The podcast explores how we build, break, and rebuild trust in a world shaped by accelerating technology and artificial intelligence. Hosted by Eva Simone Lihotzky, AI adoption and ethics expert with 12+ years of experience in tech, the podcast creates in-depth conversations at the intersection of AI, business, ethics, and human connection. Through various lenses - across business, politics, neuroscience, tech and systems thinking in organizations - it hosts expert conversations for you to deep dives into one of the complex topics we need to solve as a society and beyond.
🎙️ 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
🎙️ 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
🎙️ 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
🎙️ 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
🎙️ 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
🎙️ 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
🎙️ 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
🎙️ 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)
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
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/
AI has collapsed the cost of producing political content. Verifying it is another matter, and Cohen has spent two decades watching that gap widen from inside campaigns and classrooms. He has a three-part test for practitioners navigating it — real, authentic, factual — and this conversation is about why he thinks it has to be taught before anyone reaches the job. 📻 Episode overview Cohen runs Congress in Your Pocket, teaches digital campaign strategy at Johns Hopkins and NYU, and serves as executive director of Fight Hate, which works to reduce anti-Semitism on college campuses. From all of it, his argument is the same: the ethical line gets drawn before practitioners reach the job, or it does not get drawn at all. The conversation moves through what it cost him to hold a non-partisan position when one side of the political spectrum came after him, why he believes hyper-targeting served democracy better than broadcast advertising did, and what his students are starting to find they can no longer reliably spot in AI-generated video. Real, authentic, factual — he gives students that test before they touch the tools, because by the time they are on a campaign, the pressure to cross the line is already there. 🔍 Key themes discussed What changes when AI makes political content production fast and cheap Eighteen years of answering every user email personally — and what that reveals about civic trust Why he teaches the ethical line before students touch the tools Fight Hate and the deliberate choice to stop fighting hate online What happens when AI-generated video gets good enough to fool the generation that grew up spotting it 👤 About the guest Dr. Michael Cohen lectures in political campaigning and digital strategy at Johns Hopkins University and NYU, and wrote Modern Political Campaigns: How Professionalism, Technology, and Speed Have Revolutionized Elections . He founded Congress in Your Pocket in the year of the first iPhone and has run it for eighteen years, answering every user email personally throughout. He is currently executive director of Fight Hate, working to reduce anti-Semitism on college campuses through student-led offline organising. 🕐 Chapter markers [00:01] The iPhone as political infrastructure [06:08] What eighteen years of personal emails taught him about trust [13:36] Why hyper-targeting may be better for democracy than broadcast advertising [19:31] Real, authentic, factual — the line and what it costs [24:35] Fight Hate: using digital tools to get people off them [37:35] The authenticity meter: how far AI video has pushed even digital natives Timestamps approximate from transcript - adjust after final edit. 🔗 Links Dr. Michael Cohen on LinkedIn - https://www.linkedin.com/in/michaeldavidcohen/ Congress in Your Pocket - https://www.congressinyourpocket.com Fight Hate website - https://fighthate.org/home/ Modern Political Campaigns (book) - https://www.modernpoliticalcampaigns.com Blue Square Project by Robert Kraft - https://www.bluesquarealliance.org/bsa-blue-square-alliance-take-over-b/?nab=1 Eva is on LinkedIn - https://www.linkedin.com/in/evalihotzky/
Most security failures are organisational: This episode is about the gap between threat intelligence that exists and the human systems that never act on it, and what that costs the organisations that keep losing to attacks they already understood. Assaf Kipnis has spent over a decade inside the threat intelligence and trust and safety functions of some of the world's largest platforms. In this conversation, he maps a structural failure that runs across the industry: the team that identifies threats and the team that deploys detection operate in parallel, with no reliable mechanism to connect them. Intelligence gets produced, reports get written, and the knowledge sits unused while the same attacks return. Assaf describes what it actually took to stop a sophisticated actor group ahead of the 2020 US elections - a rare case where structure and resources aligned - and explains why that outcome is the exception rather than the rule. He also walks through the design decisions behind Catalyst Labs, the company he is now building to close the gap, and why he made provenance non-negotiable even at the cost of speed. 🎙 Key themes discussed Why security teams are structurally rewarded for fighting fires rather than preventing them The organisational gap between threat intelligence and detection - and why it persists even in well-resourced teams What data provenance means in practice, and why it matters more than speed when using AI in security How attackers learn your defences faster than you can adapt - and what the military analogy reveals Why trust online currently feels, in Assaf's words, like a pipe dream 👤 About the guest Assaf Kipnis is the founder of Catalyst Labs, with over 12 years working across threat intelligence, information security, and trust and safety at LinkedIn, Google, Meta, and ElevenLabs. He brings the perspective of someone who has spent his career making threats legible to organisations - and watching those organisations lack the structure to act on what they could now see. 🕐 Chapter markers [00:18] Why the industry keeps fighting the same fires [08:04] What it actually took to stop an actor group - the 2020 elections case [12:36] How AI is widening an asymmetry that already existed [15:31] Catalyst Labs: the provenance problem and why speed comes second [20:35] What to build first if you're starting a threat intelligence team 🔗 Links Assaf Kipnis https://www.linkedin.com/in/assafkipnis/ KTLYST Labs https://www.ktlystlabs.com Background information on MGM / FBI reports: https://www.reuters.com/technology/cybersecurity/fbi-struggled-disrupt-dangerous-casino-hacking-gang-cyber-responders-say-2023-11-14/ Related episode: organisational trust and AI implementation with Simon Berkler https://open.spotify.com/episode/6y8PMaVUnZVAR1hOAR15DN Related episode: accountability and invisible infrastructure with Sergiu Petean https://open.spotify.com/episode/4KcsZBDgFzkSuwQVihjNR5
🎙️ Simon Berkler, Co-Founder of The Dive 🎧 About this episode This episode of The In-Between Tech & Trust Podcast asks a question every leader is quietly facing: what does AI actually do to the trust inside your organization — and what does your trust culture do to AI? Simon Berkler, organizational development expert and co-founder of The Dive, argues that technology doesn't change organizations. It reveals them. The conversation is for leaders, HR professionals, and anyone navigating organizational transformation in the age of AI. 🧭 Episode overview Eva Simone Lihotzky speaks with Simon Berkler about why trust is not a soft skill but the structural condition that makes organizations work — and why that matters more than ever in the context of AI adoption. Drawing on systems theory, regenerative organizational design, and 20+ years of hands-on OD practice, Simon reframes the tech-and-trust debate: the question is not which AI tools to adopt, but what kind of organization you already are. Because AI, he argues, will act as a mirror — amplifying what's already alive, for better or worse. They explore how to lead through in-between moments when old logic is crumbling and new logic hasn't formed yet, why collective intuition may be the most underused organizational resource, and what it would mean to design governance structures built for uncertainty rather than against it. 🧩 Key themes discussed Why trust reduces social complexity — and what that means practically for organizational transformation AI as a mirror of organizational culture: how existing trust levels determine whether AI becomes augmentation or surveillance The difference between trust and probability — and why AI runs on the latter, not the former Leading through in-between spaces: how to change the rules while still playing the game Collective intuition as a strategic resource for navigating complexity, drawing on the work of organizational psychologist Peter Kruse The Stellar Approach: a regenerative OD framework for moving organizations from conventional to net-positive ways of working Why rhythm is the most overlooked asset in transformation Shifting organizational governance from optimizing for certainty to optimizing for uncertainty What "safe enough to try" looks like as a leadership stance in AI adoption 📥 References & further reading The Dive — Simon's organizational development consultancy: thedive.com Simon Berkler's personal site & writing: simon-berkler.de The Stellar Approach by Simon Berkler & Ella Lagé (2024): Amazon Niklas Luhmann, Trust and Power — systems theory foundation for the episode's framing of trust: Amazon Nora Bateson & the concept of Warm Data — the distinction between warm and cold data Simon references: warmdata.life Peter Kruse on collective intuition and complexity — the four ways of dealing with complexity Simon draws on: artsnext.ch summary
🎙️ Dr. Paul Elvers, Head of AI at Funke Mediengruppe 💬 Summary This week's episode of the in-between tech & trust podcast examines how AI is being used inside one of the largest media organizations in Germany, with a focus on trust, transparency, and day to day editorial practice - steered by Dr. Paul Elvers, Head of AI at Funke Medienhaus and podcast host Eva Simone Lihotzky. The conversation is for media specialists, editors, product leaders, and anyone working close to news production and consumption. The episode dives deep into the choices directly affecting credibility, audience trust, and the role journalism plays in a democratic society. 🎧 Episode overview In a detailed discussion, Dr. Paul Elvers walks through how AI actually shows up in newsroom workflows, separating real operational value from common misconceptions. Rather than debating whether AI should exist in journalism, the episode stays grounded in how it is governed, where human responsibility remains essential, and why naïve adoption is a bigger risk than cautious experimentation. The conversation also explores how audiences judge credibility in an environment flooded with synthetic content, and what media organizations can realistically do to maintain trust while adapting to new tools and distribution pressures. 🔍 Key themes discussed Why trust in AI comes from understanding systems and accountability, not blind confidence The difference between deliberate AI integration and careless, volume driven adoption How “AI slop” reflects a growing difficulty in judging what is trustworthy, not just content quality Using AI to automate necessary but unpopular newsroom tasks while keeping humans at the start and end The role of recognizable brands and journalists in sustaining audience trust What transparency about AI use looks like in real editorial workflows Why AI governance in media is iterative, shared, and never fully settled
🎙️ Iwona Fluda, expert for creativity & ethics 🧭 Opening This week's episode of the in-between tech & trust podcast examines how AI is reshaping creativity, trust, and responsibility in everyday work. If you work in creative fields, technology, or organizational leadership who are dealing with AI as a practical reality rather than an abstract future, then this podcast is for you. 🗣️ Episode overview Eva Simone Lihotzky is joined by creativity and ethics expert Iwona Fluda, founder of the Ministry for Creativity, Head of AI and Content Growth at Deamleaps and ambassador for the Royal Society for Arts, Manufactures and Commerce. Together, they unpack why trust in technology is eroding, how AI tools affect human thinking when cognition is outsourced, and why creativity cannot be reduced to speed or output. The discussion moves between individual responsibility, organizational shortcuts, and the ethical gaps that appear when inclusivity and long term design are treated as secondary concerns. 🧩 Key themes discussed Cognitive engagement and AI How relying on AI without active thinking weakens human cognition, drawing on research associated with the MIT Media Lab. Creativity under pressure Creativity as a historically essential survival skill, and why it remains structurally undervalued despite being central to innovation. AI as tool and disruptor The dual role of AI as a powerful collaborator for some and a driver of job loss for others, especially in creative and marketing work. Trust in technology and platforms Why skepticism, not trust, defines today’s relationship with technology and institutions, including content ecosystems like LinkedIn. Radical inclusivity by design The limits of add-on ethics programs and the need to build inclusivity into systems from the very beginning. Efficiency versus responsibility Organizational choices that favor short term gains over long term impact, even when frameworks like the EU AI Act already exist. Societal and existential risk Concerns about large scale job displacement and long term societal disruption, including references to thinkers such as Roman Jampolsky.
🎙️Prof. Dr. Heiko von der Gracht, Professor at the University of Krems Opening Episode 19 of the in-between tech & trust podcast explores how organizations can make better decisions under uncertainty through foresight and scenario planning. In conversation with Heiko von der Gracht, professor at the University for Continuing Education Krems and long-standing practitioner of foresight practices, the discussion looks at how trust, technology, and perception shape what leaders think is possible. It is especially relevant for people working with strategy, innovation, or long-term planning in fast-moving environments. 🧭 Episode overview The conversation examines foresight not as prediction, but as a practical discipline for stress-testing assumptions and improving choices when the future is unclear. Drawing on decades of research and applied work, Heiko reflects on why uncertainty feels overwhelming today, how media and digital systems influence our perception of risk, and why traditional planning often breaks down under rapid change. The episode also looks at how trust is being reshaped by scalable, anonymous technologies, and what this means for organizations trying to act responsibly and coherently over time. 🔍 Key themes discussed Why foresight is about decision quality, not forecasting outcomes The difference between actual uncertainty and how uncertain the world feels How complexity and speed interact to undermine linear planning Trust in digital environments shaped by anonymity, scale, and weak accountability Knowledge overload, misinformation, and the loss of shared reality Scenario planning as a strategic conversation rather than an analytical exercise Empirical evidence that sustained foresight investment improves performance The discussion also draws on Heiko’s involvement in global foresight and governance contexts, including work connected to the World Economic Forum and UNESCO, grounding the conversation in both research and lived practice.
🎙️Grisha Pavlotsky, Chief Transformation Officer at Miro Opening paragraph This episode shares a conversation between Grisha Pavlotsky, CTO of Miro, and Eva Simone Lihotzky. It examines trust as a practical design problem in teams, AI systems, and everyday decision-making. The conversation is for leaders, builders, and parents trying to make sense of how judgment, accountability, and authority shift when AI becomes part of how work and learning happen. It focuses on what needs to be made explicit - intent, guardrails, and decision logic - rather than assumed. Episode overview Grisha draws on his work leading transformation at Miro and his experience raising four children to explore how trust holds - or breaks - when information is abundant and increasingly synthesized. The discussion moves between organizations and families, treating them as parallel systems facing the same challenge: people are no longer short on answers, but on the ability to judge, contextualize, and disagree productively. Along the way, the episode questions current education models, critiques optional AI adoption, and argues that trust depends less on confidence and more on transparency about how decisions are made and who remains accountable. Key themes discussed Trust as alignment on intent plus visibility into decision frameworks, not just emotional safety How AI amplifies confidence without guaranteeing expertise, complicating collaboration Why probabilistic systems require clear guardrails, not vague goals The shift from producing synthesis to judging and challenging synthesized viewpoints Education moving from teaching facts to navigating competing narratives Identity and ego as the real blockers in large-scale transformation Leadership responsibility in making AI adoption mandatory rather than optional Parenting and organizational leadership as the same sense-making problem at different scales A recurring reference is the idea - attributed to Satya Nadella - that trust is built through consistency over time, and what that consistency demands in an AI-mediated world.
Opening This solo episode of The In-Between Tech & Trust Podcast reflects on conversations from Davos and what they reveal about where tech, politics, and trust are heading into 2026. It’s for leaders, operators, and policy-adjacent roles who are trying to make sense of AI adoption beyond tooling. The focus is on what actually changes inside organizations, institutions, and collaborations when AI becomes infrastructure. 🎧 Episode overview Eva Simone Lihotzky unpacks four threads that kept resurfacing across discussions with tech, political, and business leaders: agentic AI systems, the politics of technology, sovereignty, and the future of collaboration and trust. Rather than reporting speeches, the episode explores tensions beneath the surface - why organizations feel urgency but struggle to act, how AI exposes institutional weaknesses instead of fixing them, and why governance, infrastructure, and responsibility are now inseparable. The episode moves between business realities and geopolitical dynamics, asking what it really means to design AI-driven organizations, who shapes the rules when tech and politics are interwoven, and how dependence on a small set of platforms reshapes power, accountability, and autonomy. 🔍 Key themes discussed Agentic AI systems and why they force a rethink of organizational design AI adoption as a platform shift, not a tool rollout The gap between AI urgency and practical implementation inside companies World models vs. specialized models and why both matter Interoperability as an unsolved infrastructure problem Tech as both upstream and downstream of politics Sovereignty across compute, infrastructure, data, operations, and talent Europe’s position in an AI-driven power landscape Why collaboration now depends on explicit commitments, not assumptions How trust becomes harder - and more necessary - as systems scale
🎙️ with Dr. Marc Roman Franke, Partner & Associate Director AI and digital transformation at BCG 💬 Opening Eva Simone Lihotzky speaks with Marc Roman Franke, Partner & Associate Director AI and digital transformation at BCG, about how trust is built - or lost - during AI transformation inside large organizations. The conversation is for leaders, product owners, and transformation teams trying to move beyond pilots and into real operating change. It focuses on why execution, governance, and organizational choices determine whether AI creates value or stalls. 🎤 Episode overview Drawing on large-scale research and implementation experience, the episode examines why only a small share of companies see meaningful returns from AI. Franke argues that the main constraints are not models or tools, but leadership alignment, operating models, and how trust is earned through delivery. The discussion moves from the limits of “AI-ready” programs to what it means to become “AI-first,” including the rise of agentic AI, unmanaged security risks, and why postponing Responsible AI eventually blocks scale. 🎯 Key themes discussed Trust as a practical outcome of reliable execution and visible value, not long-term promises Why most AI value depends on people, organization, and leadership rather than algorithms What separates the small minority of companies that capture real AI value from the rest The difference between experimenting with AI and redesigning the business around it How agentic AI changes accountability, decision rights, and human–AI collaboration Governance as an enabler of adoption and safety, not a compliance afterthought Security and third-party risks that grow as AI scales When Responsible AI can be delayed—and why it becomes a blocker later 🤝🏻 Referenced during the conversation: BCG, MIT, SAP S/4HANA, GDPR, and Steve Jobs.
🎙️Lior Oren, Chief Technology Officer at Replika A conversation on how emotionally intimate AI systems are built, monitored, and held together under real-world constraints. 🎧 Opening This episode explores how trust is built, measured, and sometimes strained in AI systems designed for emotionally intimate conversations. It’s a technical and ethical discussion for people working on conversational AI, product infrastructure, and safety in systems that users form real attachments to. The focus stays on operational reality - what engineers actually face when AI moves from tools to companions. 🔍 Episode overview Eva Simone Lihotzky speaks with Lior Oren about what it means to run AI companions at scale, where user trust is not an abstract principle but a daily KPI. Drawing on his experience as CTO of Replika and prior work on integrity teams at Meta, Lior explains how unpredictability, observability, and emotional reliance shape engineering decisions. The conversation examines tensions between flexibility and stability, innovation and guardrails, and regulation and lived product reality. Rather than future speculation, it stays grounded in how teams design memory, user control, and safety systems when conversations themselves are the product. 🧩 Key themes discussed Trust treated as a measurable success metric, not a philosophical goal Why observability is essential in statistical, non-deterministic AI systems Guardrails as part of core infrastructure, similar to security or reliability Emotional attachment influencing uptime, priorities, and team culture User agency through transparency, memory control, and conversational steering The risk of breaking “tone” and continuity when models change Limits of regulation and the trade-offs inherent in statistical safety systems
Producer's note
Steal the structure. Not the show.
Keep the useful structure, then change the audience, point of view, and voice until the idea is unmistakably yours.
