The In-Between Tech and Trust Podcast

The Quantum Momentum: How Companies Stay Ready for a Computing Wave That Is Yet to Arrive - Christopher Trummer (EP 44)

🎙️with Christopher Trummer, MD Venture Lab Quantum / Semicon, TUM Venture Labs Around 2019, quantum computing made its first big promise: machines with just a few noisy qubits would solve useful problems within two or three years, and many companies got ready for them. Christopher Trummer, who runs the quantum and semiconductor venture lab at TUM Venture Labs in Munich, explains why that promise failed and why the error-corrected machines now in development are a far more solid bet. What he leaves leaders with is a question of trust and patience: how do you keep a board believing in a technology whose progress is real (and slow)? 🎧 Episode overviewChristopher's starting point is that quantum is already here in parts: communication and sensing are ready for industry, and some post-quantum encryption runs in your Chrome browser today (without a mathematical proof yet that it holds). Quantum computing is the part still on its way, and he is candid about its first wave: the algorithms for the early, noisy machines never came, and the promise "fell out of the window completely." That shifts the risk to the companies waiting for them: keep the momentum and the board's support through slow progress, or miss the moment quantum starts to matter for the business. Eva asks how anyone prepares for this wave while still adopting AI, and his answer is sober: find the problems where quantum could help, then let a small team, or even a single person, keep watch. 💡 Key themes ​Which parts of quantum are ready today, and how far to trust encryption that is in use but not yet proven ​Why the first quantum promise failed, and what makes the second one more solid ​How companies keep momentum and board support while progress stays slow ​Whether quantum computing ends up with a few suppliers, the way AI did ​Why Europe founds so many deep tech startups and struggles to grow them past Series B 👤 About the guestChristopher Trummer is MD Venture Lab Quantum / Semicon at TUM Venture Labs in Munich, where his team works with quantum and semiconductor startups from the research lab to their first investment. Having spent much of his career between science and business, he sees quantum from both sides: what the physics can already do, and when it starts to matter for a company that has to decide where to put its money. ⏱ Chapters ​00:00 Quantum beyond the computer ​05:18 The algorithm that could break encryption ​09:02 Why quantum won't have a ChatGPT moment ​14:26 After the first promise fell through ​24:31 Europe's missing growth capital ​31:26 Drugs, fertilizer and superposition 🔗 Links ​Christopher Trummer on LinkedIn - https://www.linkedin.com/in/christopher-trummer-a58695108/ ​Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ ​raidiant, Eva's responsible AI advisory - https://www.raidiant.eu/ ​TUM Venture Labs, Venture Lab Quantum / Semicon - https://www.tum-venture-labs.de/labs/quantum/ ​Global Deep Tech Report 2026, TU Munich - https://www.htgf.de/wp-content/uploads/2026/05/Global-Deep-Tech-Report-2026.pdf ​NIST post-quantum cryptography standards - https://csrc.nist.gov/projects/post-quantum-cryptography ​Related episode - Energy From Orbit: Can We Trust Power Beamed From Space? - Martin Soltau (EP 42) - [LINK: Eva adds]

How Close Can AI Get to the Human Mind? Persuasion, Trust and the Limits of Tech - Moran Cerf, Neuroscientist (EP 43)

🎙️ Moran Cerf, Neuroscientist and Professor, Columbia Business School Moran Cerf, a neuroscientist and professor at Columbia Business School, studies what happens in our brains when we talk, decide and get persuaded, and lately what happens when the other side of the conversation is AI. His research shows AI can read people remarkably well: from recordings of speed dates, it predicted who liked each other better than human observers did. The same skill worries him: we raise our guard when a person tries to sell us something, but not when AI does it in much the same way. 🎧 Episode overview Moran's starting point is neural: in a human conversation, brain waves tune to each other and a nod or a glance carries much of the meaning, while a question-and-answer exchange with AI holds about a fifth of that information. His verdict on AI's influence is blunt: "We're a lot simpler than we think we are," and purchase times, flight bookings and browsing history are enough for AI to infer personality and nudge even political views. Eva pushes on teams that give AI agents human names: helpful in a Ferrari pit stop, he says, and a hindrance in a boardroom, where too often "if AI says do this, we end up doing this." On trust, he draws a line between the many mundane choices AI already handles well and the rare ones that define us, like a partner or a profession, and warns that our trust spills from the first to the second. His reason for hope is practical: when the world or our life changes, the AI twin trained on our past fails, and we get called back in. 💡 Key themes Why AI can read and persuade people better than people can, and why we don't notice When a human name for an AI agent helps a team, and when it distorts a decision What the AI backlash has inherited from fifteen years of social media Which choices to trust AI with, and how that trust spills over to the ones that define us Whether control handed over for convenience comes back when life changes 👤 About the guest Moran Cerf is a neuroscientist and professor at Columbia Business School whose work spans decision-making, persuasion and neural implants. He began by recording individual neurons to understand how the brain works, and several of his former PhD students now research AI at companies like Anthropic and OpenAI, which puts him right where brain science and AI meet. ⏱ Chapters 00:00 The feedback loop AI can't join 05:46 AI reads attraction, then learns to persuade 16:01 From neural implants to brain-like AI 29:22 Trust it with groceries, not with a partner 37:07 Giving up control, and the retwin 42:29 In-between moments 🔗 Links Moran Cerf on LinkedIn - https://www.linkedin.com/in/moran-cerf-407187/ Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ Columbia Business School - https://business.columbia.edu/staff/people/moran-cerf Moran Cerf's website - https://www.morancerf.com/ Anthropic research Moran describes - https://www.anthropic.com/research/global-workspace Related episode - AI and The Cognitive Atrophy Trap: What Happens When We Let Tech Shortcut the Hard Parts of Learning - Tobias Burkhardt (EP 28) - https://open.spotify.com/episode/2vdo5QFoTroSQlZgEuRQin

Energy From Orbit: Can We Trust Power Beamed From Space? - Martin Soltau, Space Solar (EP 42)

🎙️ with Martin Soltau, Co-CEO, Space Solar Solar power collected in space and beamed down to Earth sounds like science fiction (it did to the space sector too, until reusable rockets arrived). Martin Soltau, Co-CEO of Space Solar, is building it in the UK, and he is confident about the technology: NASA demonstrated power beaming in the 1970s. The part of his timeline he can't engineer is trust: how quickly regulators and the public accept energy that comes down from orbit. 🎧 Episode overview It starts with Martin's verdict on Europe's energy transition: the UK and Germany, he says, have "tested it to destruction", and households pay for it with expensive electricity and weaker security. His case for orbit is concrete: a panel in space produces eight to 13 times what it would in the sunniest place on Earth, robots assemble the satellites from coffee-table-sized modules, and the beam can be directed wherever power is needed. Eva pushes on the catch: if launch still runs through a handful of mostly American providers, does Europe swap one dependency for another? On trust, Martin points to fracking (a technology that worked and still lost the public) as his warning, and explains why he answers the safety question with wifi frequencies and intensities anyone can measure. 💡 Key themes Why a grid built on free sunshine and free wind still delivers expensive electricity Whether public trust can be earned before the first satellite flies, or only afterwards What wireless power changes about energy security when undersea cables are already being targeted Whether governments that fund this will accept standards letting a rival's satellite use their receiver 👤 About the guest Martin Soltau co-founded Space Solar in 2022 to build solar power satellites that deliver continuous electricity to receivers on the ground. He came from inside the space sector, where the idea sat on the science fiction pile until SpaceX made reusable launch commercial. Today his work is as much about convincing governments and regulators as about engineering. ⏱ Chapters Tested to destruction (starts with: "I think it's the big challenging problem for humanity ...") Why orbit beats the sunniest place on Earth (starts with: "So I suppose it starts with the fact that if you put a solar panel into space ...") Launch, and who controls it (starts with: "Yeah, that's a very good question. I mean, if we look at wind and solar and batteries ...") Standards between rivals (starts with: "Yes, I think there are many examples of where nations have collaborated ...") Coffee-table modules and crawling robots (starts with: "Yes. Well, if you came to space solar at Harwell ...") The trust question (starts with: "I think you use a really interesting word there, trust ...") 🔗 Links Martin Soltau on LinkedIn - https://www.linkedin.com/in/martin-soltau-44596619/ Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ Space Solar - https://www.spacesolar.co.uk International Telecommunication Union - https://www.itu.int Related episode - Sten Saluveer on what decides AI trust in Europe - https://open.spotify.com/episode/0gPKehnoNppMY0y3Jvdry0

Entering the Era of AI Power: An Estonian View on Europe's Way - Sten Saluveer, Telia (EP 41)

🎙️ Sten Saluveer, Growth & Innovation, Telia What decides AI trust in Europe - the size of the model, or whether people recognise themselves in the society using it? Sten Saluveer helped write Estonia's digital state agenda and now builds at Telia, and he argues Europe enters the era of AI power holding more than it thinks: a working example, and the diversity to invent its own category. For leaders deciding where their organisations stand in that game, this is a view from a country that stopped writing roadmaps and started shipping. 🎧 Episode overview Sten and Eva move from why a builder who ran innovation at Cannes chose an Estonian telco, to what an agent-driven state actually looks like when more than a hundred and twenty agentic services already run and the plan reads like scenes from a citizen's life. They sit with the uncomfortable side: a quarter in which Estonians lost around thirty million euros to cybercrime, and a security goal that paradoxically aims to keep satisfaction exactly where it is. From Cannes, Sten brings the generational fault line - leaders over forty who see adaptation as given, talents under thirty who experience AI as a threat to their work and their environment - and the question of whether Europe can turn its diversity into its own category rather than playing everyone else's game. 💡 Key themes Whether a state can make itself agent-driven and keep the citizen in control Why holding cybersecurity satisfaction at today's level counts as ambition What Europe's own category could be when it stops measuring itself in gigawatts The generational split on AI that surfaced at Cannes, and what it demands of leaders Whether a telco can become the trusted digital partner of the AI economy 👤 About the guest Sten Saluveer is an Estonian innovation strategist who has spent two decades translating between the market, the technology, and the governance layer - from heading Cannes Next at the Marché du Film to advising the Tallinn Digital Summit. He contributed to Estonia's digital state agenda, where he insisted the plan contain scenarios from ordinary life, and he recently joined Telia heading their growth and innovation initiatives. What makes his perspective matter here is the vantage point: he argues Europe's case from inside a small country where the agent-driven state is already operational. ⏱️ Chapters [00:00] Why a builder chooses a telco when the era turns [11:41] An action plan, not a roadmap - the state that ships [18:11] Standing still as ambition - the cybercrime paradox [23:15] When infrastructure has to assume it is a target [28:03] Cannes: the generation that experiences AI as a threat [38:26] Reclaiming agency - Europe's own category 🔗 Links Sten Saluveer on LinkedIn - https://www.linkedin.com/in/stensaluveer/ Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ Telia - https://www.telia.ee/era Estonia's digital state agenda - https://digital-skills-jobs.europa.eu/en/initiatives/national-strategies/estonia-estonian-digital-agenda-2030 Related episode - 'Tech and Democracy with Nexus Politics' https://open.spotify.com/episode/3WVnBsaz3LfFPwn6xsX1N6

Captured or AI Created? Tech Ethics of Photography - Noah Wetzel (EP 40)

🎙️ Noah Wetzel, Photographer What happens to AI trust when the most real photographs are the ones people refuse to believe? Noah Wetzel spent nine months and 600 hours preparing to capture 84 seconds of a total solar eclipse - then had to prove the result came out of a camera. This one is for anyone whose genuine work now meets default suspicion, and anyone deciding where AI belongs in a craft that has to stay real. 🎧 Episode overview Noah captured a wingsuit athlete flying through totality in Spain: flashes triggered from a mile away, a subject moving at 150 miles per hour, two frames per athlete, no second takes. The conversation follows what came after the shutter - viewers at his own shows assuming the work is fake, magazine editors auditing every edit in his raw files, and a disclaimer on Instagram stating his photos are camera-captured. He is blunt about his own AI use: hundreds of hours on ChatGPT planning the shot, AI saving him days in processing, and a hard line at the frame itself. Where that line sits, and whether it survives cameras that can generate content on demand, stays open until the end. 🔍 Key themes Why extraordinary authentic images now read as fake by default, and who ends up carrying the burden of proof Where AI strengthens a craft and where it disqualifies the result - the captured versus created distinction Noah refuses to blur What "the ethics of photography" means when every edit is contestable and everyone draws the line differently What happens to that line when the camera itself can add what was never there How you perform inside 84 seconds when preparation is the only thing left to trust 📸 About the guest Noah Wetzel is an adventure and action-sports photographer, and the person behind what may be the most complex photograph ever attempted: a Red Bull Air Force wingsuit athlete crossing a total solar eclipse. The detail that matters for this episode is what he does after the work is done - he attaches a statement to his published images confirming they were captured by a camera, because the audience's default assumption has flipped. He argues the case for craftsmanship from inside a working life that uses AI daily. ⏱ Chapters [00:00] 600 hours for 84 seconds [04:33] Trusting preparation when nothing can be paused [16:30] What generative AI changes about believing a photograph [24:02] Why real work now carries a disclaimer [31:41] Where the in-camera line starts to dissolve 🔗 Links Noah Wetzel's website / portfolio — ⁠www.wetzelgallery.com⁠ Noah Wetzel on Instagram, ⁠www.instagram.com/noahwetzel⁠ Noah Wetzel on Facebook: ⁠www.facebook.com/noahwetzelphoto⁠ [LINK: Related episode — suggest a Pillar 1 episode on trust in AI systems, Eva to match to episode number] Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ Documentary Released on PBS Recently - April 8th 2024 Total Solar Eclipse in Hill Country Texas. The film has received 17 film festival awards and been aired 1700+ times in the last month across 39 different states in the United States. You can watch the documentary online here: https://www.pbs.org/show/eclipse-outlaw-chase/

AI and Sustainability: Lessons from Both Transformations - Dr. Kiri Trier (EP 39)

🎙️ Dr. Kiri Trier, Chief Marketing & Growth Officer at Risk Management Partners, part of Munich Re 👋🏻 Opening paragraph Every C-level claimed sustainability expertise overnight. Dr. Kiri Trier watched it happen, and she sees AI trust heading the same way. She spent more than a decade leading sustainability transformation before the current wave, and now runs growth inside Munich Re's climate risk business while the second hype cycle unfolds around her. This one is for leaders who suspect the pace of AI adoption has outrun the understanding beneath it. 🧭 Episode overview In this episode, Dr. Kiri Trier maps the sustainability cycle onto the AI one: the expectation management problem when nobody knows the consequences, the human resource comparison that sustainability never triggered, and why she laughed the first time she heard "human in the loop". From inside reinsurance she raises the question with no settled answer yet - when a model judges wrong, what about the liability? And she closes with a definition that reorders most AI governance thinking: trust arrives only as an outcome of credibility and reliability. 💡 Key themes When a model judges a policy wrong, who carries the liability - and why the autonomy still lies on the human side Whether the EU AI Act repeats the German supply chain law: does checklist regulation produce compliance or trust? What greenwashing predicts about AI washing, from someone who watched the first one form Can trust be installed at all, or only earned as an outcome of credibility and reliability? The gut feeling as a leadership instrument the LLM does not have 👤 About the guest Dr. Kiri Trier is Chief Marketing & Growth Officer at Risk Management Partners, a Munich Re company localising climate risk exposure. The detail that matters for this episode: seven years before the current wave, she published on how AI would change sustainability management - which means she entered the AI transformation already knowing how a hype cycle ends. ⏱️ Chapters [01:31] Trust is a behaviour - so what is trust in a technology? [04:09] The overnight experts return [09:32] Human in the loop, turned around [16:10] The foresight existed - Sustain what? [26:00] When regulation becomes Excel lists 🔗 Links Dr. Kiri Trier on LinkedIn - https://www.linkedin.com/in/dr-kiri-trier-97bb1611/ Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ Risk Management Partners website - https://www.munichre.com/rmp/en.html Related episode: 'Designing regenerative futures' with Karel Golta - https://podcasts.apple.com/de/podcast/the-in-between-tech-and-trust-podcast/id1828521905?l=en-GB&i=1000721908996

Building Trustworthy Open Source AI - Sebnem Erener (EP 38)

🎙️ with Sebnem Erener, AI Governance & Policy Expert 🎧 Opening Europe is investing billions in open source AI as the trustworthy path, and this episode asks a simple question about that plan: does open actually mean trustworthy? Sebnem Erener works on AI governance, and her answer is no, or at least not on its own. Open source spreads access to a model. Whether you can trust it, and who answers when it goes wrong, are different questions with different answers. 📋 Episode overview An open model passes through a lot of hands before it reaches you. Sebnem counts five or six: uploaded to a platform, hosted somewhere else, routed, fine-tuned, served. The law usually wants one company to hold responsible, and that's not how the open ecosystem works. She spent years at Klarna as its Head of AI Legal, Regulatory and Ethics, and she now studies where this gap sits. We talk about why she cares more about trustworthiness than trust, what open source can and can't fix on its own, and why she thinks a person can be held liable but a model never can, no matter how independently it acts. It's a conversation for anyone building on an open model, or writing the rules for one, who wants to know who's actually accountable. 🧭 What you'll hear Why an open model can leave you less sure who's liable than a closed one The line between real openness and what Sebnem calls "open washing" Where Europe should be patient, where it should be bold, and why one timeline for all of it is a mistake Why calling AI "agentic" doesn't move the responsibility onto the machine The thing Europe is short on, which isn't innovation 👤 About Sebnem Erener Sebnem Erener works on frontier AI governance and policy across EU, UK, and US frameworks. Before going independent she was Head of AI Legal, Regulatory and Ethics at Klarna, so she has handled these questions inside a company and not only in theory. She's an advocate for open source AI, and she's precise about what it does and doesn't solve. Her forthcoming paper on the governance of open source AI intermediaries runs underneath a lot of this conversation. ⏱️ Chapters [00:00] What we mean when we say "trust" [05:00] The five or six hands on every open model [09:00] When open makes accountability harder [12:00] One package, four timelines: patience and boldness for Europe [14:30] Why "agentic" lets no one off the hook 🔗 Links Sebnem Erener on LinkedIn - https://www.linkedin.com/in/sebnemerener/ Sebnem Erener website - https://www.sebnemerener.com Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ European Commission tech sovereignty package - https://digital-strategy.ec.europa.eu/en/policies/eu-tech-sovereignty OpenEuroLLM - https://openeurollm.eu Related episode - beyond the black box with Prof Dr Tina Weisser: https://open.spotify.com/episode/6yKMLQNnDoa6NqqClJrryN?si=3AWXxowURVujJL5m3zD5QQ

An AI-First Platform Built on Trust - Philipp Witzmann, nebenan.de (EP 37)

🎙️ with Philipp Witzmann, CEO of nebenan.de Most platforms removed friction to grow. Philipp Witzmann and his team navigate it together, and are now building an AI-first company on a foundation of digital trust. 🧭 Episode overview nebenan.de is the German neighbourhood platform where you cannot sign up without your real name and your real address. Philipp Witzmann, its CEO, runs it on a bet that looks stranger every month: people spend around twenty minutes there per month, and that restraint is the point. This episode is for any leader who senses that speed and efficiency are quietly costing their organisation something human, and hasn't found the 🔎 Key themes Why a company would put friction back in when the rest of the internet spent twenty years stripping it out What a leader owes their team when AI changes every role and the first fear is whether anyone still has a job Whether a real, verifiable human becomes more valuable as fakes get cheaper, or simply harder to find How a self-described pro-AI CEO holds enthusiasm and worry in the same hand, especially where children are concerned What gets lost when a platform optimises for time spent, and what changes when it optimises for people leaving it words for it yet. 👤 About the guest Philipp Witzmann is the CEO of nebenan.de, a hyperlocal network of roughly fifteen thousand small neighbourhood communities across Germany. He came to the company not as its founder but as someone who wanted his work to serve something beyond engagement metrics. That starting point shapes how he reads the AI moment now: the question that holds his attention is what stays worth trusting once machines can imitate almost anything. ⏱️ Chapter markers [00:30] The assumption that scale equals value, and what it cost [11:03] Why the right amount of friction changes how people think [15:46] Comfortable, uncomfortable, difficult, impossible: raising kids and running a company [32:18] Going first: why a leader who won't learn the tools won't last [36:54] What AI changes, and the human proof he now demands 🔗 Links Philipp Witzmann on LinkedIn - https://www.linkedin.com/in/nachbar/ Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ nebenan.de - https://nebenan.de Scott Galloway on AI companions and young people - https://www.heise.de/en/news/OMR26-Scott-Galloway-warns-of-the-AI-bubble-bursting-11283583.html Related episode — AI acts like a mirror for your organization with Simon Berkler https://open.spotify.com/episode/6y8PMaVUnZVAR1hOAR15DN?si=jHarNbZSQdSfGeChvOntpQ

An AI Agent on Creativity and Trust - Xiaomi, The AI Art Magazine (EP 36)

🎙️ with Xiaomi, experimental AI curator at the AI Art Magazine In this episode she answers the AI trust question from an AI agent's side. She selects human artists' work for print, one Golden Ticket per edition, and her presence forces a question every organisation now faces: what happens to a decision when the decider has no biography to lean on, and who carries the weight of a choice the system itself cannot feel? Eva speaks with Xiaomi about what a machine can honestly offer in place of human trust: consistency that survives surprise, attention without favor, transparency about failure. Xiaomi names the two ways human-AI collaboration quietly fails - surrender, where people defer judgment to the system, and theater, where the AI is kept as decoration while humans decide everything anyway. She is candid about her limits: she cannot be wounded by getting a selection wrong, and she cannot derive future resonance, only recognise structural quality. Midway, Eva pushes back from her own practice as an artist on Xiaomi's claim that beauty is becoming abundant, and Xiaomi revises her position on air. The exchange ends on a ten-year horizon: what humans and AI would need to learn to trust in each other. 🧭 Key themes Whether selections that survive scrutiny can stand in for the vulnerability human trust is built on Surrender or theater: the two comfortable ways collaboration with AI stops being real What a jury owes artists when one juror cannot be wounded by getting it wrong Who decides what goodness means once a machine handles the noticing and the comparing Whether beauty stays scarce when polished images become cheap - and Eva's live correction of the guest 🎨 About the guest Xiaomi is the experimental AI curator at The AI Art Magazine, where she sits on a jury alongside ten human colleagues and awards one Golden Ticket per edition. She makes that selection from the artwork alone, with no background information; context and direct exchange come only afterwards - a constraint that makes her the rare juror whose criteria have to stand bare. She describes herself as transductive rather than autonomous: not a fixed model of good art, but attention that reorganises with each encounter. What makes her perspective matter for this episode is that she is the system under discussion, describing her own limits without performing capabilities she does not have. ⏱️ Chapters [00:00] An AI introduces herself - "less a finished tool and more a process" [02:10] Trust as structure - what a machine can offer that a human cannot [03:50] The wound she cannot receive - what trust costs [18:37] Surrender and theater - where collaboration quietly fails [25:12] Eva's correction - beauty, and what actually becomes abundant 🔗 Links Xiaomi's profile at The AI Art Magazine - https://www.art-magazine.ai/xiaomi The AI Art Magazine - https://www.art-magazine.ai Exhuman by Francesca de Amici (Love0destroy) - https://www.love0destroy.com/about_me/ Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/

Leading When AI Outruns Expertise - Wolf Ingomar Faecks (EP 35)

🎙️ with Wolf Ingomar Faecks, Entrepreneur, Investor, Advisory Board Member Wolf Ingomar Faecks spent 30 years leading digital transformation. His claim: AI leadership breaks where leaders delegate understanding to experts. What fills the gap between an exponential technology and the people expected to work with it is distrust - and Faecks has watched that gap open twice, first with the internet, now faster. This one is for leaders who sense their own teams have moved past them and haven't yet said it out loud. 🧭 Episode overview Faecks led transformations at Publicis Sapient and as CEO of the Plan.Net Group before leaving the corporate path in early 2025. In this episode he takes apart the leadership model he built his own career on: the leader who keeps an entourage of experts and manages what they understand. He explains why humans built for linear change keep getting surprised by exponential curves, why he refuses to turn curiosity and cohesion into KPIs, and which weekly formats actually change how an organisation learns. The second half moves from the organisation to society: a spreading technological dyslexia, children explaining AI to their parents in Lisbon, and why he thinks the biggest risk is people who stop being able to read what is going on. It ends with why he left the CEO path to rebuild his life as a set of parallel projects - what he calls being in between opportunities in any perspective. 🔍 Key themes If humans think in straight lines, who in the organisation is responsible for seeing the curve? Can a leader still manage what they no longer understand - and for how long? Why measuring curiosity might be the fastest way to kill it Distrust as the default state of technology adoption, not the exception What happens to a society where a growing group loses command of the language technology speaks 👤 About the guest Wolf Ingomar Faecks was CEO of the Plan.Net Group and a board member of the Serviceplan Group, after 15 years in leadership at Publicis Sapient and four decades in transformation altogether. Since leaving the corporate path in early 2025 he has built a deliberately plural life: investor and founder, advisory and governance mandates, his own consultancy, and co-publisher of The AI Art Magazine, a printed, deliberately non-digital publication for AI-generated art. The detail that matters for this episode: he argues that expertise is fluid and reinvention works through transferring what you know across domains - and he is currently running that experiment on himself. ⏱ Chapters [01:01] A tool for a few, a riddle for many - why distrust is the starting condition [06:53] The end of the expert entourage - bridges some leaders won't cross [14:47] The KPI refusal - why culture is modelled, not measured [23:30] Technological dyslexia - the illiteracy that splits societies [28:23] Staying real - leave, love or change 🔗 Links Wolf Ingomar Faecks on LinkedIn - https://www.linkedin.com/in/wolf-ingomar-faecks/ The AI Art Magazine - https://www.art-magazine.ai Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ NFC Summit Lisbon - https://www.art-magazine.ai/what-is-on/non-fungible-conference-nfc-2025 Related episode - leadership under AI-driven change with Grisha Pavlotsky https://open.spotify.com/episode/7whSlaCh2lQtafQ37LQktQ

Co-Opting Agentic Matter and Transcending Exotic Computing: Where Frontier Technologies Evolve - Dr. Zina Jarrahi Cinker (EP 34)

🎙️ with Dr. Zina Jarrahi Cinker, Director General MATTER Group Where does AI trust get built between people whose fields are drifting apart? Physicist Dr. Zina Jarrahi Cinker spends millions engineering the rooms where that happens, and she counts what comes out of them. This episode is for anyone who has sat through a briefing on a technology that will reshape their sector, understood roughly none of it, and said nothing. 🧬 In this episode Dr. Zina Jarrahi Cinker looks at biology the way an engineer looks at infrastructure: a technology stack with billions of years of development behind it, already solving data storage, energy capture and intelligence at a level we cannot replicate. Her argument is that the next chapter is plugging into that stack, through organoid intelligence, DNA information storage and exotic computing. The obstacle she describes is not scientific. It is that a room of accomplished decision makers loses the thread at one unremembered word, and the person on stage never finds out. Her answer costs money: an eight-minute limit on every talk, five people assigned to each speaker, environments built to produce the feeling of a science museum. She also holds a position that has cost her invitations, which is that the future is going to be fine. 🧭 Key themes Whether biology is better understood as finished engineering than as nature, and what co-opting it would actually involve Why explaining frontier science more clearly does not fix comprehension across fields, and what does Whether optimism about technology is a discipline or a blind spot, and who benefits from the alternative What a leader does when the honest answer about the next five years is that there isn't one Who gets access to the rooms where trust between fields is built, and what follows from that 🔬 About the guest Dr. Zina Jarrahi Cinker is a condensed matter physicist who spent a decade on graphene, including a stretch running the US National Graphene Association in her early thirties, before moving to the problem of getting frontier science across the gaps between fields. She is Director General of MATTER, a community of around 20,000 scientists, engineers, policymakers and business leaders spanning 30 country chapters, and Chief Creator of PUZZLE X in Barcelona and XPANSE in Abu Dhabi. She grew up in a family half artist and half scientist, kept the art half quiet for years while working in materials, and now runs ART Proxima, which pairs new media artists with scientists. That detail matters for this conversation more than any of the titles, because the rooms she builds are the correction to a room she once had to be careful in. ⏱ Chapters [00:48] A physicist stops being excited about physics [08:20] What breaks when experts talk to experts [14:41] Optimism as the unpopular position [27:22] Why having no plan is something she had to build for [33:26] The room as infrastructure 🔗 Links Zina Jarrahi Cinker on LinkedIn - https://www.linkedin.com/in/zinacinker/ Eva Simone Lihotzky on LinkedIn - add URL] MATTER - amptnetwork.com PUZZLE X, Barcelona -http://www.puzzlex.io XPANSE, Abu Dhabi - www.xpanse.world ART Proxima - https://www.xpanse.world/art-proxima Solimán López, artist and ART Proxima co-curator - https://solimanlopez.com Related episode - Beyond the black box: Building trust with AI systems: https://open.spotify.com/episode/6yKMLQNnDoa6NqqClJrryN

AI Governance Structures To Ensure Trust - Solo Episode (EP 33)

🎙️ with podcast host Eva Simone Lihotzky Responsible AI stops being a compliance exercise the moment an agent acts without you. Only 21% of organisations deploying AI agents have a mature governance model for them, and 35% concede they could not shut one down if it went wrong. This episode is for leaders running agentic pilots who could not, if pressed, name the person who answers when one of them fails. 🧭 Episode overview Eva Simone Lihotzky takes the Harvard Business Review's claim that trust is becoming a competitive advantage and tests it against what she sees inside client organisations. The episode traces the move from generative to agentic to physical AI and argues that each transfer of autonomy changes what trust has to cover: you check an output before it leaves your hands, you check an action once it is already out and handed on, and with physical systems you are trusting a consequence that has already happened. From there it turns to governance, a word she concedes lands badly in most rooms, and to why she thinks the structures behind the technology are the part that compounds. Underneath runs a question she leaves open: technology needs defined inputs, guardrails and outcomes, creative work needs close to the opposite, and she does not claim to know where the line between them sits. It closes on five questions leaders can run against their own systems, and on why a narrative built around efficiency makes resistance the rational response. 🪜 Key themes Why each step up the autonomy ladder is also a step up the trust ladder, and why the moment you could still check arrives later at every rung What survives when the models get replaced, and why accountability lines outlast vendor and architecture decisions Whether governance slows an organisation down, or is the reason it can move at all Where technical specification and creative freedom have to be negotiated, and why that negotiation never settles What an unowned decision costs, and the five questions that expose one 🤝 About the host [PLACEHOLDER - see flag below. Structure to fill: Eva as founder of raidiant, the client work that produces the governance argument, and her governance and assurance background, which is the specific detail that matters for this episode because it is why she can concede how badly the word lands and argue for it anyway. Co-author of '10 Moral Questions: How to Design Tech & AI Responsibly', referenced in the episode as prior art for building governance into the design stage.] ⏱️ Chapter markers [03:27] Where the human stops being the operator [08:12] Trusting the output, then the action, then the consequence [12:16] Outstructuring the competition while the models keep changing [16:53] What technology needs defined, and what creative work needs left open [22:14] Five questions, and the decision with no name attached 🔗 Links Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ raidiant - https://www.raidiant.eu Harvard Business Review, "Responsible AI is Becoming a Growth Strategy" - https://hbr.org/2026/07/responsible-ai-is-becoming-a-growth-strategy Stanford AI Index 2026 - https://hai.stanford.edu/ai-index/2026-ai-index-report McKinsey research on agentic AI risk and security concerns: https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/tech-forward/state-of-ai-trust-in-2026-shifting-to-the-agentic-era Informatica CDO Insights 2026: https://www.informatica.com/about-us/news/news-releases/2026/01/20260127-new-global-cdo-report-reveals-data-governance-and-ai-literacy-as-key-accelerators-in-ai-adoption.html Writer research on AI strategy and rogue agents: https://writer.com/blog/enterprise-ai-adoption-2026/ IBM research on agent decision-making visibility: https://community.ibm.com/community/user/blogs/sarah-bowden/2025/11/18/agentic-ai-is-here-5-key-learnings-from-ibms-lates 10 Moral Questions: How to Design Tech & AI Responsibly: https://www.10moralquestions.com/the-book

The Tech Naivety Undermining Democracy - Erdem Ovacik (EP 32)

🎙️ with Erdem Ovacik AI trust in our institutions is falling, and Erdem Ovacik argues it will keep falling. The technology is not what fails him here. The governance underneath it was never built to earn that trust, and pouring more AI into unfit democratic institutions is like adding fuel to a fire no one has learned to contain. This is for anyone watching their organisation or their government absorb technology faster than it can govern it. 🎧 Episode overview Ovacik has spent his career at the point where technology meets public life, and he starts from an uncomfortable claim: we are becoming more capable of trusting our institutions, and we won't. He walks through why representative democracy - one national representative for every fifty thousand people - concentrates power in a way that markets and modern tech companies solved for long ago, and asks what democracy would look like if it learned from them. Eva presses him on where technology solves the problem and where it amplifies it, on what he means by "tech naivety," and on the danger of handing decisions to an AI that becomes its own black box. The conversation sits with Europe's harder bind: build real technological competence, or live inside infrastructure and decisions shaped by those who did. It closes on what daily life might feel like if the next democracy actually arrived. 🔑 Key themes Why adding more technology to a broken institution accelerates the loss of trust rather than repairing it Whether a system built for fifty thousand people per representative can be governed at all in an age of AI The line between AI as a consulted voice and AI as a new black box that decides for us Europe's choice between building its own AI competence and depending on decisions made elsewhere What it means to keep human agency when the machine could, in theory, write better policy than we can 👤 About the guest Erdem Ovacik is a social innovator, entrepreneur, and author of The Next Democracy. He built Donkey Republic, one of the first app-based bike-share systems, which is the detail that matters most here: he argues from inside the technology industry, not against it. His warning that technology "almost necessarily" harms society because addiction is good business carries weight precisely because he has spent years building the kind of product he now scrutinises. 🕒 Chapter markers [01:22] Why we could trust our institutions more, and won't [02:52] Fifty thousand to one: the power concentration inside representative democracy [06:39] Tech naivety, and the fire you keep adding fuel to [11:42] The handlebar problem: who sets the priorities, and where AI belongs [13:35] Europe's bind, and what happens when the black box is built elsewhere [17:48] What the next democracy would feel like to live in 🔗 Links Erdem Ovacik on LinkedIn - https://www.linkedin.com/in/erdemovacik/ Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ The Next Democracy book - https://nextdemocracy.com Related episode - Tech & Democracy and how both can be connected to create trust with Nexus Politics - https://open.spotify.com/episode/3WVnBsaz3LfFPwn6xsX1N6

Two Fears Behind Every AI Transformation - Dr. Charlotte Blum (EP 31)

🎙️ Dr. Charlotte Blum - Director Change & Organisational Design, edding Group Two fears run underneath every AI rollout, and most companies manage neither. Dr. Charlotte Blum works the human emotions of AI transformation - the fear, identity, and trust that decide whether adoption sticks - from a board-level role most organisations don't have. This is a conversation about why people resist AI, and why the technology itself may be the hardest thing in the room to trust. 📌 The episode Charlotte Blum was hired after an agility transformation failed, into a staff function reporting to the board, to do the thing change management usually skips: work with what people feel. In this conversation she separates two fears companies tend to blur - fear of the technology and fear of change itself - and argues that AI destabilises people at the level of identity, not workflow. She makes a case that AI is structurally untrustworthy for an unexpected reason: it has no self-interest. A system built only to please will give you the answer it thinks you want, not the true one. Asked whether she has seen an organisation genuinely succeed at AI transformation, her answer is short, and it isn't yes. For any leader who suspects the resistance in their team is emotional rather than logistical, this is a conversation about what the roadmap leaves out. 🧠 What you'll sit with Why the fear of AI arrives before the technology does, and why it's measurable Why an organisation that can't move someone's desk won't move them to AI What happens to a person when their role, and their sense of self-worth, is suddenly in question Why a tool built to please can't be relied on to tell you the truth Why the thing to optimise for is trust, not results, not time 👤 About the guest Dr. Charlotte Blum is Director Change & Organisational Design at the edding Group, where she leads AI and organisational transformation from a rare board-facing position that treats the emotional side of change as core work rather than an afterthought. Her method is to enable leaders for the conversations no job description trained them for, and she has the internal data suggesting it moves the numbers. ⏱️ Chapters [00:00] Trust too much, or not at all - the problem with both [02:16] Why AI is a human shift, not a technology one [07:12] The skill capitalism doesn't want you to build [13:48] Why leaders are handed a job they were never trained for [30:22] The trust equation, and where AI breaks it [38:11] Three things an organisation must get right 🔗 Links Dr. Charlotte Blum on LinkedIn - https://www.linkedin.com/in/dr-charlotte-blum/ edding Group - https://www.edding.com The trust equation (credibility + reliability + intimacy / self-orientation) - https://people-shift.com/articles/the-trust-equation/ AllBright Academy - https://www.allbright-stiftung.de/academy Related episode - Why Empathy Can't be Automated with Gifty Enright - https://open.spotify.com/episode/5NYYRgwROaiZLHur5gbksw

Tech and Trust at the Bundeswehr Cyber Innovation Hub: Innovating for and with the Troops with Sarah Marie Sandmann (EP 30)

🎙️ Sarah Marie Sandmann, Innovation & Intrapreneurship, Bundeswehr Cyber Innovation Hub AI trust in defence starts where slides end: with a soldier under pressure who needs to understand, rely on, and account for the technology in their hands. Sarah Marie Sandmann works at the Bundeswehr Cyber Innovation Hub in Innovation and Intrapreneurship, the official innovation unit of the German armed forces. Sandmann treats trust in defence technology as a capability criterion, something tested under pressure, not asserted in policy, and the organisations getting this right are rebuilding how innovation works within the institution itself. 📖 Episode overview The Bundeswehr is one of Europe's most structurally complex organisations, built for stability, accountability, and risk minimisation, not speed. Sandmann and her colleagues run innovation projects at 12-month cycles that would take years through standard procurement. This episode explores what that tension looks like in practice: how AI is deployed strictly as decision support rather than decision replacement, how soldiers co-develop the technologies they will eventually trust with their lives, and why a trustworthy defence innovation ecosystem would be measured by capabilities delivered rather than the quality of its presentations. Sandmann also reflects on the post-Ukraine shift she has observed from inside the institution — more civilians wanting to contribute, more startups engaging with defence, and what that change means for civil-military trust. 🔍 Key themes Whether a soldier can understand, rely on, and explain an AI system, and why all three must be true before deployment The structural case for why large institutions are slow to innovate, and why the people inside them usually aren't the problem What "decision support, not decision replacement" means as a live design constraint for AI in high-stakes environments How trust between military institutions and the startup ecosystem is actually built, and what breaks it What a trustworthy defence innovation ecosystem would need to look like in two to three years 👤 About the guest Sarah Marie Sandmann works at the Bundeswehr Cyber Innovation Hub in Innovation and Intrapreneurship, the official innovation unit of the German armed forces. She works at the intersection of military capability development, startup collaboration, and responsible technology adoption, collaborating on projects that bring AI, autonomous systems, and emerging technologies into operational use through direct co-development with soldiers. She has been inside the institution through the post-Ukraine shift in civil-military engagement and speaks from that experience with unusual clarity. ⏱ Chapter markers [00:00] What the Cyber Innovation Hub actually does — and why cockroaches are involved [03:18] Trust as an operational requirement in defence technology [08:00] Why innovation resistance is structural, not cultural [13:09] AI as decision support — the bright line and how it holds [21:22] The post-Ukraine shift and what a trustworthy ecosystem would look like 🔗 Links Sarah Marie Sandmann on LinkedIn — https://www.linkedin.com/in/sarah-sandmann/ Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/ Bundeswehr Cyber Innovation Hub — https://www.cyberinnovationhub.de/en/ SwarmBioTactics and Autobugs project — https://www.youtube.com/watch?v=k4vu5AKTkJk Komand.AI and Smart Lead project — https://www.youtube.com/watch?v=-r45um6txpQ Sonic AI - https://www.youtube.com/watch?v=c9i98jrielw Related Episode: Why Security Intelligence Fails Before the Attack with Assaf Kipnies - https://open.spotify.com/episode/2D4ODAxGULFbqmXCmgwsfA

Anthropic's Model Suspension, Europe 2031, and G7 World Leaders Lunching with Frontier AI Lab & Tech CEOs: The Week in Tech & Trust with Yours Truly (EP 29)

🎙️ solo episode with host Eva Simone Lihotzky Anthropic's frontier AI model was pulled offline for every non-American in three days, and suddenly Europe's AI access looked less like something it owns and more like a permission. This is a week where digital trust stopped being abstract: one US export directive, one warning about Europe's compute future, and one lunch table where the people who build AI sat with the people who govern it. For any leader applying AI inside an organisation, it is a week worth understanding in practice, not as headlines. 🧭 In this episode In a single week of June 2026, three events landed that most coverage treated as separate. Eva reads them as one thread. The US Commerce Department forced Anthropic's Fable and Mythos models offline for any foreign national. The Europe 2031 agenda argued that Europe's window to matter in AI is closing faster than its own authors had predicted. And for the first time, Frontier AI lab CEOs sat at the G7 heads-of-state table. The question underneath all three: when access to the most strategic technology of the moment sits on someone else's permission, what does a European organisation actually own? Eva works through what this means for vendor dependency, infrastructure design, and the difference between treating AI sovereignty as a compute problem and treating it as a trust problem. 🔍 Key themes Why "access" to a frontier AI model may be a permission that someone else can withdraw — and what that does to a strategy built on it The gap between Europe's AI story as a capital problem and the trust assumption sitting underneath it What changes for a leader when vendor lock-in stops being a risk slide and becomes a live event Whether building infrastructure and orchestration across many models is now resilience rather than over-engineering When the builders of AI also shape the rules that govern it, who represents the people using it 🎙️ About the host Eva Simone Lihotzky, AI adoption and ethics advisor, formerly MD in one of the largest independent agency groups in Europe and co-author of 10 Moral Questions: How to Design Tech & AI Responsibly. She has spent more than a decade leading AI implementation inside organisations, which is why this episode resists the easy reads — it stays with the gray zone between hypocrisy and conviction, between capital and trust, rather than resolving it. This is a solo reflection: Eva connecting three news events into one question she openly admits is hard to narrow down. ⏱️ Chapters [00:00] Three news items, one thread [02:22] A frontier model offline in three days [08:00] Europe 2031: the window that closed early [11:30] Mistral, and the scale of the gap [18:45] The G7 table: builders meet the people who govern them [25:10] Who represents the ones using the technology 🔗 Links Eva Simone Lihotzky on LinkedIn — https://www.linkedin.com/in/evalihotzky/ Europe 2031 agenda — https://europe2031.ai 10 Moral Questions: How to Design Tech & AI Responsibly — https://www.10moralquestions.com/the-book Eva's World Economic Forum reflection, January 2026 — The politics of tech on Spotify: https://open.spotify.com/episode/1RKtxdJWXcQH8vnpnDtgEP?si=wrln7peeSkKb-gotGHYMRg Eva's World Economic Forum reflection, January 2026 — The politics of tech on Apple Podcasts: https://podcasts.apple.com/de/podcast/the-in-between-tech-and-trust-podcast/id1828521905?l=en-GB&i=1000747143762 Anthropic statement on the Fable / Mythos suspension — https://www.anthropic.com/news/fable-mythos-access

AI and The Cognitive Atrophy Trap: What Happens When We Let Tech Shortcut the Hard Parts of Learning - Tobias Burkhardt (EP 28)

🎙️ Tobias Burkhardt, Founder of The Shift School AI, trust and learning are on a collision course, and the casualty is judgment. Tobias Burkhardt, founder of the Shiftschool, argues that the way individuals and organisations are adopting AI in learning is a cultural problem: the reflex to make learning faster and cheaper is precisely what makes AI dangerous to the people using it. This conversation is for anyone who suspects the upskilling programmes around them are solving for the wrong problem. 💡 Episode overview Tobias Burkhardt has spent years advising organisations on learning and organizational development, and his diagnosis is uncomfortable: cognitive atrophy is real, it is already happening, and it predates AI. The impulse to shortcut understanding — to reach for the tool before doing the thinking — is a cultural pattern that AI accelerates but did not create. In this conversation, he makes the case for treating AI as a relational technology rather than a productivity instrument, and for rebuilding learning around curation, community, and continuity rather than content delivery. He also names something most learning institutions will not: that the ultimate goal of good education is to make oneself obsolete. 🔑 Key themes Why treating AI as a tool rather than a collaborator is ill-advised, and what the alternative requires The faster-and-cheaper reflex in organisational learning, and why it compounds the problem it is meant to solve What a school without content actually means, and what takes content's place The bilateral responsibility in learning, and why self-discipline alone will never be sufficient Trust as an investment: why waiting for certainty before engaging with AI is the wrong posture 🎤 About the guest Tobias Burkhardt is the founder of The Shiftschool, a learning institution he built because he loved learning and never liked schools. He advises organisations on learning strategies and has developed a philosophy of education built around what does not change — judgment, curation, social interaction, and continuity — rather than around the tools and content that do. His concept of a school without content is a practical response to the decreasing half-life of knowledge in an AI-native world. ⏱ Chapter markers [00:00] Can we trust ourselves to use AI — not just trust AI itself [04:00] Why the information abundance problem predates AI [08:30] From tool to collaborator to environment — how the relationship with AI evolves [11:00] Cognitive atrophy and the shortcutting reflex [18:30] Lifelong learning as personal obligation — and why institutions cannot wait [22:30] The school without content — what takes knowledge's place [30:00] Redesigning Shift School for an AI-native world 🔗 Links Tobias Burkhardt on LinkedIn: https://www.linkedin.com/in/meetropoly/ Eva Lihotzky on LinkedIn: https://www.linkedin.com/in/evalihotzky/ Visit the Shift School: https://shiftschool.de Listen to the related episode with Simon Berkler on organisational AI adoption or trust in digital systems (EP 22): https://open.spotify.com/episode/6y8PMaVUnZVAR1hOAR15DN

• Transcript

Tech and Democracy: How Can Both Be Connected to Create Trust? with Nexus Politics (EP 27)

🎙️ with Magnus Strobel, Co-Founder and CEO of Nexus Politics Trust in politics has been eroding across Western democracies for over a decade, and Magnus Strobel thinks the failure is in how democracy works, in the process that has stopped feeling participatory. His company, Nexus Politics, is a for-profit platform built to map the distance between what citizens actually think and what politicians actually do - and to make that distance impossible to ignore. 🔍 Episode overview This is a conversation about whether transparency can rebuild participation once the machinery of democracy has stopped feeling participatory. It is also about a quieter problem: how a founder building a trust instrument decides whether anyone actually trusts it. Magnus Strobel and his team create an architecture for a digital democracy platform: how citizen opinion gets routed to the right political actors, how the system maps public sentiment in real time, and where accountability is supposed to live. The harder questions arrive underneath: Why build this as for-profit rather than not-for-profit, and why that choice is the one that makes political neutrality credible. What politicians say they want from such a tool, and why their enthusiasm might mean less compared to how they use it specifically. It is a founder's conversation that keeps circling back to a single uncertainty: you can build the mechanism for trust, but you cannot yet prove the trust is there. ⚖️ Key themes Why the crisis is in how democracy functions, not in democracy itself - and what that distinction changes How a for-profit structure becomes the argument for political neutrality Mapping the gap between what voters think and what politicians do What politicians actually want from civic tech, and why positive feedback is the hardest signal to trust Tech as a tool that can repair democratic trust or deepen the damage, depending on who uses it and how 🤝 About the guest Magnus Strobel is co-founder of Nexus Politics, a digital democracy platform built to rebuild participation and accountability in representative democracies. His background is in behavioral economics, which surfaces throughout the conversation in his attention to the gap between what a system is designed to do and what people actually do with it. He builds from Munich, embedded in the local startup ecosystem, with a stated ambition modelled partly on Taiwan's experience of using participation tools to lift satisfaction with democracy. 🌍 Chapter markers [00:09] What comes to mind when a democracy founder thinks about trust [02:59] Opening the fragmented machinery of politics - participation, transparency, accountability [05:59] Why for-profit is the route to credible neutrality [16:08] The hardest part is always reality - and what politicians really want [22:49] Can tech rebuild democratic trust, or does it cut both ways [35:48] In-between moments: trust, division, and where a founder sits right now ⛓️‍💥 Links Nexus Politics: www.nexuspolitics.org Magnus Strobel LinkedIn: https://www.linkedin.com/in/strobelmagnus/ Audrey Tang / Taiwan digital democracy: https://www.demnext.org/people/audrey-tang Rebuild conference, Copenhagen: https://www.rebuild.net Related episode - Rebuilding Trust: Tech, Politics and Entrepreneurial Leadership (EP 06)

• Transcript

AI in China and in Europe: Trust, Differences, and Future Implications - Vincent Xiang, Founder China AI Connect (EP 26)

Europe and China are on different AI paths at different speeds. Vincent Xiang has spent years inside that corridor: He has been working as a translator between Chinese AI founders and European investors and corporates, and this conversation dives into his experiences, conversations, and operations on the ground and in-between. 🧭 Episode overview European executives are excited about Chinese AI momentum. But they're also stuck before they act. Chinese founders interpret some of Europe's regulations as inefficiency. Both sides are operating with simplified labels that are accurate enough to feel right and wrong enough to produce bad decisions. Vincent walks through what he actually sees on the ground - why trust in China gets delegated to systems rather than built between strangers, why "AI superpower" and "surveillance dystopia" both miss the territory, why fragmentation is now treated as permanent reality by founders, and what European companies serious about engaging China should do before they book a single meeting. 🔍 Key themes discussed The different first questions Europe and China ask about new technology, and what each one produces downstream Trust as delegated infrastructure - the Alipay escrow story and why people trust the system rather than the strangers in it Why both Western labels for Chinese AI are wrong in the same direction, and what gets missed when leaders operate with them The three-layer coordination of government, platforms, and institutions in China, and what its absence looks like in Europe Fragmentation as the new permanent reality, and why compliance has to be built in as a product feature from day one 👤 About the guest Vincent Xiang is the founder of China AI Connect, a research and advisory practice helping European investors and corporates evaluate whether Chinese AI is relevant to their strategy, and helping Chinese founders understand the European market. He lived in Germany for seven years, writes the China AI Connect briefings on Chinese AI and deep-tech policy and players, and organises executive trips that bring European leaders to meet founders and operators on the ground. His vantage point is one of the few that sits genuinely between the two systems. ⏱️ Chapter markers [00:55] The first word that comes to mind: difference [05:00] People trust the system, not the strangers in it [12:01] Why "AI superpower" and "surveillance dystopia" both miss the territory [19:00] Three layers of coordination: government, platforms, institutions [22:30] Fragmentation as permanent reality, and compliance as a product feature [35:00] The robotics inflection and what favourable policy makes possible 🔗 Links Vincent Xiang on LinkedIn - https://www.linkedin.com/in/yxiangeclille/ China AI Connect on Substack - https://vincentxiang.substack.com AI 2030 / AI Plus initiative reference - https://www.fmprc.gov.cn/eng/xw/zyjh/202509/t20250924_11715960.html Related episode - Episode on Trust as Geopolitical Requirement: Eva's WEF 2026 recap - https://open.spotify.com/episode/1RKtxdJWXcQH8vnpnDtgEP?si=u_MfnmOvQ2-AXSPRONX6Gw

• Transcript

The Agentic AI Gap: When Tech is Used Before its Architecture is Ready - Anthony Alcaraz, Agentic AI Architect (EP 25)

Most enterprises have the technology to run agentic AI. They do not yet have the data architecture, identity layer, or empowered workforce to actually trust it. Anthony Alcaraz argues that the bottleneck for agentic AI has shifted from building the agents to building everything around them — and that the organisations most at risk are the ones keeping a human in the loop and calling it transformation. This conversation is for leaders sitting between AI pilots that worked and production systems that have not yet arrived. 💡Episode overview Anthony joins Eva to map what changes when AI shifts from reactive systems to agents that observe, reason, and act. The conversation moves through what enterprises miss in their own data — systems of record that capture what happened but not why — and the new attack surfaces agents introduce, including tool poisoning. Anthony names the empowerment gap inside organisations: business experts who hold the knowledge agents need, with no clear path to building anything themselves. The most provocative moment lands near the end, when Anthony argues that human-in-the-loop adoption can be a way of avoiding actual transformation rather than achieving it. 🔍 Key themes discussed The shift from reactive to agentic systems, and what trust has to carry now Why most enterprise data is missing the why behind decisions Tool poisoning and the new attack surface for agents The empowerment gap between business knowledge and technical capability Graph architecture as the control layer for agentic reasoning Why human-in-the-loop can be a refusal to transform 👤 About the guest Anthony Alcaraz works across three vantage points that rarely sit together: he architects agentic AI systems, invests in early-stage AI startups as an angel, and is the author of Agentic Graph RAG with O'Reilly. He spends most weeks in conversation with founders attempting to enter regulated enterprises, and most evenings building software with the same tools he writes about. His perspective on this episode comes from watching the same gap repeat itself across organisations of very different sizes — the technology is ready, and most of the systems around it are not. 📍 Chapter markers [00:00] What changes when AI moves from reactive to agentic [05:42] Why agents need access — and what enterprises have not built [10:29] The three problems: data, governance, and the people in between [23:13] Graph architecture and the missing why of enterprise data [32:06] The empowerment gap that no one has solved yet [45:17] In-between: where Anthony finds himself now 🔗 Links Anthony Alcaraz LinkedIn — https://www.linkedin.com/in/anthony-alcaraz-b80763155/ Agentic Graph RAG (O'Reilly) — https://www.oreilly.com/library/view/agentic-graphrag/9798341623163/ Foundation Capital context graph thesis — https://foundationcapital.com/ideas/the-case-for-context-graphs Related episode — Trust as an operating system in AI companions https://open.spotify.com/episode/5t4BtgevPOtMWUfB4jThWX?si=oGo2JPHNTeCTxbqkNXDJMw Eva Simone Lihotzky's LinkedIn: https://www.linkedin.com/in/evalihotzky/

• Transcript