How to Eliminate Your Own Unconscious Political Bias

How to cast an unbiased, well-thought-out vote is difficult. Politics brings out the worst in all of us. Unfortunately, the worst is often unconscious. In this episode, Stever Robbins shares one way to combat some of that unconcious bias.

Stever Robbins
5-minute read
Episode #428

It’s election time! Suddenly, all our friends are experts in foreign policy, environmental regulation, economics, and all kinds of other things they never talk about except in election years. If only they realized how ignorant, irrational, and hideously unqualified to vote they all sounded. Not like us, of course. We’re completely educated on all the issues, rational, and gloriously qualified to vote. That’s why it’s good to be us!

Sadly, though, we are human. So we still have unconscious bias that can destroy our good decisions. Our brains sometimes feel certain about an issue, even when there’s no actual basis for the certainty. I was eating Szechuan Chicken once was absolutely certain that cute little red pepper would be super-easy to eat. And it was. If by “super-easy” you mean "strapped to a gurney screaming while being shuttled to the emergency room for an emergency tongue transplant.” 

We have built-in biases that blind us to even the most obvious disasters right in front of our noses. Just take one look at 1970's fashion: flowery, embroidered bell bottoms worn with fringed leather vests. It took us years to truly realize the horror of what we’d done.

Biases Can Be Bad

Biases matter because they distort our world view. Our world view determines our actions and our actions determine the results we get. If we act on bias instead of reality, we get worse results. 

Your boss gives you a hard assignment. If you believe your boss hates you, you think, “they’re torturing me!” and you quit. Oops! It turns out your boss gave you a hard assignment because you’re up for promotion to Lesser Grand Poobah. This assignment would prove your worth to the Council of Poobahs. If you had known the truth, rather than your false belief, you might be lounging around the Lesser Grand Poohbah Den at this very moment.

Your Rants Reveal Your Biases

When electing someone to run a gigantic country, you’ll get the best outcome by choosing a candidate wisely. Sadly, when politics are involved, our rational brain takes a holiday, and our hysterical screeching monkey brain takes over. This happens to me, too. This year, however, I developed an anti-bias exercise to help. 

One bias is that whatever we’re hearing about is what we think is important. When we hear about candidate A, we keep abreast of one set of topics. With candidate B, another set of topics rises up. We end up not evaluating the candidates equally.

You Can Compare Apples and Oranges

Bernice is shopping for fruit trees to offer for sale at her plant store, Green Growing Things. As she walks past apples, she thinks, “That looks just like the apple from Sleeping Beauty! And there’s one that’s perfect for archery practice!” Pretty soon, she’s sure she wants to branch out into apples!

Until she sees the oranges. They’re such a beautiful color. So beautiful, in fact, that someone should name a color after them! But sadly, there aren’t any magical uses for a Valencia orange. (That she knows of. Bwah hah hah hah hah!!)

Which should she choose? Apples seem to be the winner, since they’re good for magic and archery. Oranges, though, win on color. She’s using different criteria to judge the different options. If you weren’t a super-smart, deep thinker like me, you might be tempted to conclude you can’t compare apples and oranges.

But you’d be wrong. We’re so awesome, we can compare apples and oranges—and thus make a better decision than we would otherwise. 


About the Author

Stever Robbins

Stever Robbins was the host of the podcast Get-it-Done Guy from 2007 to 2019. He is a graduate of W. Edward Deming’s Total Quality Management training program and a Certified Master Trainer Elite of NLP. He holds an MBA from the Harvard Business School and a BS in Computer Sciences from MIT.