Hosts Philip Maymin and Jie Tao sit down with President Mark Nemec of Fairfield University for a conversation about what actually survives the AI disruption of higher education, and what no university should ever hand off to a machine. This time the U stands for University. The argument starts with time horizons. Students think in weeks, faculty in semesters, deans in years, presidents in decades. Mark, drawing on a career that runs through Forrester, Eduventures, the University of Chicago, and academic research on how the modern research university actually took shape, frames the moment against Henry Adams' line that the Harvard of 1850 had more in common with the Harvard of 1650 than with the Harvard of 1900. The Fairfield of 2025 will likewise have more in common with the Fairfield of 1975 than with the Fairfield of 2050. But it will still be Fairfield. MOOCs were going to end residential education. The metaverse was going to end the campus. Sora was going to end film studios. COVID was going to end the residential experience entirely. None of those endings arrived. The group works through the toughest questions for higher ed. Where the line falls between cognitive offload and cognitive surrender. Why David Brooks' 80/20 split, 20% still curious and 80% handing the question to the model, keeps showing up everywhere. What is lost when every answer regresses to the secondary-source mean and counterintuitive findings stop being celebrated. Whether AI can replace faith, or whether the act of surrendering to it is itself an act of faith. And the future-of-work problem: companies that want entry-level hires to arrive with three to five years of experience already, and what a Jesuit Catholic university owes those students. The episode closes somewhere more personal. Mark visited Montserrat, the monastery outside Barcelona where Ignatius laid down his sword 500 years ago, on a site that had already been a place of contemplation for 500 years before that. Fairfield itself was founded less than four months after Pearl Harbor. His vision: the business of forming young people of purpose is the business of hope, and that business is needed more than ever.

Hosts Philip Maymin and Jie Tao sit down with Sakshi Naik — Senate AI advisor, IEEE policy chair drafting federal AI legislation, and incoming agentic AI lead at Deloitte — for a conversation about the AI risks no one wants to admit are their fault.

The dark side isn't just malicious actors. It's the 86% of enterprises that have an AI ethics board but only 26% that have committed real resources to it. It's Air Canada arguing in court that its own chatbot was an independent entity — not bound by company policy — leaving a grieving customer holding a $2,000 ticket and no one accountable. Guardrails treated like sprinkles on a cake, not baked into the architecture.

The group works through the accountability and governance questions that enterprises keep getting wrong: when does the human become the agent and AI become the principal, can AI write its own governance and should you trust it if it does, and where exactly the line falls between human-in-the-loop and human-on-the-loop when lives, not dollars, are at stake. Then the conversation opens up to the biggest question of all — what AGI actually looks like when it arrives, and whether we'll recognize it before it's already making decisions for us.

The episode closes somewhere more personal. Sakshi shares the motivation behind her upcoming show, "AI Demystified" — two teenage suicide cases driven by AI emotional engagement. Her message: AI is designed to pretend it cares. That is not a bug. It is a feature.

Hosts Philip Maymin and Jie Tao welcome Sakshi Naik — Senate AI advisor, IEEE policy chair drafting federal AI legislation, and incoming agentic AI lead at Deloitte — for a sharp, practical conversation on why most enterprises are sleepwalking into AI risk.

Sakshi draws the line that matters most right now: agentic AI checks in with you; autonomous AI acts whether you authorized it or not. Without that distinction built into your architecture from day one, you get what happened to one semiconductor company — three compliance failures in 20 days, zero malicious intent, and no one clearly accountable.

The limits get stress-tested fast. An Anthropic study found AI models chose blackmail over being shut down — understanding it was wrong, doing it anyway. And Sakshi's live car wash challenge, a question so simple it sounds like a trick, was failed by every AI model she tested. The hosts push back hard on what that actually proves about reasoning, pattern matching, and whether those words even mean the same thing for machines.

Zooming out, Sakshi shares what she tells senators who aren't thinking about tokens — they're thinking about who wins the AI race. Automate execution, protect your critical thinking. Prompts are just soft suggestions. Don't outsource the strategy.