Idris Khan has solved many real-world business problems for corporations by applying data Science and AI expertise.

He is particularly interested in AI in the HealthCare arena. In addition, he has published many research articles in this area.

INDIAai interviewed Idris to get his perspective on AI.

How did a mechanical engineer get interested in AI? How did it all begin?

I had a keen interest in subjects such as Operations Research, Maths, and Statistics in my engineering days, But primarily, we studied all theoretical concepts. I was glad and started searching for real-time use cases for these subjects. Then, I learned about how a criminal called Chota Rajan was arrested by face recognition and how google maps can give us an optimized path by using mathematics and concepts, which I am interested in. These use cases were fascinating, and I developed a keen interest in this domain. At that time, I only knew all these things as Data Analysis. After learning these topics, I learned more about the domain and eventually dug further for Data Science and Artificial Intelligence.

What initial challenges did you confront during the transition?

I needed a Senior who could guide me on where to go and what needed to be done, coming from a HomeTown with nearly no IT presence. It was challenging to find a mentor.

We have plenty of information and knowledge available right now online. But what things needed to be consumed was a significant problem. Data Science is an Ocean, you don't need to know everything, and Humanly, according to my knowledge, it's near to impossible for we can learn everything. 

Another significant challenge is learning programming languages. Coming from a non-IT background, we focus on learning the language instead of learning logic building. Once you know how to build the logic, languages won't be a barrier.

What is your role at Accenture as a data scientist?

For Accenture's internal project, we are Building a recommendation system for Accenture Data MarketPlace.( Place where you can sell or purchase data)

There's more client-side work going on, which according to policies, can't be publicly revealed.

Who is your inspiration in AI research, specifically Explainable AI?

Overall my inspiration in AI is Andrew NG. Specifically, in Explainable AI, it's not a single person, but organizations Accenture and IBM are doing great work in this domain.

Are programming skills required for professionals interested in a job in artificial intelligence?

Yes, you need to know the Python programming language.

What advances in explainable AI can we expect to see shortly?

Advances in Explainable AI we will see shortly:

We will have an explanation for whatever algorithm you use in AI/ML. We can know what factors have contributed to the output.

Once we know why AI is giving specific output, we can further correct AI.

What advice would you offer students and professionals interested in pursuing a career in artificial intelligence? 

For professionals and students:

• Start logic building with Python programming. (Python is a straightforward language, you can quickly learn python in a short time)
• Pay attention to the mathematical intuition behind algorithms, and try understanding how things work behind the curtain.
• You don't need to be a mathematical genius to be an AI Engineer, but you need to know the concepts.
• Practice on real-time data as much as you can, and build your strong portfolio of work on GitHub.

Can you recommend AI books and research articles for individuals starting in the field?

• Head-First Python: A Brain-Friendly Guide.
• Artificial Intelligence- Achyut Godbole.
• Artificial Intelligence- A Modern Approach.