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Artificial Intelligence a term that is ubiquitous in this day and age. But what exactly is AI? If you have acquired your knowledge about AI from fictitious books and movies, then you are bound to be apprehensive whenever a new robot comes to fruition.

According to the founding father of AI, John McCarthy, AI will attempt to equip machines to stimulate tasks that can only be accomplished with the help of Human Intelligence. In other words, AI is a machine or a computer program that learns how to do tasks that require forms of intelligence and are usually done by humans.

The original 7 aspects of AI framed during 1956 Dartmouth Summer Research Project on Artificial Intelligence were:

  1. Simulating higher functions of the human brain.
  2. Programming a computer to use general language.
  3. Arranging hypothetical neurons in a manner so that they can form concepts
  4. A way to determine and measure problem complexity
  5. Self-improvement.
  6. Abstraction: Defined as the quality of dealing with ideas rather than events.
  7. Randomness and creativity.

Since the inception of AI, we have been successful in achieving the first four aspects and in pursuit of randomness and creativity induced by AI we have for the past couple of years, witnessed feature film co-written or completely written by AI and as a result,  the script didn’t make any sense to human comprehension.  The output of a machine is a result of it’s learning about the nuances of human idiosyncrasies. There is no reason for AIs to have self-preservation instincts, jealousy,etc. But we can build into them characteristics such as altruism that will make them pleasant for humans to interact with them.

The two aspects of artificial intelligence are Machine Learning and Deep Learning. The major difference between us humans and the machine is that we learn from experiences but machines follow instructions. Yet the answer to the question, whether computers can learn from experience is machine learning. The machine becomes adept to learn from past data. A simple example to understand the application of machine learning is our email management system and algorithm used to differentiate between spam and non-spam emails. The data and algorithms pertinent to the task that we feed into the machine, help it to learn the task at hand. This aforementioned approach, we can establish an expert system that emulates the decision-making ability of a human expert and the advantage of such systems is this works on if-then rules rather than through conventional procedural code. Deep Learning is a facet of machine learning concerned with algorithms logical emanating from the function of the human brain also known as the artificial neural networks.

Artificial Intelligence in practice

AI is being used to identify and address socially relevant problems such as homelessness. At Stanford researchers are using AI to study satellite images to identify the geographical regions with the highest poverty levels.

In the aviation industry, AI has its application in the allocation of gates while landing of planes and deterministic ticket pricing.

Robots are adept to even teach humans as in the case of ITS (Intelligent Tutorial Systems). An ITS by the Sherlock teaches air force technicians to diagnose electrical problems in aircraft.

As far as the healthcare industry is concerned, there are companion robots for the elderly, mining medical records to provide information and design treatment plans, assist in repetitive tasks including medication management and using, avatars in place of patients for clinical training.

In heavy industries, robots are assigned tasks that are either very dangerous to humans or repetitive in nature. Robots are imperative whenever precision, is in consideration

In the field of finance, AI can help us make algorithmic trading and help us make investment decisions on a reduced level of risk. Portfolio management can be done with the help of artificial intelligence and as a result, improve its efficiency.

Some of the recent advances in the field of AI have been helping human beings in our day to day life. Every year, nearly 1.3 million people lose their lives due to road accidents caused due to human negligence and the panacea to this could be a self-driven car.

Is AI ominous for employment?

In an interview couple of years ago the former president of the USA, Mr.Barack Obama said:

”One of the promising aspects of AI is that in playing chess a computer with a human often times can do better than just the computer and think of this application broadly to different disciplines. What we want to be able to do is develop systems that are open enough, transparent enough that human judgement , imagination and creativity are still intruding but a lot of the routine stuff has to be taken over by machines”

For the humanity to be successful in AI we have to think through the economic implications because most people aren’t worried about the singularity, but instead, they are worrying whether they are going to lose their jobs to machines. Let’s see, on the positive side of things and consider that historically humans have been able to absorb new technologies and have found that new jobs have been created and we migrate in search of better opportunities and our standard of living tends to improve.

We might find ourselves in a different situation this time because of the pervasive applicability of AI and other technologies. On the flip side, low wage earners become redundant as their jobs may not be replaced but their wages are suppressed.

The good thing is that fully incorporating AI into our lives is not going to happen overnight. It is a gradual process taking place over the next two to three decades. The societal conversation that the decision makers and governments across the world need to have is on how it could have inclusive growth propelled by technological advancements. AI will definitely bestow upon us an opportunity for pursuing high skilled jobs in the near future. The question though, will we be equipped to grasp those opportunities?

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