Intuition vs data: Making the right decisions
Intuition by definition means something that you feel is the right thing to say/do but you cannot specify the logic behind that. The importance of intuition is widely acknowledged and many leaders and business executives underline the need for intuition is their line of business. Even further, in some cases people quite openly share, when asked how they have come to a certain conclusion or why they acted in a certain way, that they’ve trusted to their intuition.
People are often very happy to admit they have relied on these gut feelings for major decisions, being unable to point to any specific logic or evidence that has guided them. I've always been quite intrigued by this, since there is something about human nature that's profoundly contradictory here - why do we trust our feelings when it comes down to making hard business decisions?
The value of intuition
This is something that seems to be hard-wired into how we as humans think. In his book 'How We Decide', Jonah Lehrer explains how the orbitofrontal cortex is responsible for integrating the visceral emotions into the decision making process; it connects the feelings generated by the more primitive parts of the brains to our conscious thought.
This analysis take place outside of our conscious awareness and it is the orbitofrontal cortex that connects that result in a timely manner as emotions to our behaviour/operations.
You can see this in action, for example, in the extremely quick decision making processes of top athletes. In the heat of a game, they have to evaluate different types of alternative game plans in less than split tenths of seconds. However, it can also lead to poor decision-making when our subconscious fears and biases take part in the decision making process.
Building on the human brain
Building up good intuition is expensive, and it can take years to gain the necessary experience. So wouldn't it be beneficial to have computers do that for you?
In some sense, today's deep neural networks and machine learning work in the same way as our unconscious brain. They can categorise and find connections between things that our logical mind would find; and often do this even faster. Of course, there are some differences. For instance, the use of human experience and knowledge in decision making does not scale in the same way that machine learning algorithms do.
I think it's fair to say that robotic decision making won't replace the need for the human touch in the process for a very long time, if ever, and there's still a lot we need to learn from intuition before we can mimic human thought processes with computers.
Having said that, there is already a lot what we can do with the current understanding, and artificial intelligence and making learning techniques are getting better all the time.
Relying on your gut is not necessarily a bad thing. But if you can support or even prove that with real evidence derived from advanced data analytics, you can have even greater confidence that you're on the right path.
Read about the value of data www.tieto.com/data-driven and more thoughts about how machine learning and robotics could help in decision making.