Riding Uncertainty

To appear in JPER

Commentary

Introduction

We “ride uncertainty” when we must act, perhaps make a

decision, but the probabilities and consequences are

unknown. In fact, we do not know what we do not know:

there are unk-unks, unknown-unknowns, a term developed in

the aerospace industry, which, having systematically analyzed

“all” contingencies, in practice discovered ones that

they hadn’t imagined. We do not know that we do not know

or what we do not know. We are to be genuinely surprised.

   Often, such situations are ambiguous, their meaning is

unclear, or there are many potential meanings to what is

going on. We encounter piracy when the world and our

adversaries do not follow any of the standard rules, violating

the laws and expectations. And in an unknown-unknown

ambiguous piratical world, action may well be deterred

because we cannot figure out the consequences of any particular

action.1 We are in an uncertain situation: unk-unks,

ambiguities, piratical, and deterring. At the same time, uncertainty

means that there might well be opportunities we had

not imagined and chances for inventive action where we

once thought we were so precluded by our lack of knowledge

and information. By our action, we might well tell a new

story about our situation and give it concreteness and meaning,

taking noise and signals and making of them something

that allows us to figure out what we might do. Ambiguity

becomes resolved through our actions and the story we tell.

In effect, while we know less than we believe we know, we

also know more than we allow.2 While some awful contingencies

might be given small but reliable probabilities, it

may be that the consequences of uncertainty are even more

awful and even likely. Out of a noisy, deceptive environment,

through prudence, vigilance, and curiosity, through attention

to precursors, we forge our way forward.

    Entrepreneurs, Special Forces soldiers, particle physicists,

and new parents ride uncertainty. The physicist probes

by shooting high-energy particles into other particles,3 and if

that is not enough, the physicist builds more sensitive detectors

or larger accelerators to burst through the curtain of

uncertainty. The Special Forces soldier is in fact the model

for much of what I describe here as riding uncertainty, and

what I say here is drawn from conversations with my students

who were members of the Special Forces and from the

literature.4 For the entrepreneur, uncertainty is the opportunity

to exercise one’s experience and judgment. New parents,

no matter which books they read, whatever guidance they

receive from others, are recurrently in the uncertain, their

infants challenging them and training them to be parents.

   My purpose in this Commentary is to describe riding

uncertainty. I am making no prescriptive claim. The italicized

phrases throughout epitomize my description. To keep

this Commentary within an acceptable length, yet to indicate

how riding uncertainty is related to other notions in planning

and the wider literature, my notes and references will be

briefer than I would prefer.5

   I first discuss planning, riding and riders, and then related

earlier work.

Planning and Uncertainty

Planning, by its nature, demands that we consider uncertainty.

We have limited knowledge of the future, of potentialXXX10.1177/0739456X19893448Journal of Planning Education and ResearchKrieger

article-commentary201

actors, of contingencies, the economy, and changes in values.

We might make alternative plans, with different assumptions,

to get a sense of the range of possibilities. Decision

analysis has come to play a central role in planning. This

prevailing social scientific model of decision-making is a

matter of probabilities of outcomes multiplied by costs or

benefits, to get expectations. And then one seeks the most

beneficial expected outcome. The vast literature in this field,

including risk analysis, articulates this model, taking into

account multiple objectives and decision-makers and

sequences of decisions, and how we might deal with our lack

of knowledge (often called “uncertainty”) about risks and

costs or benefits.6 Rare events or those with catastrophic outcomes

require careful consideration, since multiplying small

probabilities by large costs may give unreliable guides to

decisions. And so one also wants to have estimates of the

range of expectations (also sometimes called “uncertainty”),

and perhaps one needs to develop an insurance scheme to

deal with such situations. Flexibility and better rational decision-

making, in the context of organizational learning, and

better modes of discerning less-imaginable events, are some

of the main themes in the literature (Mack 1971). Hence, one

may speak of risk governance and management. Moreover,

in many planning projects, the decisions are “big” and they

are likely to transform the landscape, so that our prospective

valuations of benefits and costs may well change dramatically

were we to have the project in place. All of these situations

and considerations have been incorporated into the

dominant model. Still, this canonical account of decision and

judgment needs to be supplemented if we are to give a better

account of what people actually do in planning and subsequently

in building and developing.7

   But “uncertainty,” as understood in the dominant model,

does not encompass the kind of uncertainty I want to address,

a distinction between risk and uncertainty already provided

by the economist Frank Knight. When we don’t know what

we don’t know, or that we don’t know, what I shall here call

uncertainty, it is difficult to plan. For the dominant model

has less to say when we don’t know our alternatives or their

probabilities, and we don’t know we don’t know them. Still,

there are other avenues that may prove valuable. Namely,

planning for uncertainty may be being ready for just what we

cannot anticipate or imagine anticipating, so that we ride

uncertainty, welcoming the opportunities and challenges it

presents. Here planning enters a realm where a different sort

of rationality and chance-taking may make sense.

  Planners sometimes act this way, their vision and power

sufficient to silence conventional rational arguments.

Nowadays, we are likely to condemn such actors. (Robert

Moses, as described in Caro’s [1975] The Power Broker is

archetypal, although Moses’ reputation is now undergoing

something of a revision.) Whether we approve of such action,

we need a way of understanding it that does not reduce it to

defective vision and out-of-control power.

Riding Uncertainty

In this realm, action leads to information and decision. Not

quite, Act First, Then Think, but almost. Actions probe the

world, and its response is informative. Those actions are

drawn from our repertoire of actions and responses, gained

through experience and learning. We skillfully cope with

what is in front of us. We make preemptive moves that shape

the world so that what is uncertain is bounded, and we might

beat some worst consequences. We make moves that are

good no matter what the other side will do. And we might

well go for broke since the alternative is our never having a

chance to move forward. We use research and policy analysis

to discover options others do not yet realize, the means

through which we discover alternatives we had not imaged

before we began such an analysis.8 And, through self-insurance,

we may encourage prevention, moderation of consequences,

and perhaps compensation for harm. Were it

possible, it is worth investing to lessen regret, but here, in so

far as we are uncertain, those regrets cannot be imagined. For

reinsurance, we might be attached to an insurer of last resort,

that is, one who takes on the uninsurable (typically, government).

Ideally, we have budgeted (cut our expenditures) to

allow for uncommitted resources, liquidity in our assets

(Keynes), so that we may draw on them in the most strenuous

of circumstances. And, we want to stay alive, and keep

staying alive, be sufficiently resilient, so that we might be

able to make moves in another day and time.

In trying moments, when uncertainty is the order of the

day, there emerge practices that more or less work well

enough, or if not we learn what we might do the next time.

We do not attend to, we do not focus on impossibility, for we

are driven by invention and novelty that we believe will allow

us to go around impossibility by seeing constraints as opportunities.

We may prefer some disjointedness to coordination,

so that on-the-ground improvisation is available to us.

From experience, from practical knowledge, and from

skills which are preconscious, we bring something unexpected

into being: that is, we go from intuitive knowledge to

creation (what the Greeks called a transition from métis to

poesis9). And we may be able to manage uncertainty, those

“unstudied” conditions we have not anticipated, by, for the

moment, managing the interplay of volatility of the situation

and the options we have available.10 So, for example, in a

situation in which there is great volatility and limited options,

we might violate the rules just for now; if volatility is high

and options are plentiful, we operate just on time, aiming for

flexibility. (There is also just in case and just this way.) To

find out more about what is going on we might tickle or

probe the world and see how it responds, and if that is precluded

by a curtain of uncertainty, we may explode materiel

(say, employ spy satellites, not a literal explosion) so that the

curtain is parted a bit and we know more.11 We are trying to

bound uncertainty.

Moreover, we are always doing repair work, going around

the rules, cutting organizational boundaries, so that we are

less likely to have cascading failures. We want to stop a rip

in the fabric before it becomes catastrophic.

   Following Roe and Schulman, rather than asking what

could go wrong, how likely is it, and what are the consequences

if it does go wrong, we might ask what’s going right,

what’s even better, how do I get there, and then what could go

wrong in trying to get there, how likely is that, and what are

the consequences if that goes wrong.

   You want to do a decent job of finding signal buried in the

noise, but if you have an idea of the shape of the signal (as they

did for gravitational waves) that helps enormously. It is not

quite a curtain you need to part nor is it the uncertain that is

hidden from us. What needs to be done is to see the “not knowing”

and then respond. While much of this sounds impractical

and abstract, in actual practice it turns out to be good guidance,

at least according to those who ride uncertainty.

   Of course, these actors will fail and there will be sacrifice.

But they and their colleagues come back and go on again and

again, and for good reason.

   I am trying to describe what people actually do. We live in

cities that have been transformed by such action (New York

and Paris are archetypal), and one might well not approve of

such planning, yet also want to understand how it works.

Riders of Uncertainty

Those who ride uncertainty move toward the uncertain (for it is

safer to go toward it than to avoid it), forge their way forward in

each moment, and when the ball comes to them they do not

clutch but catch and then make a move, and their teammates

may take over, and then they keep going. Riders are hopeful and

practically optimistic, for then they are more likely to succeed.

They blunt downsides and take advantage of upsides. They are

hungry for the opportunities, for the products of uncertainty.

Failure is the occasion for invention. And fear is indicative,

dreams are proleptic—of potential action. Riders are in the middle,

on the ground, and they find there is always one more move

to be made (if not now, then after they have restored themselves).

They are never at rest (Newton (1850): “. . . he that is

able to reason nimbly and judiciously about figure, force, and

motion, is never at rest until he gets over every rub.” [1694]).

Moreover, for the rider of uncertainty, time is a matter of events,

rather than clock time, and so in effect they are never rushed,

never out of time as long as they keep going.

   Riders of uncertainty are usually part of a team, with a

wide range of experience among the team’s members, each

of whom makes the others’ work better. Their shared experience,

and their complements to what is not shared, gives

them a resource of moves and a chance to invent new moves

as part of their repertoire. There is strength in numbers, and

in effect it is the kindness of strangers, that is, the contributions

of the team’s members, that empowers them much

above what they might do on their own.12 As a team, they are

reliable, more practically vigilant, noticing precursors, double-

checking without clutching or paralyzing each other.13

In uncertainty, as we learn more, as our actions teach us

more about our situation, we become more capable of imagining

the unimaginable. Namely, we can more effectively

take what is uncertain and make it less ambiguous, make

decisions based on our probing actions, and relieve ourselves

of implicit constraints we once took as given. That imagining

does not assure us of its correctness. Rather, it allows us to be

more vigilant, more inventive, and less bound by what everyone

claims to know. In effect, what is taken to be necessity

may be a false necessity (Unger 1987).

   Of course, you may well have an adaptive piratical adversary,

perhaps informal rather than bureaucratic, readily cutting

corners, gaming the system, deceiving you, taking your

moves, and turning them on yourself, creating further ambiguity

and previously unimagined piracy, so deterring you.

Yes, the adversary gets a vote, as they say. Even if you are

proficient in “thinking about what they are thinking about

what you are thinking,” and you create much the same situation

for your adversary that they plan to create for you, your

advantage is that you are never at rest, you are moving, so in

effect you might fake them out. You set the terms and sites of

engagement, allowing for fewer sites where they may choose

to engage you. But you may well be defeated, for the moment,

your devices and desires14 not being up to the challenge. You

will come back stronger, more rested, and so create problems

for that adversary they cannot now imagine. So you might

erode your adversary, degrading them so that they will cry

“Uncle!” Your task is to prevail, and you might come back

again and again, never at rest, never without a next move, so

wearing them down. If you can buy time through options and

invention, you have more time to survive and to degrade the

adversary.

   Now, you may well find yourself in need of the insurer

of last resort, for you have discovered that your uncertainty-

riding has lost its horse. You may choose to sacrifice

yourself; more wisely, you may choose to rest, to regroup,

and be indomitable. That demands a high level of successful

experience, so that your confidence in yourself and in

your team is well founded. And it may be that another

team, fresher, with a different repertoire, needs to be called

in off the bench.

Will the survivors envy the dead (Herman Kahn’s question)?

Namely, in the end, you must feel justified, legitimate,

whole, able to go on to the next task, with hope, and

once more to get on your horse and ride uncertainty as you

encounter it.

Predecessors

It is revealing to find ourselves describing uncertainty by

carving out a realm for it. For what earlier authors were doing

was allowing for what modern rational decision theory would

aim to displace.

   Albert Hirschman spoke of possibilism. Chia and Holt

suggested that “acts are attempts to intervene and clarify the

ambiguous situation we naturally find ourselves in.” The

poet John Keats suggested that some people have what he

called Negative Capability, to transcend and revise contexts,

a rejection of constraints, “capable of being in uncertainties,

mysteries, doubts, without any irritable reaching after facts

and reason.” Bracha & Brown, following Ellsberg, suggest

that a preference for ambiguity is an indicator of optimism, a

willingness to face undefined situations, take hold of them,

and so find meaning in the world. And Dreyfus suggested

that skillful coping based on deep experience allows a person

to act automatically and sensibly in otherwise indecipherable

situations. They do not run out of luck, for luck is in the leftovers,

that we find luck by keeping on going. John Maynard

Keynes described how people act without information, when

they haven’t a clue, pushed on by their animal spirits. And,

Frank Knight emphasized that there are situations when we

do not know enough to think in terms of risk and probability,

for we are in an uncertain situation. James Scott uses the

Greek notion of métis to describe how we act: locally and

sensitive to the unique environment, relying on our experiential

intuitions.15

   Just as we cannot know all the contingencies that will

defeat us, just enough of them, and we have convinced ourselves

that we have considered enough of them and still find

our path blocked, we cannot anticipate our inventions at the

moment of need that would seem to go around the proofs of

impossibility and the blocked paths. Such actors are rational

given their experience, their capacity to invent backups to

their backups. For them, there are always emergent practices

and local contingent scenarios, derived from the particulars

of a situation, particulars we are unlikely to have been able to

foresee. Crucially, uncertainty is not merely a matter of notknowing

defined as probabilistic risk, it is a matter of not

knowing you do not know: an unknown-unknown. Riders of

uncertainty do know what they are doing when they believe

that they will succeed despite the odds.

    Theories of planning have almost always sat on a bedrock

of rationality, articulating and rejecting rationality—with

new considerations appearing each twenty years. Planners

adopted the dominant model and tried to make it work for

their purposes, realizing that considerations of politics and

participation may have overarching importance.

Riding uncertainty is not a rejection or articulation of

rationality in planning as it has been conceived, so far. Riding

uncertainty has its own logic, and, in terms of that logic, it,

too, is rational.16 To bring its model to the fore, as we understand

planning and planners and other actors, is to give ourselves

a way of thinking that complements the dominant

model. And also a mode of criticism very different than that

provided by conventional rationality, for we may understand

what people are doing and then critically think about that.

Notes

1. Delpech (2012) suggests that piracy—lawlessness and deception,

disrespect for international law and accepted rules of

behavior—thrives when there is no acknowledged hegemon.

While uncertainty may contribute to a deterrent effect making

your adversary more prudent, as argued by T. Schelling, H.

Kahn has argued that knowing just what your adversary will

do will contribute to deterrence, making you more prudent.

If we are in a piracy regime, Delpech suggests that our opponents

will gamble more, be less willing to follow conventional

norms, and so not only increase uncertainty, but make it much

harder to figure out what they might do.

2. Here I follow Emery Roe and L. S. Schulman’s work (Roe 2013).

The relevant skills are pattern recognition, scenario formulation,

and performance-mode-maneuverability among options.

3. See Hacking (1983), more generally on probing.

4. So, for example, there is a chapter in Piore (2017), “Soldiers

with Spidey Sense,” about the role of intuition and pattern

matching.

5. Gaddis (2018) writing about “grand strategy,” using examples

from history and literature, emphasizes the importance of living

with incompatibilities, having experience corrected by

theory, improvisation complementing planning, juggling as

a balancing act of those incompatibilities, and what he calls

temperament, having capacities in mind when ambitions are

prime. I believe his account is a complement to mine, the storyteller

and historian rather than the decision analyst.

6. For a review of some of this literature, and references to more

of it, see, for example, Andrews, Hassenzahl, and Johnson

(2004). For a state-of-the-art survey of current practice in this

realm, see Ezell et al. (2010) and Friedman and Zeckhauser

(2012). In the latter, uncertainty is treated by reviewing

National Intelligence Estimates. For a discussion of uncertainty

in the context of contemporary theoretical notions, see

Javorsek and Schwitz (2014). Earlier surveys and analyses

are to be found in Morgan and Henrion (1990), Finkel (1991),

Smithson (1989), and Funtowicz and Ravetz (1990). See also

R. J. Lempert’s work at Rand Corporation on Robust Decision

Making and Y. Ben-Haim (2015) “info-gap” decision theory.

7. Kahneman (2011) provides some correctives. And Bent

Flyvbjerg’s work on megaprojects tries to discover ways of

restoring conventional rationality to this realm.

8. It was said of Albert Wohlstetter that his analysis method as

developed at RAND Corporation in the 1950s was to find such

alternatives.

9. J. C. Scott, in Seeing Like a State, defines métis as a wide array

of skills learned in responding to a changing environment,

Krieger 5

rules of thumb acquired through practice, resisting simplification

and transmission through book learning, since the environment

is novel each time, local, and situations are never

identical. See C. M. Patrick (2013), who quotes from Scott.

10. Here and in what follows, I am following Roe (2013)/

Schulman.

11. Hence the value of spy satellites (Ruffner 1995).[AQ: 3]

12. “Strength in Numbers” is a phrase from Steve Kerr, coach of

the Golden State Warriors. Basketball play is not far from my

mind as I write.

13. I take this notion of vigilance from the Harry Potter novels; it

is Alastor Moody’s mantra (Rowling 1998).

14. From the general confession in The Book of Common Prayer

(1662).[AQ: 4]

15. Hirschman (1995, 64; 1971, 21; 1967). Chia and Holt (2009,

42–43, 112–13). Keats (1947, 72). Bracha and Brown (2013).

Bracha and Brown’s discussion draws from Ellsberg (1961,

659–60), in which uncertainty is divided into risk and ambiguity,

and where he suggests that subjective probabilities depend

on payoffs. Dreyfus (2014) calls this System-0, distinguishing

it from Kahneman’s System-1 and System-2. Kahneman

is suspicious of this mode of acting, since it is subject to a

variety of mistakes, which he has described; Klein suggests

that this mode of acting is often quite successful and wants to

account for its success (Kahneman and Klein 2009). As for the

“leftovers,” this comes from a Japanese phrase I encountered

it in Cameron (2017, 564), “. . . we must keep going. We find

our luck by working through to the last.”[AQ: 5]

16. For an example of critical consideration of riding uncertainty,

see Bergman (2018).

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[AQ: 6]

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Author Biography

Martin H. Krieger is professor of planning in the Sol Price School

of Public Policy at the University of Southern California, Los

Angeles, CA. He is preparing a book of his photographs of people

at work in industrial Los Angeles, under the auspices of the John

Randolph Haynes and Dora Haynes Foundation.

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