Point Lookout: a free weekly publication of Chaco Canyon Consulting
Volume 20, Issue 20;   May 13, 2020: Neglect of Probability

Neglect of Probability


Neglect of Probability is a cognitive bias that leads to poor decisions. The risk of poor decisions is elevated when we must select an option from a set in which some have outstandingly preferable possible outcomes with low probabilities of occurring.
Matt Schaub, as quarterback for the American football team known as the Houston Texans

Matt Schaub, as quarterback for the American football team known as the Houston Texans, about to deliver a pass. American professional football provides another example of neglect of probability. As I approach secondary school graduation, I receive offers for both a full athletic scholarship as a football player at one institution with a championship football team, and a full academic scholarship at another institution with a leading program in Computer Science. The athletic scholarship has the largest post-graduation upside if I can avoid injury and play well enough to be drafted by a professional team. But according to the U.S. National Collegiate Athletic Association, the probability of selection by a pro football team is 1.6%. This is low compared to the probability of a Computer Science graduate landing a high-paying job — 80% or more. Nevertheless, many choose the athletic scholarship over the academic scholarship. They neglect probability. In this example, the probabilities have a significant effect on the expected value of the outcome of each choice.

When we've made a decision that has led to serious trouble, it's possible that a cognitive bias known as neglect of probability might have played a role. This cognitive bias can affect decision making by causing us to choose among options based solely on the values of the respective "best outcomes," respectively, of those options. Using this criterion leads to trouble when the outcomes of the options are uncertain, because it ignores the probabilities of actually achieving those outcomes.

Stated a Neglect of Probability causes us
to choose among options based
solely on the values of their
respective "best outcomes,"
ignoring the likelihood of those
outcomes actually coming about
bit more precisely, a rational decision would be based on considering both the value of an option's potential outcome and the probability of actually generating that outcome. Instead, when we're under the spell of Neglect of Probability, we tend to assess the goodness of an option by focusing solely (or excessively) on the value of its best outcome, while ignoring the probability of achieving that outcome.

An illustration might clarify this effect further.

The IT department at Dewey, Cheatham and Howe, LLP, (a fictitious global law firm), is upgrading the operating systems of DCH's fleet of personal computers from PC-OS 11 to PC-OS 12 (a fictitious operating system). The task would be relatively straightforward were it not for the enormous number of commercial and custom applications running on those computers. DCH's experts expect that the change from PC-OS 11 to PC-OS 12 will render many of those applications unusable. Among the 18,000 total applications, most are expected to operate correctly, but many will not. The full list of questionable applications is unknown.

Testing all 18,000 applications is an impractically large effort. But by working with the vendors of the commercial applications, and by collaborating with IT departments in other law firms, DCH has reduced the number of applications whose status is unknown to a mere 1,500. That number is less daunting, but it's still impossibly large.

IT has therefore decided to let users of each of the questionable applications perform the testing and certification, in three stages. In Phase I an application expert checks that the app operates in PC-OS 12. If it does, then in Phase II for that app, 10% of the app's users are authorized to use the app for up to 30 days. If they report no problems, then the app is cleared for Phase III, general use. If the Phase II users do report problems, usage of that app is suspended and IT works with the vendor or internal author to resolve the issue. When the issue is resolved, the app is returned to Phase II for another 30 days and the procedure repeats until the app is cleared.

In this way, IT can reduce the number of apps that need more thorough testing. And when an app functions properly, the cost of determining that it does so is very low. These cost-control features are very attractive to IT decision makers.

But there's a problem with this approach. In the 30 days during which Phase II users operate untested apps, those untested apps might corrupt existing data or documents, without the knowledge of the users of the apps. Based on prior experience with PC-OS 10, this corruption is almost certain to occur in many apps. Therefore, the probability of a successful outcome for IT's intended three-phase approach is very low. But the decision makers in IT who conceived of this plan are neglecting the probability of that good outcome. They're attracted by the low cost of the best outcome, and that has caused them to ignore the fact that some applications — IT knows not which ones — will almost certainly cause data corruption. In this example, IT's approach might have a very good outcome, but the probability of that outcome is small.

Neglect of Probability is most likely to play a role in decision making when the decision-making scenario involves choosing among a set of options, some of which have outcomes very much more attractive than others. In these decision-making scenarios, Neglect of Probability tends to cause the decision makers to choose options with too little regard for — or without regard for — the probabilities of success of the various options.

And even when decision makers do consider probabilities, the risk of a poor decision remains unacceptably high for some kinds of mission-critical decisions. Decision makers might in some cases estimate probabilities in a biased way that tends to favor the options with the outcomes they find most appealing. There are indeed many ways to mess things up. Go to top Top  Next issue: Hidden Missions  Next Issue

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More articles on Cognitive Biases at Work:

Deputy Secretary of Defense Wolfowitz, Defense Secretary Rumsfeld, and President Bush in a press conference on September 17, 2001Overconfidence at Work
Confidence in our judgments and ourselves is essential to success. Confidence misplaced — overconfidence — leads to trouble and failure. Understanding the causes and consequences of overconfidence can be most useful.
Brendan Nyhan and Jason ReiflerWishful Significance: I
When things don't work out, and we investigate why, we sometimes attribute our misfortune to "wishful thinking." In this part of our exploration of wishful thinking we examine how we arrive at mistaken assessments of the significance of what we see, hear, or learn.
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The techniques of influence include inadvertent — and not-so-inadvertent — uses of cognitive biases. They are one way we lead each other to accept or decide things that rationality cannot support.
Prof. Jack Brehm, who developed the theory of psychological reactanceCognitive Biases and Influence: II
Most advice about influencing others offers intentional tactics. Yet, the techniques we actually use are often unintentional, and we're therefore unaware of them. Among these are tactics exploiting cognitive biases.
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Planning teams, like all teams, are vulnerable to several patterns of interaction that can lead to counter-productive results. Two of these relevant to planners are a cognitive bias called the IKEA Effect, and a systemic bias against realistic estimates of cost and schedule.

See also Cognitive Biases at Work and Critical Thinking at Work for more related articles.

Forthcoming issues of Point Lookout

The future site of 2 World Trade Center as it appeared in 2013Coming October 5: Downscoping Under Pressure: I
When projects overrun their budgets and/or schedules, we sometimes "downscope" to save time and money. The tactic can succeed — and fail. Three common anti-patterns involve politics, the sunk cost effect, and cognitive biases that distort estimates. Available here and by RSS on October 5.
A hummingbird feeding on the nectar of a flowerAnd on October 12: Downscoping Under Pressure: II
We sometimes "downscope" projects to bring them back on budget and schedule when they're headed for overruns. Downscoping doesn't always work. Cognitive biases like the sunk cost effect and confirmation bias can distort decisions about how to downscope. Available here and by RSS on October 12.

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