Your AI Chats Aren’t Private (And How “Unlinkable Inference” Can Help)
Release Date: 05/13/2026
The Enterprise AI Mistake Most Companies Will Regret
The Brave Technologist
Joel McKelvey, VP of Product Marketing at Glean, shares why the enterprises winning with AI right now aren't the ones chasing the latest model—they're the ones who got their context layer right first. He explains why AI has moved from experimentation to company-wide production almost overnight, and why the biggest mistake enterprises are making is one they'll only recognize in hindsight. Key Takeaways Why the model you're running matters far less than the context you're feeding it How to think about AI ROI across three levels: individual, team, and organization What actually breaks...
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Why Most Enterprise AI Projects Never Make It to Scale
The Brave Technologist
Natalia Konstantinova, Lead Enterprise Architect in AI at Natwest, shares why most enterprise AI projects don't fail because of the technology, they fail because organizations skip the foundations. She also explains how responsible AI and scalable AI have converged, and why you can't achieve one without the other. Key Takeaways: Why most enterprise AI projects stall before scale What software engineers consistently get wrong about AI reliability Why governance actually accelerates delivery How to make AI transformational rather than just another digital tool Guest Bio: is Lead...
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The Global Fight for Free Speech Starts With a Hamster
The Brave Technologist
Preston Byrne, Tech & Free Speech Lawyer at Byrne & Storm, P.C., shares how a small American imageboard became the first test case for whether foreign governments can legally force American companies to comply with their censorship laws on American soil. He breaks down why the UK's Online Safety Act can't actually be enforced against US companies with no British presence; how a picture of an AI-generated hamster became a more effective legal strategy than a hundred-page brief; and what the proposed GRANITE Act would do to permanently close the loophole foreign regulators have been...
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How to Know When Personalization Becomes Creepy (AI Summit LDN)
The Brave Technologist
Dr. Mohsen Ghasempour, Chief AI Officer at Kingfisher, unpacks why the most dangerous thing a company can do with customer data is use all of it. He explains how a global, multi-brand retailer can draw the line between personalization that feels helpful and personalization that feels like surveillance. He also discusses why AI success is ultimately an execution problem rather than a technology problem. Key Takeaways: What the "comfort test" is and how Kingfisher uses it to decide whether a personalization decision has gone too far How global retailers are resolving the tension...
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What Counter-Terrorism Taught the NFL About Cyber Risk
The Brave Technologist
Kam Karaji, Director of Cyber Security & Risk Management at the NFL, shares what 13 years in counter-terrorism and criminal intelligence taught him about protecting high-stakes environments, and discusses how that thinking now shapes security across five countries and 70,000-person stadiums. He explains why a venue full of fans is really just a very large computer, and why the data a fan hands over the moment they buy a ticket is more time-sensitive than most people realize. Key Takeaways: How the NFL manages fan data across different legal jurisdictions, and why that data becomes...
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How a 200-Year-Old Bank Deploys AI Agents
The Brave Technologist
Andy McMahon, Principal AI Engineer at Barclays, shares how a 200-year-old bank is deploying autonomous agents inside one of the most heavily regulated environments in the world. He argues that observability and kill switches matter more than raw capability, and that the real test isn't whether the AI works in a demo, but whether it can fail safely in production. Key Takeaways How a major bank is giving AI agents real autonomy while keeping them bounded inside strict permission structures Why "could I build this" is the wrong question for engineers to ask Some of the current bottlenecks...
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LIVE FROM THE AI SUMMIT LDN: Inside Sony AI's Bet on Open Research
The Brave Technologist
Fred Gifford, Strategy Lead and Sr. Product Manager at Sony AI, shares how his team is building knowledge graphs from academic literature to predict new biomedical relationships and accelerate drug discovery. He explains why Sony AI publishes so much of its research openly, what he got wrong about AI therapy when writing his novel and why he believes accountability for AI's ethical failures still lags dangerously behind the pace of the technology itself. Key Takeaways: Why specialized AI tools are losing ground to all-in-one chatbots and what that means for the personal data we hand...
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Pandora: How Much Freedom Should a Shopping Agent Have? (AI Summit LDN)
The Brave Technologist
Riccardo Arnaldi, Agentic AI Product Manager at Pandora, shares what it actually looks like to build and scale a brand-facing LLM shopping agent live with millions of customers. He explains why too much autonomy is a liability, how a deterministic routing layer keeps the AI from going off-script, and why traditional QA teams had to rebuild their processes from scratch. He also breaks down a real customer interaction that exposed the gap between automation and appropriate human sensitivity, changing how the team handles frustrated users. Key Takeaways Which metrics Pandora uses to measure...
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AI Is Now Buying Cars and Negotiating Better Than You
The Brave Technologist
Zach Shefska, Founder & CEO of CarEdge, shares how he and his father (a 43-year auto industry veteran) turned a broken, opaque car buying process into a transparency-first business powered by AI agents that now negotiate deals on behalf of consumers. He also explains how data collected from over 100,000 agent driven negotiations is reshaping what buyers can know before they even walk into a dealership. Key Takeaways: Why the car buying process is structurally designed to work against both consumers and the salespeople serving them and what's starting to change How AI...
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Why Your VPN Isn't Actually Keeping You Anonymous
The Brave Technologist
Harry Halpin, CEO of Nym Technologies, shares why the surveillance Web is more dangerous than most people realize, and why most privacy tools aren't enough. He explains how traditional VPNs still leave you exposed, why metadata is more revealing than the content of your messages, and how Nym's decentralized mixnet offers unique protection. Key Takeaways: Why encrypting your data isn't enough and what metadata reveals that most people don't consider What a mixnet is and why it's built differently than Tor Why age verification mandates could be the real turning point for Internet freedom ...
info_outlineKen Liu (Computer Science PhD at the Stanford AI Lab) and Erik Chi (CS PhD at UMich) are the Creators of the Open Anonymity Project, which lets people prove things about themselves online without revealing their identity. In this episode we explore what it means for AI systems to “know” you; why today’s so-called privacy modes fall short; and how the next generation of AI systems could be built with privacy as a default, rather than an afterthought.
Key Takeaways:
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What “unlinkable inference” means and why it changes the privacy model of AI chat tools
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What actually happens to your data the moment you hit “send” in a typical AI system
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Why incognito mode in AI tools is largely a UI illusion, rather than a real privacy protection
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The role of metadata in identifying and profiling users, and how “secretary models” could enable personalization without sacrificing privacy
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How anti-censorship and privacy intersect in a future dominated by agentic AI systems
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Why now is the time to rethink assumptions about privacy in AI tools
Guest Bio:
Ken Liu is a Computer Science PhD student at the Stanford AI Lab, advised by Percy Liang and Sanmi Koyejo. His research focuses on foundation models and data/user privacy, and the intersection between the two. His recent work studies the privacy properties of AI (such as membership, memorization, and unlearning), and various AI privacy tools (such as anonymization, differential privacy, and federated learning). His papers have earned spotlights at top venues, and his findings have been deployed at scale on Android. Ken also led a team to a 1st-place win at the US-UK PETs Prize sponsored by the White House OSTP and the UK Government. Previously, Ken spent time at Google DeepMind, Carnegie Mellon University, Meta, Apple, and Amazon.
Erik Chi is a CS PhD at UMich, advised by J. Alex Halderman. His research focuses on security and privacy, particularly network security and anti-censorship. He worked on a new standard for implementing and distributing censorship circumvention protocols—a standard that’s now being adopted by VPN vendors to help millions of users access the free Internet. He also did content moderation (surveillance) and recommendation systems at ByteDance before realizing how censors will evolve in the AI era.
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About this Show:
The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all!
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Produced by: Sam Laliberte