Beating Bias: Debiasing Strategies for Everyday Decisions
As we gain a fuller understanding of the heuristics and biases that influence our everyday decisions, so too are researchers looking for ways to combat their ill-effects. From this literature, two main strategies for combatting decision biases have emerged — detailed in the below analogy:
“Imagine a simple door that is normally held shut with a spring mechanism. If the spring is faulty (i.e., it has lost its ability to push the door shut), this door would remain open. Let this open door serve as a metaphor for a bias. There are two ways to correct this bias. One option is to simply repair the faulty spring hence directly address the cause of the bias. This would constitute a debiasing strategy. Alternatively, we can exert an opposite force of the faulty spring that keeps the door shut, and this would constitute a rebiasing strategy. Note that both strategies achieve the same end result (a shut door), but do so using very different mechanisms.” – Soman and Liu 2011 
In essence, debiasing seeks to remove a bias altogether, while rebiasing seeks to swap one bias for another. [1,2]. This article focuses on lessons from the debiasing literature, and offers real world strategies for combatting bias in our daily lives.
Behavioral Science, Democratized
We make 35,000 decisions each day, often in environments that aren’t conducive to making sound choices.
At TDL, we work with organizations in the public and private sectors—from new startups, to governments, to established players like the Gates Foundation—to debias decision-making and create better outcomes for everyone.
According to Sharot (year), about 80% of the population has an optimism bias — meaning we are more likely to adjust our beliefs in response to positive information than we are negative information of the same quality . So, for example, though being lauded by a colleague may boost our self-image, being criticized by the same person would have less effect. Sharot attributes this to an error in our frontal lobe, which has an easier time encoding positive information. What this leads to, then, is a mis-calibrated belief system, erring towards positivity. What type of impact could this have on our decision making?
While optimism can, of course, be helpful, too much optimism leaves us naïve to fully-feasible, negative future outcomes. To combat this, many behavioral scientists, including Gary Klein and Daniel Kahneman, have embraced a strategy known as prospective hindsight [4,5,6,7]. This strategy asks individuals to imagine that the future outcome of the choice they are currently making turns out to be a failure. Put simply, this strategy asks individuals to imagine that whatever decision they make turns out poorly — and it is intended to make us more aware of alternative outcomes.
Imagine trading stocks without ever having experienced a significant correction in the market. Your experience in a market boom may make you discount the prospect of a market drop in the near future. This notion has lead some investment banks to employ prospective hindsight strategies (i.e. “premortem”) to account for the possibility of overly optimistic traders .
Now let’s say it has been about a year since your last trip to the dentist. You know you need to schedule an appointment, as your future, shiny smiled self will thank you — but you are loath to spend an hour actually having your teeth cleaned.
We all have this natural inclination towards doing what feels good now as opposed to what is good for us in the future [4,9]. One of the more interesting solutions to this present bias is known as temptation bundling . That is, the pairing of an easy, immediately-gratifying behavior with one that is more effortful, but which entails a long-term payoff.
Cue the dental spa (link). This dentist-spa hybrid offers patients fresh coffee, heated pillows, and even massages to go along with their dental treatment . From this concept, it is apparent that dental offices are aware of the fact that people need an extra incentive to make their appointments. The hope is that, by coupling their cleaning with more-gratifying activities, they can ensure clients schedule their annual check-ups.
People may also be considered biased if their behavior deviates from a norm in a specific way [4,12]. Creating a decision environment to increase the salience of social norms is a debiasing strategy that has proven to reduce this biased behavior [4,13].
The AI Governance Challenge
Imagine if you could see how much water you use compared to your neighbors. What if the majority used significantly less than you? Would you aim to reduce your water consumption or simply keep using the same amount of water? The dropcountr app takes this exact approach with the hope that comparing your water use to your neighbor’s will incentivize users to curb their water use .
Remember that what’s important here is to focus on creating behavior change. To start:
- Identify the biased behavior. Some biased behaviors are more evident than others. Do not get discouraged if you can’t identify a specific bias.
- Identify the root cause of this biased behavior. This step is where the behavior change needs to happen.
- Develop a corrective strategy to moderate this biased behavior. This is what will be applied to fix the root cause of the behavior.
Debiasing may not be a one-size fits all solution to reducing our biased behavior — but used in the right contexts, it can have a significant impact on how we make decisions.
Soman, Dilip, and Maggie W. Liu. “Debiasing or rebiasing? Moderating the illusion of delayed incentives.” Journal of Economic Psychology 32, no. 3 (2011), 307-316. doi:10.1016/j.joep.2010.12.005.
Larrick, Richard P. “Debiasing.” Blackwell Handbook of Judgment and Decision Making (n.d.), 316-338. doi:10.1002/9780470752937.ch16.
McRaney, David, and Tali Sharot. 2017. “Optimism Bias”. Podcast. You Are Not So Smart.
Soll, Jack B., Katherine L. Milkman, and John W. Payne. “A User’s Guide to Debiasing.” The Wiley Blackwell Handbook of Judgment and Decision Making, 2015, 924-951. doi:10.1002/9781118468333.ch33.
Mitchell, Deborah J., J. Edward Russo, and Nancy Pennington. “Back to the future: Temporal perspective in the explanation of events.” Journal of Behavioral Decision Making 2, no. 1 (1989), 25-38. doi:10.1002/bdm.3960020103.
Klein, Gary. “Performing a Project Premortem.” Harvard Business Review. Last modified 2007. https://hbr.org/2007/09/performing-a-project-premortem.
Kahneman, Daniel. Thinking, Fast and Slow. New York: Farrar, Straus and Giroux, 2011.
“UBS Investment Banking’s Andrea Orcel on Testing Against a Market Crash.” Business Insider. Last modified 2015. https://www.businessinsider.com/ubs-investment-banking-chief-andrea-orcel-runs-a-pre-mortem-to-test-against-a-huge-market-crash-2015-10.
Milkman, Katherine L., Todd Rogers, and Max H. Bazerman. “Harnessing Our Inner Angels and Demons: What We Have Learned About Want/Should Conflicts and How That Knowledge Can Help Us Reduce Short-Sighted Decision Making.” Perspectives on Psychological Science 3, no. 4 (2008), 324-338. doi:10.1111/j.1745-6924.2008.00083.x.
Milkman, Katherine, Julia Minson, and Kevin Volpp. “Holding the Hunger Games Hostage at the Gym: An Evaluation of Temptation Bundling.” PsycEXTRA Dataset, 2012. doi:10.1037/e513702014-057.
McKinney, Merritt. “Lie Back and Be Pampered … in the Dental Chair – Health – Special Reports – Taking the Bite Out | NBC News.” Msnbc.com. Accessed October 8, 2017. https://www.nbcnews.com/id/5327027/ns/health-special_reports/t/lie-back-be-pampered-dental-chair/#.Wd0rgBNSy1u.
Hammond, Keith. “Human judgment and social policy: irreducible uncertainty, inevitable error, unavoidable injustice.” Choice Reviews Online 34, no. 08 (1997), 34-4545-34-4545. doi:10.5860/choice.34-4545.
Allcott, Hunt. “Social norms and energy conservation.” Journal of Public Economics 95, no. 9-10 (2011), 1082-1095. doi:10.1016/j.jpubeco.2011.03.003.
Dropcountr – Dropcountr. Accessed October 10, 2017. https://dropcountr.com.