Human Intuitions And Machine Learning

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Rana Muhammad Usman

Alan Turing was the first one to present the idea of simulating the machine thinking. Its been more than 60 years since the ground breaking paper of Alan Turing came out, The Imitation Game. The world has changed rapidly since then.

The machines of today have become so powerful.
They can actually think, which endorses the idea of Alan Turing presented in 50s. However, the machine thinking may be different. Alan Turing argued, just because the thinking can be defined differently for different objects, does it mean it is not thinking at all.

Turing test is still the best out to stress test machines and hardware on all levels. We have support vector machines, we have decision trees that quickly sums up any problem in human readable hierarchy. We have Artificial Neural Networks based on human brain neuron structure.

The rapid growth of Machine Learning and its application in real world has already taken its toll. Hospitals are using Machine Learning to cross check if the patient needs a specialist advise. Banks are using machine learning to know if the person will return the loan or not. Education sector will soon foresight the future of student at the entry tests.

This argument is no different from saying, they are actually foresighting future but with margin of error. The precision and accuracy of predictive models are definitely not concrete. They can change for different circumstances, but the question is, how positively can we rely on machine learning outcomes.

The need of human experts will always remain there because a computer can generate data, follow an assigned path but it cannot have the decisive powers. The decisive powers would always remain with humans who have back in time actually invented the computer and hence the technologies which emerged out of it.

The biggest difference between a human mind and a machine brain is that Humans have intuitions. Humans may tend to decide on the basis of their intuitions. Intuitions develop over the span of years of experience, mistakes and bad decisions. Machine Learning algorithms may have neural networks based on the human brain neuron structure, but they still cannot embed the power of intuition.

The humans were powerful and would remain powerful but the addition of emerging technologies have eased their work and slowed their thought process. Perhaps, not far away is the time when Machines would be ruling the world.

Author Bio:
Usman is an aspiring data scientist who is exploring depth of Machine Learning and Analytics.
He tweets @rana_usman

Image source: techcrunch.com

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