Generative AI & Privacy: Risks, Realities, and What Comes Next

Moderated Panel

Panelists:

• Jason Clinton: Deputy CISO, Anthropic
• Whitney Merrill: Head of Data Protection, Privacy, and Compliance, Asana
• Sunil Agrawal: Chief Security Officer, Glean
• Nat Rubio-Licht: Senior Reporter, The Deep View

Generative AI is rapidly transforming how organizations innovate, but with new capabilities come new risks. This session will unpack the complex privacy challenges posed by generative AI, from data leakage to compliance blind spots. Attendees will gain a clear-eyed view of the risks and realities shaping today’s landscape, along with practical guidance on how to safeguard privacy without slowing down innovation. Join us to explore what’s next for AI and what it means for privacy—and how to build a strategy that drives growth but is rooted in doing the right thing.

Transcript

Hello everyone, and welcome to our panel on Gen AI and Privacy Risks Realities, and what comes next.

Um, I am Nat Rubio Licht. I'm a senior reporter with the Deep View, a daily newsletter on all things ai, and I am so excited to be the moderator today.

Um, as generative AI reshapes how organizations operate, it's redefining what responsible innovation looks like. Understanding and addressing its privacy risks isn't optional. It's essential in building trust, maintaining compliance, and enabling sustainable growth in the AI era. That is what we are going to talk about today.

Jason Clinton Introduction

Great to be here. 25 years in tech, long time at Google, and been in Anthropic for about two and a half years, so that's been a wild ride. Glad to talk about those today.

Whitney Merrill Introduction

Hi everyone. It's so great to be here. I've spent my entire career doing privacy and consumer protection. I started my career at the Federal Trade Commission and then went in-house, and I've been enjoying that ever since. Looking forward to the discussion.

Sunil Agrawal Introduction

Absolutely. Sunil Agrawal been in the security space for a good 25 plus years. Folks who don't know, Glean started as a Google for Enterprises search, B2B search engine, graduated to being a chat GPT for enterprises.

Main Discussion

• Is privacy keeping pace with innovation, or is it lagging behind?

  • Jason: Technology is offering solutions to some privacy challenges we face today. AI is changing things quickly, and we need to put the right guardrails in place.
  • Whitney: Strong foundational elements established over the last 20 years of privacy still apply to AI. Balancing gaps in innovation with these fundamentals is crucial.
  • Sunil: The timeline for privacy regulations has compressed recently, as AI regulations have emerged faster than in the past. There are still gaps in adoption across organizations.

• How does data leakage occur in generative AI?

  • Sunil: Data leakage can happen through three main forms: leakage into the model, leakage around the model, and side channel attacks.

• How do unintended outputs in generative AI lead to IP or privacy exposure?

  • Jason: Models can accidentally transmit privacy-related information due to their context and data handling.

• What are some of the key challenges of AI adoption in B2B vs. B2C?

  • Sunil: Enterprises need to ensure data isolation and enforce strict permissions to prevent unauthorized access to sensitive data.

Closing Thoughts

• Sunil: AI is your friend. Use AI to govern its own compliance and privacy assessments.
• Whitney: Controls and guardrails can actually help you move faster and drive innovation while maintaining privacy.
• Jason: Leaders need to decide their desired level of AI autonomy based on organizational risk tolerance.