Many readers will know that this past spring I published my third book, Tomorrowland: Scenarios for law firms beyond the horizon.

With the author’s permission, I reproduce here the Introduction to Tomorrowland.  I hope you might find it of interest.

The future may be unknowable, but it’s not unthinkable.

This book is intended to help you think about the future.

Thinking about the future is quite different from predicting the future—it’s unknowable, remember—but that scarcely means we’re helpless or without tools in this endeavor.  This book is such a tool.

I write specifically about possible futures for sophisticated law firms—“Law Land”—but I believe the approach I take and the techniques I’ll apply could be extrapolated without violent distortion to inquiries into possible futures for many other professions, especially those that operate primarily on the home turf of business-to-business  commerce.

Scenarios are at the heart of this book.  A scenario is not a prediction.  A scenario is a mental model, a powerful one I believe, for delving into the question, “If this (current or nascent) trend or phenomenon continues or accelerates in operation, what would the world then look like?”

Scenarios also provide the book with its structure.  As you’ll see, I will propose a series of different scenarios, each of which—were it the only evolutionary force at work—would define strongly if not dictate outright where Law Land is going.   Do not underestimate this.  Indeed, I’ll remind you of and underscore the power of any single scenario, operating unchecked and in isolation, to dominate events through the straightforward and direct matter of chapter titles: I give each scenario one chapter where it “wins.”

Proceeding as if one and only one scenario will “win,” of course, would be too easy.  Come to think of it, in that case I might be able to get away with a single chapter devoted to the winner—why trouble ourselves with the also-ran’s?   Unfortunately that would bring us right back to you, Dear Reader, proceeding with this book in the expectation that I will be advancing predictions and your job is merely to follow along.  Wrong, and wrong.

First, I will not be offering predictions because, aside from the obvious awkwardness should they prove to be mistaken as time unfolds, I find predictions self-referential; they inevitably seem to map the writer’s own self-centered view of the world into the indefinite future in a brute-force, linear fashion.  Understand that we all have such views and that this is not the core of the problem. The problem as I see it is that once one understands the writer’s premises, you tend to learn little more by ploughing through the volume.

This brings us to the second expectation I labeled “wrong:” Do not expect to read this book in passive “receive mode”—not, at least, if you want to extract the most value from it.  I understand that advising you on the attitude with which you should approach this book may seem presumptuous, and at the very least a bit of an imposition, but that’s the way scenarios work.

Scenarios have another advantage in helping us think about how the future might unfold.  We tend to find ourselves trapped by the temptation to default to a linear extrapolation of what’s recently just occurred:  It’s tough to escape the assumptive box that “the best predictor of the weather tomorrow is the weather today.”

This simplistic approach turns out to be improbably accurate when it comes to the weather, but it’s wildly fallacious when it comes to human behavior and the ways of the world.  Yes, the groundwork for any given scenario ought to be discernible in conditions as they are today—I find it a sturdy guide to try to stay in touch with reality whenever possible—but no scenario takes today’s conditions at face value and more pointedly, none follows Alexander Pope’s counsel that “whatever is, is right” (An Essay on Man, I.292 [1733—’34]).

That said, if you are now on the verge of despairing of finding even one prediction in this book, here you go:  This will be my first and last, but one I stand behind with a high degree of confidence:  The world is far too complex for any one-dimensional scenario to win.

Here are a few ways the world is too “complex:”

  • We will experience many surprising exogenous economic and political shocks. That they’ll be “exogenous” implies they’ll be harder to see coming. Nassim Nicholas Taleb famously labeled these as “black swans,” events that have a major impact, come as a complete surprise, and which people often attempt, fecklessly, to rationalize in hindsight.  Black swans:
    • Are rare, high-impact events that normal expectations in finance, science, technology, and political theory cannot predict or account for;
    • Thanks to the essential nature of tiny probabilities, escape normal calculations of likelihood; and
    • Exploit our psychological biases, which blind us to an accurate understanding of uncertainty and the massive impact of rare events.
  • Technology will develop in unforeseeable and, in a profound sense, unimaginable ways. Imagine showing a smartphone to Thomas Jefferson, or for that matter Dwight Eisenhower, and asking them to guess how its technology works and what it can do.  This illustrates Arthur C. Clarke’s postulate that “any sufficiently advanced technology is indistinguishable from magic.”  We may think we live in the post-Steve Jobs era, but viewed differently we’re living in the pre-Benjamin Franklin era.
  • Social mores, customs, and assumptions about such bedrock institutions as work, family, religion, sexuality, and education will, if the past few decades are any guide, soon make today’s received wisdom seem primitive and unsuitable for polite society, even contemptible.
  • The ongoing struggles between liberty and authority, spontaneous bottom-up and technocratic top-down organizing principles, and meritocratic vs. egalitarian societies, will continue to play out unabated.  Contrary to “end of history” buffs, you can trace this debate forward from Plato through Locke, Hume, and Rousseau, to Kant and Nietzsche, and lately even to John Rawls and Richard Dawkins, with no sign of its impending resolution.
  • And competitors, rivals, clients, and talented professionals within your industry or adjacent to it will react to all of the above in unforeseeable ways.

In reality, the word “complexity” fails to do justice to why the future will never play out quite as we might have liked to imagine.  The shortcoming of invoking “complexity,” in isolation, is that we tend to view it as a spatial characteristic of the world—technology in this corner, shocks and black swans erupting from that corner, special interests in their own Venn diagram bubbles, etc.—and we ignore the all-important dimension of time: If one condition changes, it is intellectually and analytically impermissible to assume no other conditions will change in response.

The military has a nice phrase for this: “The enemy gets a vote.”

Or, completing our geometric analogy, the world is not only three-dimensional, it is dynamic.

A tributary of economic thinking that went sadly ignored for nearly a century, and is now enjoying an overdue and well-deserved renascence, is typically referred to as the concept of “radical uncertainty,” and whether or not that term fires your memory neurons, that’s what we’ve been talking about for the past few pages.

Frank Knight (1885—1972), a University of Chicago economics professor, published Risk, Uncertainty, and Profit in 1921 (Boston: Houghton Mifflin), which introduced the world to the distinction between “risk” and “uncertainty:”

“Uncertainty must be taken in a sense radically distinct from the familiar notion of Risk, from which it has never been properly separated…. The essential fact is that ‘risk’ means in some cases a quantity susceptible of measurement, while at other times it is something distinctly not of this character; and there are far-reaching and crucial differences in the bearings of the phenomena depending on which of the two is really present and operating…. It will appear that a measurable uncertainty, or ‘risk’ proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all.”

Indeed, “radical uncertainty” is by some referred to interchangeably as “Knightian uncertainty.”  Examples can be useful in drawing the risk/uncertainty distinction, and a few common ones are insuring your home against fire (a “risk,” with a calculable policy premium associated with it, which actuaries will happily specify for you) vs. asking whether nuclear fusion will be a significant source of electricity generation by 2040.  Where to begin?

Similarly, airlines and regulatory authorities can calculate the likelihood of a fatal crash per X million passenger-miles, but what the economics of the airline industry will look like in (say) 2040 and who the major carriers will be, pursuing what business models?  Not a prayer.

Keynes himself not only fully appreciated Knight’s insights, but extended their implications to conventional economic analysis in The General Theory of Employment, Interest, and Money:[1]

Our knowledge of the factors which will govern the yield of an investment some years hence is usually very slight and often negligible. If we speak frankly, we have to admit that our basis of knowledge for estimate the yield ten years hence of a railway, a copper mine, a textile factory, the goodwill of a patent medicine, an Atlantic liner, a building in the City of London amounts to little and sometimes to nothing; or even five years hence.

By ‘uncertain’ knowledge, let me explain, I do not mean merely to distinguish what is known for certain from what is merely probable.  The game of roulette is not subject, in this sense, to uncertainty.  [The] expectation of life is only slightly uncertain [and] even the weather is only moderately uncertain.

The sense in which I am using the term is that in which the prospect of a European war is uncertain, or the price of copper and the rate of interest twenty years hence, or the obsolescence of a new invention.  About these matters there is no scientific basis on which to form any calculable probability whatever.  We simply do not know.

Nevertheless, the necessity for action and for decision compels us as practical men to overlook this awkward fact and to behave exactly as we should if we had behind us a good Benthamite calculation of a series of prospective advantages and disadvantages, each multiplied by its appropriate probability, waiting to be summed.

Mervyn King, chair of the Bank of England from 2003 to 2013, adopts radical uncertainty as his core idea in his book on the great financial crisis, The End of Alchemy: Money, Banking, and the Future of the Global Economy (W. W. Norton, New York: 2016). He’s also careful to distinguish radical uncertainty from behavioral economics, to which it bears a casual resemblance:

The danger in the assumption of behavioural economics that people are intrinsically irrational is that it leads to the view that governments should intervene to correct “biases” in individual decisions or to “nudge” them towards optimal outcomes.

But why do we feel able to classify behavior as irrational? Are policy-makers more rational than the voters whose behavior they wish to modify? I prefer to assume that neither group is stupid but that both are struggling to cope with a challenging environment.  […]

The problem with behavioural economics is that it does not confront the deep question of what it means to be rational when the assumptions of the traditional optimizing model fail to hold. Individuals are not compelled to be driven by impulses, but nor are they living in a world for which there is a single optimizing solution to each problem.

If we do not know how the world works, there is no unique right answer, only a problem of coping with the unknown.[2]

I would ask you, then, Dear Reader, to proceed with the book in your hands with the notion of radical uncertainty as something of an organizing principle.  Risk lends itself to quantification and indeed to mind-bending equations and economic models, but radical uncertainty is mathematically intractable.

Perhaps that’s why economists tried to ignore it for nearly a century; they didn’t know quite what to do with it.

This is not the time or place to speculate about the future course of academic and popular economic thinking, but permit me to note that taking radical uncertainty seriously demands a profound rethink of conventional economic analysis.  To begin with, rather than postulate a rational homo economicus as the kicking-off point for analysis, convenient because utility-maximizing functions and indifference frontiers lend themselves to standard techniques in algebra and geometry, the intellectual task would be of a different order altogether.

Under radical uncertainty, people, firms, and nations leave the realm of dealing with quantifiable risks and move directly into “coping.”

Which brings us back to scenarios and not predictions.  Predictions are grounded in (usually fallacious) calculations of probabilities; scenarios ask us to imagine how we as individuals and leaders of firms would cope “if…..”

So with this introduction and counsel, shall we begin?

Slip your critical faculties into gear, and I’ll preview the scenarios to follow. I have not arranged their sequence and presentation in any particular structured or principled order or along any spectrum from “most ___” to “least ____” or vice versa, so don’t be disconcerted if you find no such flow.  My goal, to the extent the sequence is purposeful at all, is primarily to keep the perspectives appearing fresh.  Logic compels only the first and the last to appear where they are.

  • Nothing to see here, folks; move along
  • Lawyer psychology, enabled by the partnership model, wins
  • Talent and free agency win
  • Differentiation and “speciation” win
  • New entrants win
  • Networks win
  • Brands win
  • Machines win
  • The dynamics of market evolution.



[1] (London: Palgrave Macmillan) 1st ed. 1936, at 113-114..

[2] Alchemy at p. 133-134.


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