An Interview with the Probability Man
Call it the wildest dream of Pascal, Leibnitz, Babbage or Lady Lovelace, or even an analytical engine that eats its own tail — computers are fascinating machines. These little electronic brains are believed to do anything and everything we know. But can they rise above just being performers and become creators? The idea of computers and machines in general having an intelligence of their own has been around for a long time. This psychology of intelligence in machines, commonly called artificial intelligence, is a captivating idea and has kindled curiosity in the minds of many. I am no exception and have always been intrigued by the term. The invitation of Dr. S.K. Pal, a computer scientist and Former Director of ISI (Indian Statistical Institute) as a guest lecturer for Pragyan ‘17 resulting in a chance to interview him was a dream come true.
All set for the deterministic encounter with a person who ruled the world of probability, there was a tinge of nervousness left in me. The man who had coined the term “machine intelligence” and mastered fuzzy logic came in with a heartwarming smile and the simplicity of a next door friend. I questioned him like a little child in awe and he answered with all the patience of the best of teachers.
Since he has encountered different audiences across the globe, I wanted to start off with his take on our college tech fest.
What are your expectations from Pragyan 2017?
I just landed in Trichy. I am really excited to talk before such a diverse audience. I hope to explore the fest a bit before I leave.
Being a man who has served in the field of education for more than a decade, his words on the current education system are invaluable. I was also curious to know about his work. He was a man of few words yet his passion was infectious.
Engineering colleges have become a hub to ideate in terms of career paths. Being a person with such diversity in your educational qualifications, how do you see the growing trend of switching alternative career?
In my time, engineering courses were rare to find. So I had to start with a pure science course. I always wanted to take the path less explored. So, when most of my classmates decided to pursue masters in physics, I decided to switch to pattern recognition. I believe in today’s scenario, students must take up a course in science along with engineering because science and technology go hand in hand.
What drove your interest in machine intelligence? What about this subject made you break records and write groundbreaking journals?
It was just my interest to explore the unexplored. I coined the term “machine intelligence” and so it was more like my interests paved way for a new field.
Being a person who has pursued education both in India and abroad, what difference do you feel in the learning scenarios?
I would say whatever I have learnt in the subject was from India, I travelled abroad majorly to teach. But I feel I learn equally from an Indian student, a Chinese student and an American student. The learning scenario is the same if you are interested to learn.
Given the fact your work has been cited more than 24000 times, which proves its credibility, can you explain to us in layman terms the crux of your work?
I never worked keeping in mind the citation index. My work has been cited largely because most of my work was on areas of science which were in their incubatory stages. My research was majorly to create intelligent machines which make better logical decisions. We do this with the help of mathematics, probability theory and fuzzy logic in particular.
Can you elaborate on ISI a little and the opportunities available for engineering students?
Indian Statistical Institute was majorly a pure science institute earlier. But we have now introduced computer science courses. For engineering undergraduates we offer M.Tech courses in computer science.
Being a science person, I knew his views on the recent discoveries would be worth hearing. Also working with statistics, probability and nature of intelligence, I wondered if he looks at the world the same way we do.
Dealing with probabilistic decision making for major part of your life, does it influence your decision making skills in everyday life?
(Laughs) It does not. I prefer taking hard decisions in life. If I had to use a lot of my analytics, I would have a tough time dealing with people. I don’t believe in 0 or 1 decisions in life either. When you are young, it feels right making binary decisions, but with age it does tend to change.
Being both physics and a computer person, what is your take on quantum computing?
I cannot comment much on the subject because I have not intensively worked on the subject. I feel it is still limited to the physicists and will take some time for the engineers and technologists to try their hand at it.
It seemed like I had just started, but the interview had come to a close. I was not sure if the time dilation that happened during the course of the interview was because of relativity. I would attribute it to the simple and inspiring nature of the person I was sitting with. He was a master of his subject. He could compose scientific pieces of any degree of complexity. But what made him stand apart was that he had weaved a beautiful story for a kid with curiosity from the complex web of subjects. And that made Pragyan ‘17 an experience for a lifetime!
