3 Problem-solving Strategies You can Learn from AI

The methods used by humans and AI to solve problems are not the same.

An AI may fail a thousand times in an hour and it means nothing.

Each failure is neutral data that brings it closer to the solution.

A person might fail one time in an hour and be devastated.

That failure increases doubt which moves them away from the solution.

What can we learn from AI’s problem solving strategies?

1. Results are neutral data that indicate what to do next.

2. Lack of data is worse than failure. Take rapid action.

3. Every result is valuable. Doubt is a waste of time.

If you get a result you don’t want (like a proposal you didn’t win, a piece of code that doesn’t work, a new hire that quits) it doesn’t have to mean something is wrong with you.

It’s up to you how you interpret the data.

If you make it mean something’s wrong, you’ll probably end up feeling bad, which will reduce the effectiveness of what you do next.

This creates a downward spiral leading to more results you don’t want.

Instead, decide to see all results as priceless data about what to do next. Be willing to take more action to get additional data.

Results don’t define your worth as a person.

Measure your self worth by your willingness to learn and grow.

Let results guide you and drive you forward, regardless of whether they are positive or negative.

It’s one of the most valuable lessons we can learn from AI’s problem solving approach.

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