Our cloudy crystal balls

Behavioral New World

July 1, 2026

Our cloudy crystal balls

Consider this possible scenario: You currently work at Company A. You think there is some probability that you will become CEO of the company in about five years and that you will find a high degree of satisfaction in that role. But you’ve recently been presented with the opportunity to move to Company B, where you would also have some probability of becoming its CEO in the same amount of time, and you would also experience a high degree of satisfaction if that were to happen.

Thinking about each possibility, you recognize two primary facts as relevant: the probability of your getting to the CEO’s seat, and the “utility” you would experience if it were to happen. Economists use the word utility to refer to satisfaction or happiness.

So how might you decide between staying with Company A and moving to Company B? Daniel Bernoulli, the famous Swiss mathematician, offered (in 1738!) a framework for thinking about decisions nearly identical to this (there weren’t CEOs per se back then, but let’s stay with that example for the time being). His approach consists of three seemingly straightforward steps.

First, you estimate the utility associated with being CEO of Company A. Compensation is certainly one consideration but it’s just one, and maybe not even the main one. Your utility depends on many other subjective factors, e.g., the quality and type of the individuals you would work with daily; the inherent interest you might have in the company’s particular industry, not to mention products; and the opportunity the company might offer you to stretch and grow your skill set, to name only a few.

To make an estimation of this kind may seem rather daunting, so you decide to quantify your satisfaction on a 1-to-100 scale. You decide that the score at Company A is 90. Now repeat the thought experiment, thinking about being the CEO of Company B. Let’s say you decide in that case on a satisfaction score of 95.

(If this approach to decision-making seems impractical, bear with me—I’ll suggest its value below.)

Second, because neither outcome is guaranteed, you need to estimate the probability of each occurring. How likely is it that you will become CEO of Company A? Let’s suppose you assess that possibility as 70% likely to occur. And how likely would it be that you will become CEO of Company B if you change jobs? You assess that probability as 60%.

Third, you multiply the probability of each outcome times the utility you expect from each. The results are called the “expected utility” of each outcome. You then choose the outcome with the higher expected utility.

The expected utility of staying with Company A is 0.7 x 90 = 63. The expected utility of moving to Company B is 0.6 x 95 = 57. Danny B, as he was known to his friends, would have you stay with Company A.

In his best-selling book, Stumbling on Happiness, psychologist Daniel Gilbert suggests that estimating probabilities is the easier of the two tasks: “Calculating such odds is relatively straightforward stuff, which is why insurance companies get rich by doing little more than estimating the likelihood that your house will burn down…” (p. 260).

I’m less confident than Gilbert about the ease of calculating the probabilities (“odds”). Predicting how many houses among many will burn down can be done with some precision. But that is different from predicting whether one house in particular will burn down. That depends on specific factors such as the behavior of the residents (do they smoke?), the construction of the house (wood or cement?), and the location of the nearest fire hydrant.

Your potential promotion to CEO is a singular case, analogous to the single-house case. Put differently, there is no database of CEO promotions that would permit you to arrive at a confident prediction of your probability of being promoted (though theoretically, in another 10,000 years or so of corporate experience and data collection, there might be).

However, the focus of Gilbert’s book is on the difficulty of estimating the utility associated with a future, uncertain event, and here I am in full agreement with him. He offers two suggestions for dealing with this challenge. First, “…the best way to predict our feelings tomorrow is to see how others are feeling today” (p. 251). Although imperfect, this exercise does provide information. If most people appear to be quite happy as CEOs (especially people who seem to have some similar character traits and background to you, I would add), then probably you would be as well.

His second suggestion: “…simply step into tomorrow’s shoes and see how well they fit” (p. 262)—the first step described above. That is, imagine being the CEO of Company A—how much satisfaction do you feel? Now imagine being the CEO of Company B—how much satisfaction? Here again, although not an exact science, a potentially useful exercise.

One limitation of this second approach is “projection bias,” which refers to our tendency to overestimate the stability of our current beliefs, values, and feelings.** For example, when we are hungry, we can project that into the future, unconsciously feeling that we might always be hungry. Consistent with projection bias, hungry shoppers have been shown to buy more groceries than those who aren’t hungry.

And moving out into left field for a moment, here’s another suggestion for making better decisions: Make them with a full bladder. The title of the research (link) says it all: “Full Bladder, Better Decisions? Controlling Your Bladder Decreases Impulse Choices.” Stay well hydrated as you decide whether to move to Company B. Who knew?

Anyway, where does this leave us? First, we can make better decisions by assessing, as best we can, the probability of future events and the utility associated with those events. For example, we can easily imagine the utility of winning the lottery, but let’s also think about the probability of that occurring. (The lottery industry won’t like this, though: If more people focused on the probability, surely fewer lottery tickets would be sold.)

Second, in assessing the utility associated with future events, be aware of projection bias. Specifically, recognize that our current mental state can influence our decisions. One way to neutralize that risk is to stop and ask oneself: Am I in a “hot” mental state? Wait to cool down. Another question: Am I currently engaged in or particularly susceptible to catastrophic thinking? Step back—how likely is that worst case that I am imagining? You want to get yourself on a more even keel before making a major life decision.

Finally, given the lack of precision of these exercises, I personally recommend something Danny B never got into: The notion of becoming more comfortable with uncertainty. One place you might start is Pema Chödrön’s book, Comfortable with Uncertainty. She argues, as many a philosopher has, that the nature of our existence, whether we realize it or not, is relentlessly in flux. Embracing that fact, rather than resisting it, can lead to a much more fulfilling life, which includes better decision-making.

**See here for a more detailed explanation of projection bias.

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