Events 
NCAER hosted a lecture, “Thriving with Human-Centred AI” by Ravi Bapna, Curtis L. Carlson Chair Professor in Business Analytics and Information Systems at the Carlson School of Management, University of Minnesota, where he also serves as the Academic Director of the Analytics for Good Institute and the Carlson Analytics Lab (CAL)
The lecture explored how organisations and individuals can harness human-centred Artificial Intelligence (AI) to drive innovation, enhance productivity, and create sustainable value. In his welcome remarks, Mr Suresh Goyal, Director General, NCAER, said that with his extensive expertise in analytics, AI, and Machine Learning (ML), digital transformation, and economics of information systems, Professor Bapna is likely to play a vital role in coordinating research on AI and DPI at NCAER.
The lecture covered various key themes, perspectives, and frameworks associated with the use of AI, including AI dystopia; use of AI in dealing with challenges related to data overload and analysis; foundations for data engineering; the role of AI in powering descriptive, predictive, causal, and prescriptive outcomes; and, the performance of AI in generating and curating information vis-à-vis human resources.
Professor Bapna explained that generative AI is only one subset of a broader AI ecosystem, which also includes traditional machine learning approaches widely used for predictive tasks such as fraud detection and disease prediction. In practice, much of the work in AI projects involves data engineering, including collecting, cleaning, and integrating data, which can account for 60–70 per cent of the effort in building AI systems.
Professor Bapna also discussed the possibilities of use of deep learning AI, reinforcement learning, interaction of Large Language Models (LLMs) with proprietary organisational data and software tools through Application Programming Interfaces (APIs), and training AI to counteract biases inherent in human decision-making. Some of the research questions that the lecture highlighted were:
- Can an agentic-AI based virtual data scientist help MBAs develop stronger analytics capabilities?
- Is there heterogeneity in the usage of agentic-AI across key student characteristics?
- What are the specific mechanisms that link agentic-AI usage with learning outcomes?
The lecture also addressed broader policy and societal issues, including the potential for bias, regulation, and unequal access to AI technologies.
Professor Bapna highlighted the importance of DPI and data ecosystems, particularly in a country like India, where large-scale digital platforms generate valuable data that can be leveraged for research and policy insights. He delineated the limitations of AI, such as its probabilistic tendency, and potential for producing hallucinations or generating inaccurate or insufficient information, which necessitates validation and responsible usage of AI. The breakthrough behind tools like ChatGPT is not just the model architecture, but the large-scale human effort needed to fine-tune these models and add guardrails.
Finally, Professor Bapna emphasised the significance of lifelong learning and responsible governance to optimise the benefits of AI for society. Like any technology, AI carries risks, but its impact ultimately depends on how humans design, govern, and deploy it. “Rather than replacing humans, the real promise of AI lies in augmenting human capabilities. We need to orchestrate and conduct human-AI symphonies to solve grand challenges and make the world a better place”, he noted.
In conclusion, Dr Anil Sharma, Secretary and Operations Director, NCAER, while thanking Professor Bapna for his incisive lecture, suggested the need for continually assessing the role of AI in enhancing human productivity and efficiency, and how AI can help produce solutions for a large number of social problems and glaring questions through better research and policies.