Artificial Intelligence is a computer program of a higher order and nothing else.

When I saw men fighting off a sinister takeover attempt by machines in Terminator 2- The Judgment Day, 25 years ago, I laughed it off, even though I enjoyed the thrill of the movie.

Man versus machine is probably the second best bogey after God versus Lucifer eternal battle.

Of course, we all want the man to win. We cant imagine ourselves serving some metal bodies, after all. But there may be some among us who are still wondering if the consequences of AI would eventually lead us there.

Recently, a senior manager in analytics in one my client companies, a very large business house indeed, was infatuated with the idea that AI can eventually take over human intelligence. That was surprising because he is not a teenager looking for cheap excitement or someone who does not know what analytics is about.

In fact, he has a pedigree of working for one of the largest analytics companies in the world before he joined my client company. Until now, I thought this idea is for Hollywood filmmakers who are short on creativity. But I think it is better to put this into right perspective as folks are churning enormous hype about AI, confusing everyone as usual.

AI means different things to different people. Some visualise machines working for their own purposes like in Terminator movies. Others imagine something like Watson that is so intelligent that it has solutions to all kinds of problems of mankind. Yet, to some data scientists, it means a piece of python code or a software package which they can run every day to earn a living.

But we can broadly divide AI into two streams: Generalised AI, which we call as Machine Learning (ML) and Applied AI, which focuses on replicating human behavior, such as making robots.

In either of the cases, it is a computer program of a higher order and nothing else!

Let me explain. In programming, we define what a program has to do. We then input data and get an output. We look at the output and if its not satisfactory enough, we go and correct the program. Now, what if, the program itself can look at the output and improve for itself? That is MLor generalised AI. But how does it do that?

Suppose you want to guess the next product a customer is going to buy on Amazon or anywhere else based on her activity until now. If you are a predictive modeler from econometric school, you would want to look at all historical data and find out the factors that determine a customers behavior and use that learning to predict what this customer would do now in the near future.

In reality, these factors can be anything. It can be demographic factors such as her age, marital status, location, education, or occupation. Or it can be the offers of competing products available at that point in time. Or let us say, even the weather influencing her buying behavior, or just that she is frustrated with the results of the American presidential elections. And, lets not forget the influence of her boyfriend on her buying moods?

As we can see, the possibilities are many. And if we consider further possibilities of all the interactions of these different factors among themselves, which means each factor having a partial influence by itself and a combined influence along with some other factors, then the combinations become unmanageable to human attention.

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Artificial Intelligence versus humans, who will win? - YourStory.com