In a recent Masterclass on AI Risk Management, co-hosted by CNBC-TV18 and ICICI Lombard, a striking revelation came to light: only a couple of people in the audience expressed confidence in entrusting a robot to perform surgery. This strikingly low figure underscores the deeply ingrained skepticism of the average Indian when it comes to embracing cutting-edge technology. Despite artificial intelligence weaving itself seamlessly into many aspects of our daily lives—from personalized recommendations to fraud detection—uncertainty and doubt persist. This cautious mindset, however, is not unprecedented. A similar sentiment was palpable in the 1990s when computers were first introduced in India, evoking fear and resistance. Yet today, India stands tall as a global IT powerhouse—a testament to how initial apprehension can evolve into exceptional mastery, innovation, and leadership.
Risk, as the adage goes, is the price of progress. History has consistently shown that the greatest rewards often come from meeting the toughest challenges head-on. While success may not always impart profound lessons, failure is an unyielding teacher. In the digital age, risk is no longer an option—it is an ever-present reality, an unavoidable cost of participation in our interconnected world. The pertinent question is not “Who is exposed to risk?” but rather, “For how long can one remain shielded from it?” Unlike earlier times when risks were primarily localized and tangible, today’s challenges are global, intangible, and deeply interconnected. They are driven by evolving geopolitical dynamics and manifest as supply chain disruptions, climate crises, cyber threats, and vulnerabilities in IT security. This paradigm shift calls for a proactive approach to risk management. These crucial deliberations shaped the discussion during the Masterclass, aptly titled “AI Risk Management: Safeguard India Amid Global Shift.”
One of the pivotal insights from the session was the integral role of artificial intelligence in risk prediction. By leveraging structured data, AI offers the ability to foresee and mitigate potential threats. This capability transforms uncertainty into a quantifiable and manageable variable, effectively neutralizing certain risks before they fully materialize. However, this effectiveness hinges on the integrity of data, which is increasingly vulnerable to breaches and manipulation. Data, though inherently revealing, is also fragile—it can be tampered with to distort realities, introducing new layers of risk. This vulnerability is far from hypothetical; it has far-reaching implications. Consider the growing concerns over election data and electoral rolls. If data integrity were immune to compromise, such apprehensions would not exist. While AI can efficiently identify fraudulent documents, the same technology can just as easily be weaponized to fabricate them. This dual-edge of AI technology poses threats not only to businesses but also to the very foundations of democracy.
In this broader context, the glaring lack of robust oversight mechanisms becomes evident. While the scope of the Masterclass was confined to the business domain, it is difficult not to draw parallels to other spheres where accountability is crucial. For instance, our electoral process. It may be noted that while government expenditures are rigorously audited by institutions like the Comptroller and Auditor General (CAG), the Election Commission of India (ECI), despite its critical role in safeguarding democracy, operates without comparable oversight on electoral data. This lack of checks and balances is a cause for concern, given the stakes involved and asks for risk-management!
Adding to this discourse is the global debate on the reliability of electronic voting machines (EVMs). Former U.S. President Donald Trump has been vocal about his preference for ballot papers over electronic systems, citing concerns about potential manipulation and lack of transparency. During a joint press conference with Indian Prime Minister Narendra Modi, Trump reiterated his belief that paper ballots offer greater security and trustworthiness in electoral processes. His remarks have resonated with critics of EVMs, who argue that the technology, while efficient, is not immune to vulnerabilities. This perspective underscores the need for robust mechanisms to ensure the integrity of electoral systems, whether through audits, enhanced security protocols, or a reevaluation of the technologies in use.
Perhaps the time has come to explore mechanisms for auditing electoral data, ensuring that the integrity of our democratic processes remains unassailable in an era where technology evolves at an unprecedented pace.