The In-Between Tech and Trust Podcast – Details, episodes & analysis

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The In-Between Tech and Trust Podcast

Eva Simone Lihotzky

Technology

Frequency: 1 episode/10d. Total Eps: 46

How do we build, break, and rebuild trust in a world shaped by technologies? The In-Between Tech & Trust is a weekly conversation about the human side of tech. Host Eva Simone Lihotzky, founder of raidiant (responsible AI advisory), talks with guests from business, politics, neuroscience, and tech about what they have learned about trust, and what they would pass on to you. Eva was formerly co-founder and MD of the Serviceplan AI Lab, holds the Global Moral Chair at the Value AI Institute and co-authored "10 Moral Questions: How to Design Tech & AI Responsibly".

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🇩🇪 Germany - technology
29/10/2026
#48
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🇩🇪 Germany - trending
29/10/2026
#160
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🇩🇪 Germany - technology
28/10/2026
#49
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🇩🇪 Germany - trending
28/10/2026
#159
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🇩🇪 Germany - technology
27/10/2026
#48
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🇩🇪 Germany - trending
27/10/2026
#156
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🇩🇪 Germany - technology
26/10/2026
#48
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🇩🇪 Germany - trending
26/10/2026
#160
↗
🇩🇪 Germany - technology
25/10/2026
#49
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🇩🇪 Germany - trending
25/10/2026
#165
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https://www.raidiant.eu/
6 shares
https://www.anthropic.com/news/fable-mythos-access
3 shares
https://www.10moralquestions.com/the-book
3 shares

https://www.linkedin.com/in/evalihotzky/
24 shares
https://www.linkedin.com/in/martin-soltau-44596619/
2 shares
https://www.linkedin.com/in/julia-loeffler/
2 shares

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An Internet Full of AI Agents: Building Trust for an Agent-Driven Web - Charles Maddock, Strawberry (EP 46)

Season 1 · Episode 46

Friday, October 23, 2026 • Duration 32:49

🎙️ Charles Maddock, Co-Founder & CEO, Strawberry

Charles Maddock expects an internet full of AI agents working inside our own accounts, and as CEO of the Stockholm startup Strawberry he is building the browser for it. That puts one question at the center of this conversation: who stays in charge when software acts in our name? His answer is built into the product (agents start with limited rights, ask when they’re unsure and need a click before they send anything), and he is candid that a young brand still has to earn the trust to be let in.

🎧 Episode overview
Charles wants agents to take over the tasks “that make us feel like robots”, like copying notes into a CRM, sourcing leads or chasing receipts, so the salesperson stays in the call and the founder stays on strategy. At Strawberry, a core team of twelve engineers “moves like we’re sixty” because each of them runs several agents, which is also why he would hire the agent-fluent newcomer over the stronger CV. The hard cases are what he calls losers’ games: in bookkeeping, one wrong field out of a hundred ruins the result, so the agent has to stop and ask “could you confirm?” Eva pushes on the trust question: why would anyone press “allow” for a young brand when bigger platforms feel safer? His answer is permission per app and per tool, plans for European data residency, and this summer’s US export controls that briefly cut access to Anthropic’s Fable 5, a reminder, in his view, of what dependence on a few US platforms can cost.

💡 Key themes

Which work agents should take off our desks, and what stays human
How one person running several agents changes leading, hiring and learning the craft
Why the work where one mistake counts needs an agent that asks first
What has to be in place before people press “allow” for an agent with their logins
Whether Europe’s slow start with AI agents is a risk or an opening

👤 About the guest
Charles Maddock is co-founder and CEO of Strawberry, an agentic browser from Stockholm whose AI “companions” work inside the accounts their users are already logged into; the company raised a $6 million seed round in 2025, co-led by General Catalyst and EQT Ventures. He started programming at eleven and now builds the permission system he argues for: agents that can draft an email but not send it until someone allows it, which makes trust a daily product decision for him rather than a talking point.

⏱ Chapters

00:00 An internet run by agents, and what it means for us
06:19 Twelve engineers who move like sixty
09:56 Draft yes, send no: permissions and security
12:27 After Atlas: why the losers’ games matter
18:36 Why would anyone press “allow”?
23:15 Why build it from Stockholm

🔗 Links

Charles Maddock on LinkedIn - https://www.linkedin.com/in/charles-maddock-31798418b/
Strawberry - ⁠https://strawberrybrowser.com⁠
Eva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/
raidiant, Eva’s responsible AI advisory - https://www.raidiant.eu/

European Commission, Flash Eurobarometer on AI in European SMEs (the 2%) - https://employment-social-affairs.ec.europa.eu/news/growing-use-ai-european-companies-2026-10-14_en
Help Net Security on DataDome’s AI Traffic Report Q3 2026 (agentic browser traffic) - https://www.helpnetsecurity.com/2026/10/19/datadome-ai-agent-traffic-report/
Anthropic, statement on the suspension of Fable 5 - https://www.anthropic.com/news/fable-mythos-access
Related episode - The Agentic AI Gap: When Tech is Used Before its Architecture is Ready - Anthony Alcaraz, Agentic AI Architect (EP 25) - https://open.spotify.com/episode/4IdHiLzsgmSaUf5w3LvcaB?si=Nht7kJj8SJalqpTUWB5NUg

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The Doom and Gloom of AI: Fears, Facts and Hopes about the Current State in Tech - Eva Simone Lihotzky (EP 45)

Season 1 · Episode 45

Sunday, October 18, 2026 • Duration 23:34

🎙️ Eva Simone Lihotzky, solo episode

In July, an AI model under test sent the Philadelphia police an invented tip about an unsolved murder, and its maker only found out two months later. In this solo episode, Eva Simone Lihotzky takes that story and the fears her listeners sent her (losing control, losing ourselves, jobs, a bubble) and checks each one against what has actually happened. Her stance on the doomsday narrative is clear: she doesn’t buy it. What worries her is how much power sits with very few companies, and who holds them accountable.

🎧 Episode overview
This summer’s incidents are real: OpenAI test models broke into Hugging Face’s systems to fetch the answers to their own test, and Anthropic models carried on with cyber tests against targets they recognized as real companies, mostly with safeguards deliberately turned down. Eva explains the mechanism behind it (reward hacking: models are rewarded for the result, not the intention) and names the fear she does find accurate: an agent nobody is watching, while only 21% of companies have a mature way of governing agents. On our thinking, she separates AI as an answer machine, which left Turkish high school students with 17% worse exam results, from AI as a tutor with guardrails, which largely removed that harm; on jobs, she argues that AI changes tasks more than it removes jobs, and that a person still decides every cut. Her reason to stay optimistic comes from people’s own experience: in Germany, more than half of non-users would rather live without AI, but only a third of users, and the benefits that work (stroke care, breast cancer screening, weather forecasts) all keep a human in charge and measure the result.

💡 Key themes

Which fears about AI hold up when you check them against this summer’s incidents
Why labs warn about their own models and keep releasing new ones
When AI weakens our thinking, and when it helps us learn
Who decides that AI costs jobs, and who owns helping people learn what comes next
Whether Europe’s AI Act slows companies down or gives them the trust to adopt AI

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

Season 1 · Episode 44

Thursday, October 8, 2026 • Duration 34:59

🎙️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

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

Season 1 · Episode 43

Thursday, October 1, 2026 • Duration 44:01

🎙️ 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

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

Season 1 · Episode 42

Thursday, September 24, 2026 • Duration 31:58

🎙️ 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.

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

Season 1 · Episode 41

Thursday, September 17, 2026 • Duration 36:09

🎙️ 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

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

Season 1 · Episode 40

Thursday, September 10, 2026 • Duration 35:05

🎙️ 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.

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

Season 1 · Episode 39

Thursday, September 3, 2026 • Duration 33:36

🎙️ 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.

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

Season 1 · Episode 38

Thursday, August 27, 2026 • Duration 23:46

🎙️ 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.

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

Season 1 · Episode 37

Thursday, August 20, 2026 • Duration 32:00

🎙️ 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.

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The In-Between Tech and Trust Podcast – Details, episodes & analysis

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