Learn What You Live? New Research Shows Watching Others Can Reduce Decision Bias (Psychology)

New research from the Indiana University Kelley School of Business shows first evidence that watching and learning from others can help reduce bias and improve decision-making.

The research, published in the journal Organizational Behavior and Human Decision Processesused a computer game designed to decrease bias to see if people who watched others play the game could in turn reduce their own bias. Through three experiments, researchers found that watching others solve bias-related problems helped the observers learn about decision biases and improve on their own. Their study showed this observational learning reduced decision biases such as anchoring – or, relying too much on an original bit of information — and also improved how the observers take advice.

“Everyone has biases when it comes to making decisions,” said study co-author Haewon Yoon, assistant professor of marketing at the Indiana University Kelley School of Business on the IUPUI campus. “We’ve found these biases can be mitigated by watching others and observing how they make decisions. For example, as people observe others playing these interactive games, they’re able to see inside the game player’s decision process and learn from their mistakes. Likewise, in a business setting, a training module or video showing employees how managers or co-workers demonstrate decision biases — or avoid such biases — could reduce that employee’s own decision biases. This is a more cost-effective way to teach employees than through extensive training with individualized feedback.”

“From childhood on, we learn by watching others like our parents, siblings, and friends: ‘What is safe to eat? How do I do that? How should we behave in social contexts?’” said Carey Morewedge, professor of marketing at Boston University Questrom School of Business and co-author of the study. “This kind of observational learning teaches us important lessons about the world around us. Unfortunately, it also leads us to absorb many of the biases we observe and exhibit those biased behaviors ourselves. This new research shows that we can learn to improve our decision-making and unlearn some of our biases by watching others. We glean unique insights from seeing others solve problems that help us make better and less biased decisions.”

The researchers explain there is value in reducing decision bias in both personal and professional domains – Take, for example, buying a house. Research has shown that whatever price the seller puts it up for sale at – No matter how much – buyers tend to adjust based on that price. These researchers argue that if you watch someone else committing or correcting the bias, you could take away insights that help you better make those decisions. For hiring managers, this could be used while onboarding employees – or interviewing employees. Asking others to watch and learn helps reduce bias.

“Social learning interventions like observational learning are not only promising in their effectiveness; they are relatively inexpensive to implement and scalable,” said Irene Scopelliti, professor at the Business School (formerly Cass) and co-author of the study. “The findings could benefit all kinds of cases where people have to make decisions under uncertainty (i.e., without all the facts), from which gift to buy a friend to major business, law and policy decisions. We hope this strategy for debiasing decision making is added to the many training interventions used by teachers, government officials and industry leaders to help people make better decisions.”

Featured image: Haewon Yoon, assistant professor of Marketing © IU

Reference: Haewon Yoon, Irene Scopelliti, Carey K. Morewedge, Decision making can be improved through observational learning, Organizational Behavior and Human Decision Processes, Volume 162, 2021, Pages 155-188, ISSN 0749-5978, https://doi.org/10.1016/j.obhdp.2020.10.011. (https://www.sciencedirect.com/science/article/pii/S0749597820303976)

Provided by Indiana University

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