S1E23 - You Can't Trust What You Can't See, The Case for Federated AI with Tiffany Wang

S1 E24: Where Trust Breaks When the Law Gets Involved with Deanna Reitman

In this episode, we sit down with Deanna Reitman, Partner at Foley & Lardner LLP, where she works at the intersection of energy, commodities, and compliance. Her career has been built on a simple premise: trust has to survive scrutiny, not just sound good in a pitch deck. Deanna shares how an early grounding in rules and consequences shaped a career spent in the rooms where deals unwind, ownership gets disputed, and standards collide with the law that actually applies. As more markets lean on real-time data and digital platforms, she's blunt about where people get it wrong: "Data doesn't prove ownership. Leases do." We explore what it actually takes to protect a buyer from acquiring something they don't own, why self-reported compliance keeps creating the same failures, and what she needs to see before she'll stand behind any system, digital or otherwise. The conversation closes on what it would take for carbon markets and digital assets to hold up under real pressure, instead of unraveling the moment scrutiny arrives. If you enjoy the episode, don't forget to subscribe and leave a review.

S1E23 - You Can't Trust What You Can't See, The Case for Federated AI with Tiffany Wang

What happens when someone who spent years studying broken institutions decides to help build the next generation of them? Tiffany Wang trained as a corporate lawyer, moved into risk assurance and fraud investigation at PwC, and then made the jump to FLock.io — a federated AI company building the infrastructure for private, decentralized model training. Her whole career has been defined by one question: why do institutions say one thing on paper and operate completely differently underneath? In this episode, we get into her path from law firm to Big Four to AI startup, what federated learning actually means and why it matters for governments and sensitive sectors, and how FLock is working with UNDP to build climate resilience tools and micro-insurance platforms for unbanked communities in the Dominican Republic and Peru. We also dig into the Mauritius healthcare project, the work happening with the state of Sarawak in Malaysia on sovereign AI, and what trust actually looks like when you build it into the architecture instead of just promising it. Tiffany is also candid about what she learned about trust the hard way — from writing legal contracts designed to exploit ambiguity, to realizing words alone are never enough. Trust needs to be tested in difficult times, not comfortable ones. This one covers a lot of ground. If you work in government, healthcare, climate resilience, or you're just trying to understand where AI governance is actually heading — worth your time. Connect with Tiffany Wang:LinkedIn: https://www.linkedin.com/in/tiffany-wang-91a3ab13a FLock.io: https://flock.ioX Twitter: @flock_io Subscribe & follow The Future of Trust:Spotify - https://open.spotify.com/show/6zQ2p7k8q7OAuxqJElQjjh?si=35045c6c6b264f55 Apple Podcasts - https://podcasts.apple.com/us/podcast/the-future-of-trust-with-mat-yarger/id1792163372 Youtube - https://www.youtube.com/@DemiaOfficial 00:00 Introduction 02:00 Meet Tiffany Wang — Lawyer, Risk Investigator, AI Builder 03:00 Why she became a lawyer (and why debates shaped her more than law school) 05:30 What was missing in corporate law — the gap between paper and impact 07:10 The PwC pivot — getting closer to business, finding the same problem 10:20 Joining FLock — why it took three weeks and a regret calculus to say yes 12:40 What startup culture actually looks like vs. Big Four 15:40 Trail running, sacrifice, and how Tiffany thinks about hard things 18:15 Growing up between a risk-averse mom and an open-minded dad 23:00 Dating across cultures and how Tiffany learned to negotiate disagreement 31:25 The recurring question: when was your trust broken or strengthened? 33:00 What legal work taught her about the weaponization of language 35:30 Why she no longer gives 100% trust based on words alone 39:30 The gradual pivot — why there was no single turning point 44:50 What does FLock actually do? Explaining it from the ground up 47:00 Federated learning vs. traditional machine learning — the key difference 51:20 Who FLock is actually for (and who it isn't) 55:00 Working with UNDP — micro-insurance for unbanked women in Latin America 01:01:30 Puerto Rico, climate disasters, and why speed of response matters 01:04:00 Where does trust actually live in a decentralized system? 01:05:00 The verification layer — on-chain, auditable, no black box 01:07:30 Open source, community accountability, and why no one person holds the keys 01:10:00 FLock's healthcare project with the Mauritius government 01:12:00 The 10-year vision — AI tools people can use without fear 01:13:30 Sovereign AI and the work in Sarawak, Malaysia 01:16:00 Why education has to come before adoption 01:18:30 Closing — being known well vs. being well-known 01:21:00 How to connect with Tiffany and follow FLock

S1E22 - The Moment Founders Find Out Who’s Real with Matt Ober

What happens when the data looks right, but you still can't trust it? Matt Ober didn't walk through a polished front door into finance. He answered phones at Bloomberg, landed a hedge fund role through Craigslist, and built one of the world's most aggressive alternative data programs at WorldQuant, a quantitative hedge fund inside Millennium Partners that was testing thousands of new datasets a month and spending over $100 million to stay ahead of the signal. In this episode of The Future of Trust, host Mat Yarger sits down with Matt Ober, Managing Partner at Social Leverage and former data strategist at Third Point, for a candid conversation about what it really means to trust information, trust founders, and trust yourself when the stakes are high, and the answers aren't clean. Matt shares how he built trust frameworks not from theory, but from experience, watching convincing data collapse out-of-sample, witnessing activist investment battles at Third Point (Campbell Soup, Sony, Nestle), and being the investor founders call when things are going wrong. This is a must-listen for founders, investors, data professionals, and anyone navigating decisions where the signal is loud and certainty is low. IN THIS EPISODE: * How growing up as the oldest of five shaped Matt's instinct for responsibility and trust * Why answering phones at Bloomberg was the best preparation for working inside a hedge fund * How Matt found his WorldQuant role on Craigslist, and what that says about unconventional paths * The difference between data that looks convincing and data you can actually trade on * What "trust but verify" really means when you're testing thousands of datasets a month * Why activist investing is really about conviction, not confrontation * The single most repeated trust problem Matt sees in early-stage founders * How AI is changing the revenue-per-headcount benchmark, and what 3x-10x actually looks like * What Social Leverage looks for when deciding to stay close to a founder long-term CONNECT WITH MATT OBER: * Social Leverage: http://www.socialleverage.com * Newsletter: https//www.mattober.co * LinkedIn: https://www.linkedin.com/in/obermattj/ CONNECT WITH THE FUTURE OF TRUST: * Subscribe so you never miss an episode * Leave a review, it helps new listeners find us * Tag someone who needs to hear this conversation * Email us if you’d like to be a guest on the podcast - media@demia.net

S1 E21: When Your Name Is the Only Thing You Own with Oscar Hedaya

Trust does not break all at once. For some people, it cracks early, quietly, and permanently reshapes how they move through the world. Oscar Hedaya learned that lesson young. He grew up in New Jersey in a community that looked stable from the outside. Inside his home, things changed fast. Money disappeared. Certainty disappeared. But what stayed, was responsibility. Oscar started working at twelve, fixing spreadsheets for adults. At fifteen, he took a business owner to court because he wasn’t paid, and there was no one else to fight that battle for him. That experience did not make him cynical. It made him precise. In our first conversation, Oscar said something that stuck with me. When you grow up without money, the only thing you really have is your word. Your name becomes your currency. Lose it, and there is nothing left to fall back on. That belief shows up everywhere in how he operates today. Oscar is the founder of The Safe Space, a smart safe designed around a simple idea. People should not have to blindly trust companies, platforms, or institutions to feel secure. Ownership should be clear. Access should be earned. And systems should be built to protect users even when pressure shows up. He refuses to build in backdoor access. He designs for misuse, not best-case behavior. And he treats reputation as something you defend over decades, not something you trade for short-term wins. This episode is not about hardware specs or features. It is about what happens when someone who learned trust the hard way decides to encode that worldview into a system that other people rely on. We talk about early environments, personal lines he will not cross, and what it actually takes to build something people can depend on when it matters. Chapters: 0:00 – Introduction 02:10 – Growing Up in a Stable World That Wasn’t 08:45 – The Moment Trust Broke 15:20 – When Your Name Is Your Only Currency 21:30 – Wired to Build, Not Just Get By 28:10 – “My Company Is Me” 34:40 – The Theft That Sparked the Idea 40:25 – No Backdoors, No Blind Faith 46:50 – The 100-Out-of-100 Rule 52:30 – Looking Ahead 56:30 – Being Known Well

S1 E20: Designing Systems People Will Actually Trust with Richard Savoie

Trust rarely breaks loudly. Most of the time, it erodes quietly, one small doubt at a time. A number that feels off. A recommendation that does not quite match reality. A system that is technically correct, but still ignored. Richard Savoie has spent his career sitting right inside that tension. He started in regulated medical devices, where mistakes can have dire consequences and trust is not optional. In that world, data has lineage, accountability is clear, and failure forces learning. Later, he moved into logistics and transportation, a very different environment, but one facing its own quiet crisis. Labor shortages. Rising complexity. Pressure to automate faster than people are ready to trust the systems doing the work. In this first conversation, Richard shares that his focus on trust does not come only from engineering. It comes from experience. A long professional relationship ended when trust was broken in a way that forced him to rethink how people protect themselves, how they recover, and how they decide who or what deserves their confidence going forward. Today, Richard builds digital twins of logistics networks that help fleets decide how to move, when to electrify, and where automation fits. These systems recommend actions to streamline our orders with UPS, FedEx, Amazon, and more. That is where trust becomes real: if the operators on the ground do not believe the data or the actions they're recommended, they stop listening. If they cannot explain a decision, they override it. So if accountability is unclear, adoption stalls. This episode is about the human threshold where trust either forms or fails. We talk about early environments and how they shape responsibility. We talk about why people trust Google Maps without thinking, and why enterprise systems still struggle to earn that same confidence. And we explore what happens next as AI, EVs, and autonomous systems move from experiments into everyday infrastructure. Chapters: 00:00 – Introduction:  Trust Breaks Quietly 03:30 – Childhood, Broken Homes, and Early Trust 10:45 – Moving to Australia and Building a Life 16:00 – When Trust Is Actively Broken 22:30 – Reliability, Systems, and the Light Bulb Cartel 26:30 – Medical Devices and Designing for Certainty 32:30 – Leaving Healthcare and Starting Adiona 37:00 – COVID and the Scaling Moment 43:30 – Why Operators Ignore “Correct” Systems 51:00 – AI, Probabilistic Systems, and the Limits of Certainty 57:30 – Energy Grids, Electrification, and Profit Optimization 1:00:00 – Autonomous Delivery and the Last Meter Problem 1:12:00 – Being Known Well