcomes that define new markets.[2]

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Add in the views of Ray Kurzweil and Peter Diamandis (the co-founders of Singularity University) and the strongest advocates of the power of “exponential technologies,” supposedly leading us to a world of Artificial General Intelligence (AGI) by 2029.  Put them all together and we are birthing new Black Swans on a daily basis, allowing most of them to rapidly attain Unicorn status, and collectively solving all the world’s problems while making their backers billions in profits.  At least that seems to be our current market mythology.

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The realities of Power Laws, Fat Tails and Volatility

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But a deeper look at what is going on suggests that what we are seeing is the interplay of three related concepts: Power Law, Tail Risk, and Volatility. 

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Power Law describes situations in which a small number of events or entities (e.g., companies, investments) produce the vast majority of outcomes (e.g., returns, wealth,, market share).  In a Power Law world a very small number of winners dominate, typically described by the 80/20 rule (Pareto principle), where 20% of inputs drive 80% of results, diverging from normal, bell-curve distributions, but increasingly seen in venture capital situations as extreme as 95/5 distributions – meaning that a tiny fraction of portfolio investments generates nearly all returns.  Recent stock market returns research implies a very small percentage of stocks (e.g., 4% in one study) are responsible for almost all net long-term market gains.  Together they project Winner-Take-All outcomes where those Black swan Unicorns grow the fastest, becoming more valuable than the sum of all smaller participants.

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Unfortunately, these Power Law distributions also require the existence of what is referred to as the Fat Tails.  A fat-tail distribution has a higher frequency of outliers (three or more standard deviations from the mean) than a normal distribution.  Put differently, life at the mid-point or “mean” of a fat tail isn’t much fun, it is where investment don’t return invested capital or significant efforts do not produce profitable returns.  We contrast these Power Law/Fat Tail distributions with what we have long referred to as “normal distributions;” those where most results cluster around the mean, what have long been called Bell-Shaped distribution curves – a place where living at the midpoint or mean was an “ok” place to exist. 

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Volatility and the end of Normal Distributions

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The world of our parents grew comfortable with these “normal distributions” and governments and institutions developed ways to create orderly societies around them.

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That is where “volatility” comes in.  What happens when we no longer live in a “normal” world and instead live in one where extreme outcomes become more and more common? Whether we choose to believe it or not, climate change is already causing far more volatile “weather” patterns where what were assumed to be 1-in-100 year or even 1-in-1000 year events are occurring with far greater frequency.  Political change seems to have adopted a similar pattern. Thus, we shouldn’t be surprised as market follow.

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That was Taleb’s deeper conclusion – that modern markets are not well described by neat bell curves. In stable environments, outcomes cluster around the mean and extreme events are genuinely rare. Under stress, however, markets become fat‑tailed: the center thins out, volatility increases, and both catastrophic losses and extraordinary gains become more likely.[3] Empirical research in financial economics, network theory, and firm‑growth distributions supports this view—real‑world systems routinely exhibit power‑law behavior rather than Gaussian symmetry.[4][5] In such environments, safety does not come from hugging the mean. It comes from structuring exposure so that the extremes work in your favor. This is the logic behind the “barbell” approach: concentrate most resources in robustness while allocating a meaningful portion to open‑ended upside.[6]

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A compelling reason to pursue real options

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Real options theory provides the economic framework for operating in this new, more volatile world. A real option is simply the right—but not the obligation—to pursue a future opportunity.[7] When uncertainty is high and outcomes are asymmetric, options become more valuable, not less. The strategic implication is straightforward: expose yourself to many small risks and opportunities so you can learn from both; accept that only a tiny number will produce outsized results; and recognize that modern markets, shaped by network effects, globalization, and interdependence, increasingly behave like winner‑take‑all systems.[8] Research on firm‑size distributions, platform economics, and preferential attachment all point to the same conclusion: we now live in a 95/5 world, not just an 80/20 one, and certainly no longer a 50/50 one.[9][10]

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Tinkering at the speed of Artificial Intelligence

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In such an environment, tinkering is not a hobby—it is a requirement. But tinkering must be aggressive, not passive. Optionality decays when experiments are slow, constrained, or overly optimized for near‑term efficiency. Continuous, rapid evolution—rather than episodic revolution—is the only way to maintain a portfolio of live options. This is where Taleb’s notion of “antifragility” becomes operational: systems that gain from volatility are those that run many small experiments, prune ruthlessly, and double down only when the upside is open‑ended.[11] Research on exploration vs. exploitation, adaptive expertise, and innovation portfolios reinforces this logic.12][13]

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Previously, this tinkering occurred at the speed of the human mind, hopefully allowing us both to experiment and absorb the results of that experimentation.  Today, the tinkering is occurring at the speed of AI, thus ever more frequently outrunning our ability to absorb its implications.

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Do People still matter?

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Until recently, people mattered as much as strategy, now speed may have overtaken both. Some individuals exhibit “proven optionality”—the ability to adapt dynamically, learn quickly, and reconfigure themselves as conditions change. Those individuals, when armed with the power of AI, can move themselves even further out into the steepest part of the Power Law curve.  Studies on learning agility, cognitive flexibility, and adaptive performance consistently show that these individuals outperform in volatile environments.[14][15] Investing in such talent is itself a form of optionality.  It is just that today you must do more than just pursue that option, you must turbocharge it with the power of AI.

Historically, the counterpart to “free-option cultures” were those that celebrate heroism—those who take real downside risk on behalf of the organization—and such heroic cultures even tended to outperform cultures that reward free options, where individuals benefit from upside while externalizing the downside onto others. Taleb referred to this as the “skin in the game” principle; and it served as the practical antidote to moral hazard.[16] Today, we run the risk that heroism is not just ephemeral, but illusory, an Internet, Social Media or AI generated vision without substance and clearly not a limiter on moral hazard or a provider of insurance against bad outcomes.

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When all of this moved at the speed of the human mind, “focus” was the ability, by leadership, to separate the wheat from the chaff, benefitting from the good while discarding the bad.  Focus, in this context, was not about saying yes to the obvious priorities, it was about saying no to the hundred good ideas that dilute optionality. Steve Jobs captured this succinctly: innovation is saying no to a thousand things.[17] Except that today it is a million, if not a billion things to which we must say no and still only a very few for which the right answer is yes. 

Our collective discipline to prune, to concentrate, and to avoid premature convergence is what has kept optionality alive long enough for tail outcomes to emerge.  What if AI and virtual reality have now given us a world in which we no longer understand where to prune, where to concentrate, and what to converge on?

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The uncomfortable truth is that an increasing proportion of those in power, of corporations large and small, of institutions large and small, but importantly of governments large and small —especially those operating under public scrutiny —go through the motions of optionality without actually allocating people, resources, or capital to it.

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Can we sustainably harness creative destruction?

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At a corporate level, leaders they talk about innovation, disruption, and experimentation, but when budgets are set, 99% of resources flow to risk preservation and only 1% to true optionality. Research on corporate resource allocation, R&D portfolio bias, and the innovator’s dilemma all document this pattern.18][19] Meanwhile, those chasing Black Swans and building Unicorns often behave in ways that appear 1% rational and 99% reckless—until they succeed. At that point, the market retroactively labels their behavior visionary.  Increasingly, we have elected officials that are treating our governments and our personal well-being as though they were Black Swans assured of becoming Unicorns but in a world where almost all of us are destined to have to live in the Fat Tail?

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In nature, this process is referred to as “creative destruction.”  In that natural world, as volatility increases, most species of plants and animals begin to assume behaviors that look more like a Black Swan world – they tend toward far greater experimentation, diversity and an understanding that only the few may survive but that life will go on through that process.  The process is not one of recklessness; it is simply a recognition that in volatile, tail‑heavy environments, the rational strategy looks irrational to those anchored in bell‑curve thinking. Real optionality requires real exposure, real experimentation, and real willingness to let the extremes work in your favor. Anything less is theater.

The challenge for us is, what happens when most of humanity cannot or will not follow that edict?  What happens when we leave most behind in a world we tell them is bell-shaped, but has long ago moved to power law status?  In nature, the mutation that chose the right diversification thrives and it becomes the dominant species in the new hopefully returned to normality environment, while those who choose poorly become extinct.  Is that the human path we are on?

 

Footnotes (Sources You Can Cite)

1. Aileen Lee, “Welcome to the Unicorn Club,” TechCrunch (2013).

2. Taleb, The Black Swan; Taleb, Antifragile.

3.  Mandelbrot & Hudson, The (Mis)Behavior of Markets.

4.  Axtell, “Zipf Distribution of U.S. Firm Sizes,” Science (2001).

5.  Taleb, Antifragile (barbell strategy).

6.  Stewart Myers, “Determinants of Corporate Borrowing,” Journal of Financial Economics (1977).

7.  Barabási, Linked (network effects and preferential attachment).

8.  Reed & Jorgensen, “The Double Pareto‑Lognormal Distribution,” Theory and Methods (2004).

9.  Gabaix, “Power Laws in Economics and Finance,” Annual Review of Economics (2009).

10.  Taleb, Antifragile.

11.  James March, “Exploration and Exploitation in Organizational Learning,” Organization Science (1991).

12.  McKinsey, “Innovation Portfolio Management” (various reports).

13.  Lombardo & Eichinger, “Learning Agility” (Center for Creative Leadership).

14.  Hatano & Inagaki, “Two Courses of Expertise,” Child Development and Education (1986).

15.  Taleb, Skin in the Game.

16.  Steve Jobs, Apple internal design philosophy (widely cited).

17.  Bower & Gilbert, From Resource Allocation to Strategy.

18.  Christensen, The Innovator’s Dilemma.