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Is AI Really the Future? Dr. Partha Mohanram’s Bold Insights on the Promise and Perils

Dr. Partha Mohanram, John H. Watson Chair in Value Investing at the University of Toronto, explored AI’s transformative potential, the ethical dilemmas it presents, and its impact on industries like finance, healthcare, and education.

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Aanchal Ghatak
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Partha Mohanram, John H. Watson Chair in Value Investing at the University of Toronto

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Artificial Intelligence is evolving at a pace that has never been seen before, changing industries, societies, and economies. As AI continues to advance, its capabilities expand from predictive models to more complex judgment-based systems.

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In an exclusive interview, one of the very few experts to have experience from AI to its implementation in various segments, Dr. Partha Sarathy Mohanram, John H. Watson Chair in Value Investing at the University of Toronto, enlightens us with his views regarding the limitations within the current model of AI, his views on making India an AI leader, considerations of ethics surrounding AI usage, and the profound impact made by AI across industries such as finance, healthcare, and education.

During the inaugural Dr. Bala V. Balachandran Memorial Lecture, Dr. Partha shared his insights on the transformative potential and inherent challenges of artificial intelligence in today’s business landscape. The event, organized by Great Lakes Chennai in collaboration with the Madras Management Association, attracted 150 senior professionals from various corporate sectors.

The Limitations of AI Models: A Critical Look at Growth vs. Judgment

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While Dr. Mohanram acknowledges that AI is improving exponentially, particularly with the leap from GPT-3 to GPT-4, he raises an important point. 

“The key question is whether this growth will enhance AI’s predictive capabilities or its judgment abilities. Technically, AI is advancing at a rapid pace. But from a broader perspective, the real focus should be on how AI intersects with management and decision-making, not just on the technical improvements,” he says.

As AI evolves, its applications in business and governance grow. Yet, there remain critical limitations. Current models often struggle with tasks requiring high-level reasoning, ethics, or complex decision-making—areas where human oversight is still vital. AI research is increasingly focusing on making models more adaptable to these real-world complexities.

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According to Dr. Mohanram, much of the progress being made in AI focuses on enhancing its technical side but remains a challenge in real-world decision-making. 

This theme is one that underlines the infusion of AI with management and decision-making, not just the technicalities, amidst growing concerns about how AI will get meshed into more human-centered processes.

AI and Productivity: The Paradox of Longer Hours

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The most debated aspect of AI is its tendency to increase productivity. Here lies the paradox; if AI is meant to make tasks more efficient, then why is it that employees are seeming to work longer hours?

According to Dr. Mohanram, this paradox stems from not AI itself but rather from how it's implemented by companies. While AI is meant to make work smarter and more efficient, it is very often misused in ways that increase pressure on workers. 

In response to the paradox of increased work hours despite AI’s promise of productivity boosts, Dr. Mohanram offers a sharp critique. “The situation where employees are working 84-hour weeks seems more about creating soundbites than fostering real productivity. The promise of AI should be to make work more efficient, not to increase work hours. Long hours don’t necessarily equate to productivity,” he explains.

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For instance, industries like investment banking require long hours that do little to enhance productivity but are more about appearing busy. Ideally, AI should reduce this need for long work hours by automating the repetitive tasks and providing better decision-making tools that enable employees to focus on higher-value activities.

"Long hours don't necessarily equate to productivity," he asserts. "AI should help people work smarter, not longer, ideally making us better versions of ourselves." He believes AI should be that tool for individual and organizational efficiency, so a person can have more productivity on the job at normal working hours.

India's AI Potential: Moving Beyond the Tech Boom

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India is considered a technology player in the world, but majorly, that is through the IT outsourcing business. For AI, Dr. Mohanram remains cautious on its assessment. In India, despite having one of the biggest and most developed markets, where there is the ability to create massive benefits, such as health care and education sectors, it cannot be forecasted that India would be at the forefront globally, for the time being.

"I don't see India leading AI on a global scale yet," he explains, sighted the dominance of other countries like the US, China, and Europe in AI research and development. "India's tech boom has essentially been cost-driven, providing cheaper alternatives for tech development. But in AI, India needs to focus on producing high-quality research and develop a robust AI ecosystem to compete globally."

Dr. Mohanram has emphasized the fact that AI could address some of the most pressing challenges in India's resource-constrained sectors. For example, AI-enabled education tools could bridge the teacher shortage in rural areas and drastically improve the quality of education.

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Similarly, AI applications in healthcare could offer personalized treatments, optimize resource allocation, and improve access to healthcare services in underserved regions.

The Government's Role: Fostering the Right Ecosystem

While private-sector players like OpenAI and Google are at the forefront of AI advancements, Dr. Mohanram emphasizes the importance of government involvement in creating the right ecosystem for AI innovation.

Drawing parallels to the early days of the internet, which was nurtured through government-funded initiatives in the U.S., he advocates for a similar approach in India. He warns, however, that this is where the real breakthroughs will come, from the private sector, to drive adoption and application.

The government of India needs to make the right infrastructure available for AI growth in terms of AI research and development funding, public-private partnership tools, and appropriate regulatory frameworks with innovation encouraging, not inhibiting progress, Dr. Mohanram suggests.

Drawing Lessons from the IT Revolution

India's IT revolution in the 1990s holds lessons for AI development. According to Dr. Mohanram, India needs to replicate the robust tech ecosystem that was established during that period, with a focus on research and innovation. The country's top institutes, such as the Indian Institutes of Technology (IITs), must produce world-class AI research, while domestic players should be encouraged to create AI solutions tailored to India's unique challenges.

The IT revolution taught us the importance of having a strong tech ecosystem," says Dr. Mohanram. "We now need to apply those lessons to AI, ensuring that our research infrastructure is equipped to produce breakthroughs in AI that can address local problems."

The Ethics of AI: Balancing Innovation and Responsibility

Ethical issues have been brought to the forefront as AI becomes more integrated into business and society. A company must always strive toward a perfect balance between innovation and its social responsibility. Boosting efficiency and, thus profitability can be a booster with AI, but the decimation of human workers would eventually prove a disaster, not just for the company but also for society as a whole if AI does not work as expected.

"Companies that aggressively replace workers with AI may face long-term consequences," he cautions. "AI should not be about removing jobs but about enriching human capabilities. The ideal way is to upskill employees to work alongside AI rather than replacing them."

Impact of AI on Finance Market: Efficiency vs. Risk

In the financial sector, AI has already begun making waves. It is being applied in everything from earnings forecasting to stock prediction as a tool for improving decision-making and optimizing portfolios. But just as any revolutionary technology, the growth of AI poses new risks - especially in the financial markets. The ability of AI to recognize market inefficiencies may make markets more efficient; however, flawed data it depends on could instead increase volatility.

The risk could be that the efficiency of AI could be inhibited if the data used for training AI models isn't correct," says Dr Mohanram. "Just as algorithmic trading can disrupt, AI would simply amplify similar risks if the models aren't well-calibrated.

The Road Ahead: Identifying the Winners in the AI Race

The companies that will make real money off of AI, he believes, are those which realize the benefit of AI far beyond short-term profits. Businesses which focus AI for efficiency improvements, employee empowerment, and longer-term growth and development will find their way into leadership positions; the businesses following the AI craze without strategic use or meaningful applications will be laggards.

"AI is not about just improving stock prices," he says. "It's about how AI can drive real changes-be it productivity, engagement, or innovation. Companies that approach AI in a thoughtful way will be leaders in it."

The Human Factor of AI

Dr. Mohanram has a deep affinity for AI, which goes beyond his professional life. In the lecture, he shared a beautiful personal anecdote about his long-standing friendship and collaboration with the late Professor Bala, who had shaped his perspective on AI. The humility, generosity, and dedication of Professor Bala continue to inspire Dr. Mohanram as he navigates the AI landscape.

Reflecting on his own journey, he traces his interest in AI back to his B.Tech in computer science from IIT Madras, where he first worked on neural networks for speech recognition. Though his career took him into the realm of finance and valuation, AI remained a constant area of interest.

Over the years, he has incorporated AI and machine learning into his research, exploring their applications in earnings forecasting and investor sentiment analysis.

As AI continues to reshape industries and societies, Dr. Mohanram’s insights highlight both the immense potential and the inherent risks of this transformative technology. While the road ahead may be uncertain, one thing is clear: AI’s impact on business, society, and the economy will be profound—and its future will be shaped by careful, responsible innovation.

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