If we know the right choice, why don’t we always make it?
On your way home from work you hit a traffic jam caused by a broken down truck. You decide to take a different route that turns out to be faster and you're home even earlier than usual! Will you take the new route the next day even though your usual route is better most of the time? A study conducted at the University of Ohio looked at our decision-making when it comes to choosing between what worked yesterday and what normally works best. What if your most recent experiences were preventing you from making good decisions?
As Ian Krajbich, one of the study’s co-authors explains, the study was designed to explore “this tension between doing what you should do, at least from a statistical perspective, versus doing what worked out well recently.” To do so, participants were invited to play a simple computer game in which they could earn money by detecting and exploiting trajectory models.
More concretely, the subjects (20 women and 38 men) had to choose between two symbols shown at the upper part of the computer screen on either the left or the right side. Then, by moving the mouse cursor under a line (invisible on the screen) a new symbol would appear (on the lower part of the screen). Participants had to click on this new symbol to discover a reward. For the following tests, the subjects moved their mouse above the same imaginary line (which divided the screen into two parts) and depending on the experimental conditions and the previous choices made, one of the two starting symbols was more likely to lead to a greater or lesser reward.
The participants “played” the game dozens of times. The researchers watched the subjects’ mouse movements to determine whether they had learned a preferential pattern that optimized their earnings between what they were selecting at the top and what they got at the bottom. For example, subjects learned that choosing the top left symbol usually led to the bottom right symbol having the largest reward. At this stage in the protocol, 56 of the 57 participants were able learn the most profitable pattern. The scientists could predict the participants' choices based on where they moved the cursor above the line.
But in the next phase of the study, the researchers broke this established pattern (which led to the biggest reward) by making sure it no longer worked 10 to 40% of the time. The goal was to see if after the most profitable pattern failed, participants would still stick to it anyway or change their habits and choose the other option.
The results show that the participants only followed the old model, which still gave them the best chances for success, in 20% of the situations.
According to the authors, these and other associated findings "suggest that many times we will take the route that worked yesterday and ignore the evidence of what normally works best.” Habits and gut feelings may partially explain why we don’t opt for the best strategy, even when we know it’s the best strategy. As Krajbich states, “It can be hard to judge whether you made a good or bad decision based just on the outcome. We can make a good decision and just get unlucky and have a bad outcome. Or we can make a bad decision and get lucky and have a good outcome.”
As Ian Krajbich, one of the study’s co-authors explains, the study was designed to explore “this tension between doing what you should do, at least from a statistical perspective, versus doing what worked out well recently.” To do so, participants were invited to play a simple computer game in which they could earn money by detecting and exploiting trajectory models.
More concretely, the subjects (20 women and 38 men) had to choose between two symbols shown at the upper part of the computer screen on either the left or the right side. Then, by moving the mouse cursor under a line (invisible on the screen) a new symbol would appear (on the lower part of the screen). Participants had to click on this new symbol to discover a reward. For the following tests, the subjects moved their mouse above the same imaginary line (which divided the screen into two parts) and depending on the experimental conditions and the previous choices made, one of the two starting symbols was more likely to lead to a greater or lesser reward.
The participants “played” the game dozens of times. The researchers watched the subjects’ mouse movements to determine whether they had learned a preferential pattern that optimized their earnings between what they were selecting at the top and what they got at the bottom. For example, subjects learned that choosing the top left symbol usually led to the bottom right symbol having the largest reward. At this stage in the protocol, 56 of the 57 participants were able learn the most profitable pattern. The scientists could predict the participants' choices based on where they moved the cursor above the line.
But in the next phase of the study, the researchers broke this established pattern (which led to the biggest reward) by making sure it no longer worked 10 to 40% of the time. The goal was to see if after the most profitable pattern failed, participants would still stick to it anyway or change their habits and choose the other option.
The results show that the participants only followed the old model, which still gave them the best chances for success, in 20% of the situations.
According to the authors, these and other associated findings "suggest that many times we will take the route that worked yesterday and ignore the evidence of what normally works best.” Habits and gut feelings may partially explain why we don’t opt for the best strategy, even when we know it’s the best strategy. As Krajbich states, “It can be hard to judge whether you made a good or bad decision based just on the outcome. We can make a good decision and just get unlucky and have a bad outcome. Or we can make a bad decision and get lucky and have a good outcome.”
Source: Konovalov, A., Krajbich, I. “Mouse tracking reveals structure knowledge in the absence of model-based choice”, in Nature Communication, April 2020 // Ohio State University website: “People may know the best decision – and not make it” - https://news.osu.edu/people-may-know-the-best-decision--and-not-make-it/