Quick decisions are often biased and misleading

Who hasn’t made a snap decision and later regretted it? Maybe our biases had something to do with it. Surprisingly, the speed of our decision-making process may reveal a lot about our inherent prejudices, according to an intriguing study conducted by mathematicians at the University of Utah.

The lead researcher is Sean Lawley, an associate professor of mathematics, supported by a skilled team of former and current graduate students from Utah. Together, they have examined the interplay between biases and the velocity of decision-making.

Mathematics of decision-making

Now, what does mathematics have to do with the psychological process of decision-making? The answer is, quite a lot, as Lawley’s team has demonstrated. They developed a mathematical framework to understand decision-making patterns in groups where individuals hold different levels of bias.

“In large populations, what we see is that slow deciders are making more accurate decisions,” said lead author Samantha Linn, a graduate student in mathematics.

“One way to explain that is that they’re taking more time to accumulate more evidence, and they’re getting a complete picture of everything they could possibly understand about the decision before they make it.”

Biases in decision-making

The researchers sought to unravel how individual biases within groups play a role in the quality and order of choices being made. Are decisions simply an echo of an individual’s predispositions, or does accumulated evidence have a role in shaping the final call?

Turns out, the old saying “haste makes waste” might hold some truth. The team found that the faster the decision was made, the less informed it probably was, and therefore, more likely to be incorrect. 

“Their decisions align with their initial bias, regardless of the underlying truth. In contrast, agents who decide last make decisions as if they were initially unbiased, and hence make better choices,” noted the study authors. “Our analysis shows how bias, information quality, and decision order interact in non-trivial ways to determine the reliability of decisions in a group.”

Old theories, new understandings

Beginning their quest, the team embraced the “drift diffusion model,” a long-standing decision-making model in the field of psychology. They built on it and developed a scenario where groups of individuals (referred to as “agents”) had to choose between two alternatives – one correct, the other incorrect.

One of the fascinating aspects of this study is how algorithms and equations can seamlessly transition from one context and apply to another. 

“It really illustrates the power of math that the same equations can describe one phenomenon and then they can describe something completely different,” Lawley said. “The math doesn’t care. The equations don’t care. Seven days or seven apples. The number seven doesn’t care. And in this context, the math doesn’t care if you’re talking about animals searching for food or people making a decision.”

Decision-making practices

The insights gained from this research extend beyond theoretical mathematics and psychology; they offer practical implications for decision-making practices in various domains.

For instance, in business settings, these findings underscore the importance of fostering an environment where thorough deliberation is encouraged, rather than promoting rapid consensus. By recognizing the value of slower, more considered decision-making, organizations can mitigate the risks associated with cognitive biases that lead to suboptimal choices.

Furthermore, in contexts such as public policy or social justice, where decisions often have widespread consequences, striving for a balanced approach that prioritises evidence over impulse could enhance the overall quality of governance.

This research serves as a reminder that taking the time to weigh options and seek diverse perspectives can lead to more effective, reliable outcomes.

Decisions free from biases

It doesn’t matter if the decision is about which college to attend, what pizza topping to choose, or even something more complex. Lawley and his team’s model suggests that early decisions are often driven by agents with extreme predispositions, hence aligning with their inherent bias, regardless of the evidence quality.

In contrast, late decision-makers don’t let their initial bias rule. Instead, their decisions are a reflection of accumulated evidence, invariably leading to a more “correct” choice.

“Depending on what decision is being made, if there’s data to inform the parameters, now you have numbers that are going into this that tell you how biased these fast deciders may have been or how unbiased,” Linn said. “Our model is not just about deciding between two things. It can be any number of decisions, and we make very few assumptions.”

So next time you find yourself rushing to a decision, remember, slow and steady not only wins the race but also brings more accuracy and clarity in making decisions. And remember, mathematics isn’t just for the classroom; it’s intertwined with our everyday decision-making processes.

The study is published in the journal Physical Review E.

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