I read a fascinating story the other day. A US AI model, initially designed to assist judges, developed a tendency to treat black offenders unfairly.

The machine did its job; modelling the behaviour of past judges. But there’s something no one saw coming.

The model recreated the judges’ blind spots in decision making, too.

Do you sometimes catch yourself going down a rabbit hole because you can’t focus better or can’t broaden your perspective? A blind spot can give you the illusion of having explored the whole issue, but you completely miss the point.

You can avoid blind spots in decision making easily. The answer is collaboration.

 

Understanding cognitive bias

 

Before getting into how to prevent blind spots in decision making, it’s important to understand how we create cognitive bias.

The most common ones are:

  • Confirmation bias, where you filter out everything that is not consistent with your beliefs
  • Unconscious bias, where our brains make quick judgements and assessments of people and situations without us paying attention
  • Confidence bias, where you assume your judgement is better or more reliable than it objectively is
  • Conformity bias, where you behave similarly to the others in a group, even if doing so goes against your own judgement

 

Most common types of cognitive bias

 

Blind spots in decision making come from your behaviour

 

After reading it, I told the AI story to a few data analysts I know. I wanted to understand what behaviours could isolate them from clear insights.

“What do you do to avoid blind spots in decision making?”, I asked.

This what they told me.

 

1. Ignoring creativity when you explore your dataset

 

Deep thinking requires an element of creativity. Are you really coming up with different ways to explore something?

 

 

When you focus too much on the measurable, you’re not doing much more than revisiting the past. If data gives substance to your ideas, only your conceptual thinking can draw new connections.

 

Thinking is difficult. That's why most people judge. - Carl Jung

 

2. Relying on opinions, not facts

 

Our brains love to make shortcuts on the basis of our past experiences. When you examine data and think you’re smart by re-applying some well-known conclusions, pause.

Are you just letting your opinions take over? Did you really have your ideas and assumptions challenged? What is the new element you can draw out of this?

 

 

 


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3. Looking for the right answer, not the right process

 

One of the analysts explained it simply: “When you think you’re right, you cut yourself from the possibility of improvement.” If you develop a growth mindset and admit you can always do better, then look for effectiveness.

Can you come to the same conclusion quicker? Then, how can you use that additional time to push your analysis deeper?

If data gives substance to your ideas, only your conceptual thinking can draw new connections. Click To Tweet

 

4. Disregard impact on others

 

We rarely do analysis for the sake of it. We’re always seeking an outcome, and therefore an impact on others (team, client, investor…). Who are these people? Can you relate to them? What might their view of the world be? What do they value? What do they want? How do they communicate?

Related: How to be authentic in times of change

These might seem trivial questions. But the art of a good piece of insight is to make it relateable. There will be always someone using the outcomes of your analysis, in reality.

 

Collaboration can kill your blind spots in decision making

 

The story of the biased AI didn’t surprise my data friends.

“Typical”, they told me. “For now, machines have limited creative thinking.”

Good insight relies on the ability to work with different lenses to challenge assumptions. To avoid blind spots in decision making, you need to accept feedback from a trusted set of partners.

Even though navigating data might not ring your creative bells immediately, that’s exactly where your human value resides. And by human value, I mean harnessing the power of collaboration to go beyond the obvious.

 

 

Have you tried to work with diverse minds? Do you know someone who has a different perspective and might add a new idea? Does your team regularly challenge the “how we do it”, so that you can come with a different path that will expose gaps in your logical thinking?

Be open to constructive criticism. Accept others’ priorities. They drive a different focus, and work at eliminating the bias you could create for yourself.

 

Even a good leader can make bad decisions. It takes courage to admit that the best way to avoid blind spots in decision making is to expose your ideas to the risk of tough feedback.

Always remember that an extra pair of eyes is likely to spot what you couldn’t see in the first place.

The depth of your conclusions will be determined by the quality of your collaboration. Not all team members will experience the same story, even with a similar dataset. Not everyone will respond to challenge in the same way.

And that’s exactly why a group is so powerful.

How do you overcome bias? Tell us in the comments below!

 

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