Podcast Episodes List

In this episode of Vartalap, we unpack the evolving intersection of artificial intelligence and privacy law, focusing on one of the most critical questions, i.e., how will consent architecture function in the age of generative AI?

As AI systems grow more powerful, traditional notions of user consent are being redefined. We explore what meaningful consent looks like when data is constantly learned, processed, and repurposed by intelligent systems.

The conversation also dives into the challenges of bias embedded within AI models and highlights why robust checks and balances are essential to building trustworthy technology.

As regulators and innovators navigate this rapidly shifting landscape, the questions around consent, fairness, and accountability are emerging as top priorities in shaping the future of AI and privacy. We discuss some of these issues in this episode.

What happens when machines start competing and colluding faster than humans can even detect?

In this episode of Vartalap, we dive into the fascinating intersection of artificial intelligence and competition law. As AI reshapes markets, it also raises complex questions regulators are only beginning to study.

From the subtle risks of algorithmic collusion to the growing power of data dominance, and the evolving challenges around deal notifiability, we unpack how traditional frameworks are being tested / will be tested in an AI-driven economy.

Can regulators keep markets fair without slowing innovation? And how do we strike the right balance between oversight and opportunity in this new technological era?

We break down these pressing issues, offering insights and perspectives on the future of competition in the age of AI.

This vartalap unpacks a lesser-discussed but increasingly significant challenge emerging under India’s Digital Personal Data Protection (DPDP) Act. While the law is fundamentally designed to safeguard the rights of data principals, its practical application is beginning to expose a complex “B2B conundrum” between data fiduciaries and data processors.

As businesses rely more heavily on third-party processors, questions around accountability, control, and liability are no longer straightforward. Who truly bears responsibility when something goes wrong - the entity that determines purpose, or the one that handles the data operations? While the law puts the liability on data fiduciary, but the business engagement coupled with negotiating power asymmetry, will complicate the process and raise issues.

At its core, this is not just a compliance issue, rather a shift in how businesses collaborate, allocate risk, and build trust in an increasingly regulated digital landscape.

Artificial Intelligence (Al) regulation is a pressing topic that sparks debates worldwide. The question of whether Al should be regulated, and if so, the extent and method of regulation, remains a key concern. In this Vartalap, we delve into the theme of "Artificial Intelligence and Policy Regulation: The Indian approach." This discussion aims to shed light on what could be India's perspective regarding Al regulation. We offer our insights and perspectives on this crucial subject. We discuss a wide variety of topics - from deepfakes to affixation of liability. We also discuss whether there should be any safe harbour protection.