Our next speaker in the Know Thy Speaker series is Dr. Vikas Agrawal
Vikas will deliver a talk titled – Bring in the Lawyers: Explainable AI Driven Decision-making for the Enterprise
What got you into Data Science/AI?
Since my childhood, I have been fascinated by Tycho Brahe’s coming up with the laws of planetary motion from Johannes Kepler’s data, and then Isaac Newton’s using those laws to discover the inverse squared relationship of gravitational force with distance. It seemed natural to me to investigate why or how things work the way they work. As I worked on various rich subjects like cursive handwriting recognition, multi-agent systems, modeling disease and growth signaling systems in computational biology, semiconductor reliability, smart speech-enabled agents for insurance, banking and healthcare, and solving problems in HCM, CRM, SCM, MFG and ERP areas using the scientific method, I understood the a common theme of modeling and understanding the real world, which is the core of data science. My foray into AI began as early as undergraduate research in computer vision at IIT Delhi, creating assistive systems for children with cerebral palsy at the Applied Science and Engineering Labs for the Alfred I DuPont Hospital for Children, and then with Dr. Lokendra Shastri creating activity context-aware systems.
What is most exciting for you in Data Science/AI?
Explaining the predictions of AI systems is a very interesting area for me as it helps us directly influence decision-making in any enterprise. I investigate behavioral psychology of decision-making and how to best present insights and recommendations for action in such a way to invoke a gut-feeling sense of why a decision is needed, and what would it cost or what are the implication of making the decision one way or the other.
What do you think is the biggest challenge faced by Data Scientist today?
The largest challenge for a data scientist in the enterprise is getting disparate sources of relevant data together with all the permissions, keeping algorithmically reproducible provenance of all data so that no one doubts it, and guiding the data engineering teams for scalability and deployment.
What do you think is the biggest obstacle for Data Science/AI adoption?
The biggest obstacle is the lack of actionable insights or rather a series of “sure to work” actions provided by the data scientists. Where such directly actionable intelligence is made available, the next obstacle tends to be willingness to change business processes to be data driven, willingness for businesses to be genuinely process driven as people genuinely worry what might go wrong.
Which is your favorite session at ODSC India that you looking forward to attend?
Tarry Singh‘s Deep Learning workshop promises to be very interesting as he will bring all the current research while describing the fundamentals.
You are traveling from Hyderabad to Bangalore. What got you interested to present at this conference?
The opportunity to meet great people and learn from them at the conference made me interested when the organizing committee reached out.
Any personal message/remarks you want to share with the DS/AI community in India?
ODSC is a great opportunity to learn. Let us Learn, Learn, Learn.