
Free Daily Podcast Summary
by Eva Simone Lihotzky
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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🎙️ Christopher Craig, AI GTM Startups Lead Nordics & DACH, Google Cloud | Founder & Angel InvestorIn February, new AI agents wiped about a trillion dollars off software stocks within days; by May, they had rebounded. Christopher Craig, who works with AI startups at Google Cloud and invests in founders on the side, sees both moves up close: software is not dead, he says, but it may lose the users who used to log in. And if a team of five can now build what took fifty, what earns his trust is what is hard to copy: the founders’ conviction, the data they own and the infrastructure underneath (chips, bandwidth, energy).🎧 Episode overviewChris starts from the builder: we are all “in a way a software engineer now”, a company idea can be built in four or five days, and AI gets a product “eighty, eighty-five percent there” before a person has to understand and orchestrate the rest. For SaaS, that cuts both ways: he expects software to go “headless”, opened up to AI labs, with the risk that vendors turn into database companies nobody visits. Eva brings in Alphabet’s worst day on the stock market, the day before the recording, and Chris reads it as short term, points to AI demand he sees rising, and still names the open question himself: “Do we overshoot that?” The next bottlenecks, in his view, sit underneath: bandwidth in data centers (the reason he invested in the Zurich photonic chip company Lightium, “the plumbing in a data center”) and energy, where he bets the market will outweigh local resistance. What sets people apart, he says, has not changed: founders with conviction “to the point where it’s like insane”, and the habit of choosing carefully what to read.💡 Key themesWhether software is dying or losing only the screen people log intoWhat a person still adds when AI gets a product most of the wayWhether the AI spending pays off, or the industry overshootsWhy the next bottlenecks are bandwidth and energy, not only chipsWhat still sets builders apart when everyone can build👤 About the guestChristopher Craig works with AI-native, robotics and deep tech startups at Google Cloud across DACH and the Nordics, and invests in founders through his own angel platform, Blue Trail. He came to Zurich in 2020 after five years in San Francisco, including at Uber, and today he stands on two sides of the AI build-out: selling the compute to startups, and backing the hardware and energy companies that compute depends on.⏱ Chapters00:00 After the outage: AI demand and teams that start from AI07:20 Five people doing the work of fifty14:20 SaaSpocalypse, or software going headless?16:50 Alphabet’s worst day, and three model families on one platform22:30 The plumbing underneath: chips, bandwidth, energy28:30 Everyone a builder: what still sets you apart🔗 LinksChristopher Craig on LinkedIn - https://ch.linkedin.com/in/chris-craigEva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/raidiant, Eva’s responsible AI advisory - https://www.raidiant.eu/Google Cloud - https://cloud.google.comGoogle for Startups Cloud Program - https://cloud.google.com/startup/aiBlue Trail - https://bluetrailventures.com/Lightium - https://lightium.com/ Novele - https://www.novele.comMicroAGI - https://www.microagi.aiRelated episode - Keeping Quantum Momentum: How Companies Stay Ready for a Computing Wave That Is Yet to Arrive - Christopher Trummer (EP 44) - https://open.spotify.com/episode/6Of8mRJG9KDCceSrODhTD6
🎙️Nils Giese, CEO, Edelman GermanyOnly 8% of people in Germany believe the next generation will be better off, and Nils Giese, CEO of Edelman Germany, calls it the most shocking number in his firm’s Trust Barometer. Behind it he sees trust retreating onto “social islands”: small circles of people like us, now with high walls around them. That leaves leaders with a hard job (bringing people across those walls while asking them to change, AI included), and Nils is open that he isn’t very optimistic about the months ahead.🎧 Episode overviewEdelman’s research breaks trust into five parts (ability, dependability, integrity, purpose and personal relevance), and Nils argues the human ones weigh more than competence, even in a country that likes to trust its engineering; for him personally, dependability and integrity come first when times are uncertain. The 8% tells him the contract between generations is “just collapsing”, and when Eva brings in KfW’s finding that a third of German Mittelstand firms postponed or scaled back their 2026 investments, he reads it the same way: not a lack of money or ideas, but how hard it has become to imagine the future. His answer is the employer as bridge builder, the most trusted institution in Germany because of the little word “my”. Eva pushes on how leaders can do that when everyone, Gen Z first, feels overwhelmed, and Nils points to what transformation stories leave out: empathy, and the rule that what the recipient hears matters more than what the sender says. On AI, he describes the fear in large companies as diffuse rather than experienced, sees trust rise after one good experience, and says AI “had the worst PR agency in the world”.💡 Key themesWhat trust is made of, and why honesty can outweigh competenceHow companies invest in a future only 8% expect to be betterWhether employers can bridge the social islands people retreat toWhat AI transformation loses when it speaks only to the rational caseWhere trust can grow again: small steps, close to home👤 About the guestNils Giese is CEO of Edelman Germany and leads Edelman’s healthcare marketing across EMEA; he joined the firm in 2021 to run its German healthcare business, after years in strategy at Saatchi & Saatchi. His firm has measured trust for 26 years through the Edelman Trust Barometer, and Nils reads those numbers as someone who has to move people through change himself: when he joined, he described his work as trusted, active and creative dialogue, long before the AI debate.⏱ Chapters00:00 What trust is made of06:34 Only 8% expect a better future11:55 Social islands with high walls16:40 Overwhelmed, and the missing empathy22:46 AI as a diffuse fear27:14 Not optimistic yet: start small, start local🔗 LinksNils Giese on LinkedIn - https://www.linkedin.com/in/nils-giese-898058151/Edelman Germany - https://www.edelman.com/de/deEva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/raidiant, Eva’s responsible AI advisory - https://www.raidiant.eu/Edelman Trust Barometer 2026, Germany - https://www.edelman.com/de/de/trust/2026/trust-barometerEdelman Trust at Work 2026 - https://www.edelman.com/newsroom/richard-edelmans-6am-blog/trust-at-work-2026Edelman Flash Poll: Trust and Artificial Intelligence at a Crossroads - https://www.edelman.com/insights/familiarity-breeds-trust-in-aiKfW-Mittelstandspanel 2026 - https://www.kfw.de/Über-die-KfW/Newsroom/Aktuelles/Pressemitteilungen-Details_910272.html Related episode - Two Fears Behind Every AI Transformation - Dr. Charlotte Blum (EP 31) - https://open.spotify.com/episode/5A0aUErqMyqTKjBQqOuGaD?si=HWFJpD3VRhqquH1hpQ0WXQ
🎙️ Charles Maddock, Co-Founder & CEO, StrawberryCharles 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 overviewCharles 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 themesWhich work agents should take off our desks, and what stays humanHow one person running several agents changes leading, hiring and learning the craftWhy the work where one mistake counts needs an agent that asks firstWhat has to be in place before people press “allow” for an agent with their loginsWhether Europe’s slow start with AI agents is a risk or an opening👤 About the guestCharles 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.⏱ Chapters00:00 An internet run by agents, and what it means for us06:19 Twelve engineers who move like sixty09:56 Draft yes, send no: permissions and security12:27 After Atlas: why the losers’ games matter18:36 Why would anyone press “allow”?23:15 Why build it from Stockholm🔗 LinksCharles Maddock on LinkedIn - https://www.linkedin.com/in/charles-maddock-31798418b/Strawberry - https://strawberrybrowser.comEva 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_enHelp 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-accessRelated 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
🎙️ Eva Simone Lihotzky, solo episodeIn 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 overviewThis 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 themesWhich fears about AI hold up when you check them against this summer’s incidentsWhy labs warn about their own models and keep releasing new onesWhen AI weakens our thinking, and when it helps us learnWho decides that AI costs jobs, and who owns helping people learn what comes nextWhether Europe’s AI Act slows companies down or gives them the trust to adopt AI👤 About the hostEva Simone Lihotzky hosts The In-Between Tech & Trust and as the founder of raidiant, she advises European companies and boards on responsible AI adoption. She previously co-founded the Serviceplan AI Lab and led it as Managing Director, and she is co-author of “10 Moral Questions: How to Design Tech & AI Responsibly”. This episode is built on the questions her listeners sent her on Instagram and LinkedIn.⏱ Chapters00:00 An AI’s false tip to the police, and where Eva stands02:53 From listeners’ questions to agents that left their tests08:42 Why the warnings got so loud10:18 What AI does to who we are, how we think and our jobs14:46 Bubble, power and Europe’s rulebook19:10 Why Eva stays optimistic, and what to do now🔗 LinksEva Simone Lihotzky on LinkedIn - https://www.linkedin.com/in/evalihotzky/raidiant, Eva’s responsible AI advisory - https://www.raidiant.eu/Anthropic, Investigating unintended model actions (the police tip) - https://www.anthropic.com/research/investigating-unintended-model-actionsTechCrunch, OpenAI says Hugging Face was breached by its pre-release models - https://techcrunch.com/2026/07/21/openai-says-hugging-face-was-breached-by-its-pre-release-models/Deloitte, State of AI in the Enterprise 2026 - https://www.deloitte.com/us/en/about/press-room/state-of-ai-report-2026Bitkom, KI macht Spaß - aber nicht allen (May 2026) - https://www.bitkom.org/Presse/Presseinformation/KI-macht-Spass-aber-nicht-allenThe New York Times editorial board, AI is not above the law - https://www.nytimes.com/2026/10/10/opinion/ai-companies-liability-laws.html Related episode - Two Fears Behind Every AI Transformation - Dr. Charlotte Blum (EP 31) - https://open.spotify.com/episode/5A0aUErqMyqTKjBQqOuGaD?si=inpGls9wQoOpsuMZaBmDsg
🎙️with Christopher Trummer, MD Venture Lab Quantum / Semicon, TUM Venture LabsAround 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 themesWhich parts of quantum are ready today, and how far to trust encryption that is in use but not yet provenWhy the first quantum promise failed, and what makes the second one more solidHow companies keep momentum and board support while progress stays slowWhether quantum computing ends up with a few suppliers, the way AI didWhy 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.⏱ Chapters00:00 Quantum beyond the computer05:18 The algorithm that could break encryption09:02 Why quantum won't have a ChatGPT moment14:26 After the first promise fell through24:31 Europe's missing growth capital31:26 Drugs, fertilizer and superposition🔗 LinksChristopher 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.pdfNIST post-quantum cryptography standards - https://csrc.nist.gov/projects/post-quantum-cryptographyRelated episode - Energy From Orbit: Can We Trust Power Beamed From Space? - Martin Soltau (EP 42) - [LINK: Eva adds]
🎙️ Moran Cerf, Neuroscientist and Professor, Columbia Business SchoolMoran 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 overviewMoran'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 themesWhy AI can read and persuade people better than people can, and why we don't noticeWhen a human name for an AI agent helps a team, and when it distorts a decisionWhat the AI backlash has inherited from fifteen years of social mediaWhich choices to trust AI with, and how that trust spills over to the ones that define usWhether control handed over for convenience comes back when life changes👤 About the guestMoran 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.⏱ Chapters00:00 The feedback loop AI can't join05:46 AI reads attraction, then learns to persuade16:01 From neural implants to brain-like AI29:22 Trust it with groceries, not with a partner37:07 Giving up control, and the retwin42:29 In-between moments🔗 LinksMoran 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-cerfMoran Cerf's website - https://www.morancerf.com/Anthropic research Moran describes - [LINK: Anthropic study]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
🎙️ with Martin Soltau, Co-CEO, Space SolarSolar 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 overviewIt 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 themesWhy a grid built on free sunshine and free wind still delivers expensive electricityWhether public trust can be earned before the first satellite flies, or only afterwardsWhat wireless power changes about energy security when undersea cables are already being targetedWhether governments that fund this will accept standards letting a rival's satellite use their receiver👤 About the guestMartin 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.⏱ ChaptersTested 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 ...")🔗 LinksMartin 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.ukInternational Telecommunication Union - https://www.itu.intRelated episode - Sten Saluveer on what decides AI trust in Europe - https://open.spotify.com/episode/0gPKehnoNppMY0y3Jvdry0
🎙️ Sten Saluveer, Growth & Innovation, TeliaWhat 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 overviewSten 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 themesWhether a state can make itself agent-driven and keep the citizen in controlWhy holding cybersecurity satisfaction at today's level counts as ambitionWhat Europe's own category could be when it stops measuring itself in gigawattsThe generational split on AI that surfaced at Cannes, and what it demands of leadersWhether a telco can become the trusted digital partner of the AI economy👤 About the guestSten 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🔗 LinksSten 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/eraEstonia's digital state agenda - https://digital-skills-jobs.europa.eu/en/initiatives/national-strategies/estonia-estonian-digital-agenda-2030Related episode - 'Tech and Democracy with Nexus Politics' https://open.spotify.com/episode/3WVnBsaz3LfFPwn6xsX1N6
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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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