Decisions: Best left to Machines?

Let’s be honest. We do think we have become more intelligent. We are used to making more decisions, bigger decisions in a fraction of time. This is all due to the constant inflow of real-time data and wizardly data scientists doing their magic to come up with directions, insights that cut our decision-making time.

We have entered the fast-food age of decision making. It’s great; no doubt but are we sacrificing a bigger skillset as we get more and more comfortable in the machine-driven decision making infrastructure?

Don’t get me wrong; we NEED this data-backed, decision-making infrastructure. But it need not come by sacrificing some of the unique skillsets critical to our evolution. Let me list down a few to see if I can get some thoughts running for you.

1. Powers of observation: Do we actually sit down and take in what’s happening around us? Do we consume behaviours, patterns & conversations without the need to take immediate action? Are we absorbing information by just observing and making sense of seemingly unrelated, dissimilar occurrences? For Eg. – Is the race for nanochips the main reason why the USA sent its aircraft carriers in the South China Sea recently? The moot point is; are we letting the power of our cognitive abilities decay because we are letting the machines make the decisions for us? The human mind is a wondrous thing with cognitive powers that we don’t realize. Observation and the ability to put two and two together is a skill we can hardly afford to lose.
2. Critical thinking: Belief Bias+Confirmation Bias of Behavioural economics says that we tend to believe more in answers that are in-line with our beliefs. But are your beliefs watertight, Six Sigma godly level? No. So why do we not go out and consciously lookout for instances that contradict our pre-set beliefs? Because another theory of (Automation Bias) of Behavioural Economics tells us that we are excessively dependent on automated systems which can lead to erroneous automated information overriding correct decisions. We aren’t looking at the other side of the story. We want data to second our version of the truth and don’t want to seek the other side, which might be right but doesn’t match with your way of thinking. Do we consciously make an effort to seek out people, reports, theories that contradict out beliefs? No. And that’s what critical thinking allows you to do. To get more pictures of the story so that you make your decisions basis a comprehensive picture and not on your version of the picture. Think about the 5 blind men and the Elephant story and this will become clearer. Do talk to others even if you don’t agree with them. Do read content that has a contrarian POV to yours. Only then will we be able to make better decisions via critical thinking.
3. Being more open-minded about being proven wrong: I am as guilty as anyone reading of this. We are afraid. We are afraid of being shown up for our lack of results. We are afraid of making a big blunder and being responsible for it. That fear makes us stick to the tried & tested; put all your faith in econometric models and data and not have enough faith in ourselves to take the right decision. Conservatism or Belief Revision talks to be the tendency to revise one's belief insufficiently when presented with new evidence. Unfortunately, we don’t let new evidence come in our decision making infrastructure since we are the ones who control the input variables for the data engines. The data engine needs to have the full set of variables that can impact your decision making; even at the cost of being afraid. Only by doing that will we make the data engines more comprehensive, more human.

If this article reads as if I am against data-backed decision making, econometric models, etc. then I have failed in my objective. I am a big believer in the power of data but an equal big supporter of the three things listed above. We need to give ourselves more time (Observation), be open to hearing other person’s POV (Critical thinking), and not being afraid of being proven wrong (Alternative datasets) to make more right decisions than wrong. Data is everywhere today and so are the techniques but they are common for every decision-maker. A great practitioner of data for decision making will have an edge versus the average one. The person with higher powers of observation, critical thinking will be heads & shoulders above everyone. That is the differentiator that we need to adopt. We are unfortunately sacrificing all that at the altar of machine-led decision making for it reduces our cognitive load and gives a fig leaf to hide behind. But all of us know while fast-food is fun to eat, a slow-cooked meal gives more nutrition and stays with us for longer. :)