The in-between tech and trust podcast

🎙️ with Magnus Strobel, Co-Founder and CEO of Nexus PoliticsTrust 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 overviewThis 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 themesWhy 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 neutralityMapping 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 trustTech as a tool that can repair democratic trust or deepen the damage, depending on who uses it and how🤝 About the guestMagnus 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⛓️‍💥 LinksNexus Politics: www.nexuspolitics.orgMagnus Strobel LinkedIn: https://www.linkedin.com/in/strobelmagnus/ Audrey Tang / Taiwan digital democracy: https://www.demnext.org/people/audrey-tangRebuild conference, Copenhagen: https://www.rebuild.net Related episode - Rebuilding Trust: Tech, Politics and Entrepreneurial Leadership (EP 06)

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 overviewAnthony 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 discussedThe shift from reactive to agentic systems, and what trust has to carry nowWhy most enterprise data is missing the why behind decisionsTool poisoning and the new attack surface for agentsThe empowerment gap between business knowledge and technical capabilityGraph architecture as the control layer for agentic reasoningWhy human-in-the-loop can be a refusal to transform👤 About the guestAnthony 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🔗 LinksAnthony 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=oGo2JPHNTeCTxbqkNXDJMwEva Simone Lihotzky's 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 discussedWhy security teams are structurally rewarded for fighting fires rather than preventing themThe organisational gap between threat intelligence and detection - and why it persists even in well-resourced teamsWhat data provenance means in practice, and why it matters more than speed when using AI in securityHow attackers learn your defences faster than you can adapt - and what the military analogy revealsWhy trust online currently feels, in Assaf's words, like a pipe dream👤 About the guestAssaf 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🔗 LinksAssaf Kipnis https://www.linkedin.com/in/assafkipnis/KTLYST Labs https://www.ktlystlabs.comBackground 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/6y8PMaVUnZVAR1hOAR15DNRelated episode: accountability and invisible infrastructure with Sergiu Petean https://open.spotify.com/episode/4KcsZBDgFzkSuwQVihjNR5

🎙️ 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 overviewIn 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

🎙️Prof. Dr. Heiko von der Gracht, Professor at the University of KremsOpeningEpisode 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 overviewThe 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 discussedWhy foresight is about decision quality, not forecasting outcomesThe difference between actual uncertainty and how uncertain the world feelsHow complexity and speed interact to undermine linear planningTrust in digital environments shaped by anonymity, scale, and weak accountabilityKnowledge overload, misinformation, and the loss of shared realityScenario planning as a strategic conversation rather than an analytical exerciseEmpirical evidence that sustained foresight investment improves performanceThe 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.

OpeningThis 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 overviewEva 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 discussedAgentic AI systems and why they force a rethink of organizational designAI adoption as a platform shift, not a tool rolloutThe gap between AI urgency and practical implementation inside companiesWorld models vs. specialized models and why both matterInteroperability as an unsolved infrastructure problemTech as both upstream and downstream of politicsSovereignty across compute, infrastructure, data, operations, and talentEurope’s position in an AI-driven power landscapeWhy collaboration now depends on explicit commitments, not assumptionsHow trust becomes harder - and more necessary - as systems scale

🎙️Lior Oren, Chief Technology Officer at ReplikaA conversation on how emotionally intimate AI systems are built, monitored, and held together under real-world constraints.🎧 OpeningThis 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 overviewEva 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 discussedTrust treated as a measurable success metric, not a philosophical goalWhy observability is essential in statistical, non-deterministic AI systemsGuardrails as part of core infrastructure, similar to security or reliabilityEmotional attachment influencing uptime, priorities, and team cultureUser agency through transparency, memory control, and conversational steeringThe risk of breaking “tone” and continuity when models changeLimits of regulation and the trade-offs inherent in statistical safety systems

🎙️ with Gifty Enright - author, speaker and expert on women's leadership Summary In this episode of The In-Between Trust Podcast, Eva Simone Lihotzky sits down with Gifty Enright - author, speaker, and women’s leadership expert - to unpack a tension many of us feel but rarely articulate:In a hyper-visible world, we are more “searched” than ever, and yet we feel less seen.Gifty exposes the invisible emotional infrastructure that holds workplaces together - the labor of noticing, soothing, anticipating, and absorbing complexity - work disproportionately done by women and almost never acknowledged as expertise.Together, Eva and Gifty explore why trust is less about performance and more about relational safety, how leaders can cultivate embodied awareness in an age of tech, and why empathy can’t be automated — even by the most advanced AI.The conversation moves from gendered trust patterns to the redesign of leadership for the AI era, offering a grounded reminder: Your body knows the truth long before your mind catches up. If you lead teams, build tech, or are navigating emotional load at work, this episode will challenge how you think about trust, resilience, and the limits of technology.Takeaways Trust is shifting from task-based to relational — people follow leaders who create emotional safety.Technology blurs boundaries and accelerates burnout unless paired with embodied leadership.Emotional labor — often carried by women — is a hidden operating system of organizations.AI can pattern-match, but it cannot feel; empathy remains a human capability.Leaders must regulate their internal systems to earn trust externally.Women are socialized to earn trust; men are often socialized to assume it.Stillness is not a luxury — it’s a leadership technology.Trust grows in the pause; speed erodes nuance.Tech should augment humanity, not override it.Soundbites “Tech can predict patterns, but it can’t feel your pain.”“Women aren’t trusted by default — they’re conditioned to earn it.”“Stillness is a leadership tool, not a luxury.”“The pause is where trust breathes.”Chapters 00:00 — What Trust Really Means in Today’s Workplace02:06 — Tech Acceleration & the Cost to Human Wellbeing04:28 — The Hidden Burden: Emotional Labor in Organizations07:50 — Why AI Can’t Replace Empathy12:17 — Embodied Intelligence: Leading from the Body, Not Just the Mind15:59 — Self-Trust vs. System Trust18:55 — Gendered Dynamics of Trust and Power22:02 — Rethinking Leadership for the AI Age24:07 — Human Evolution, Work, and What Comes NextKeywordstrust, emotional labor, leadership, AI limits, embodied intelligence, workplace wellbeing, gender dynamics, empathy, psychological safety, organizational culture, women in leadership

🎙️ With Roger Spitz – Foresight Strategist, Techistentialist & President of the Disruptive Futures InstituteSummaryIn this episode of the in-between trust podcast, Eva Simone Lihotzky speaks with Roger Spitz, a global foresight strategist and founder of the Disruptive Futures Institute. Together, they explore the deep relationship between trust, agency, and technology, and why decision-making in complex systems requires more than control.Roger introduces the concept of techistentialism - a lens through which to understand how humans and algorithms now share the terrain of choice, risk, and consequence. This conversation invites us to rethink the foundations of leadership, the illusion of predictability, and the necessity of awareness, resilience, and anticipatory thinking in an era shaped by disruption.🔑 TakeawaysTrust is a fundamental need, not a luxuryAgency is the basis for ethical and effective decisionsTechnology and human decision-making are inseparableAwareness of complexity changes how we lead and respondAnticipatory thinking is essential for navigating uncertaintyControl is incompatible with complex systemsAntifragility allows organizations to benefit from shocksAgility enables more resilient leadership and communicationAI can enhance trust — if used in the right contextsDelegating decisions to machines can erode human capacity🎙️ Sound Bites"Control is incompatible with complex systems.""Antifragility means benefiting from shocks.""Foresight is a form of intelligence."⏱️ Chapters00:00 Introduction to Trust and Agency02:17 The Role of Trust in Decision Making04:41 Understanding Technology and Trust08:03 Incorporating Techistentialism in Business11:24 Awareness, Agency, and Anticipation17:14 Navigating Control in Complex Systems23:00 Agility in Communication and Leadership28:56 The Impact of Technology on Systems33:49 AI’s Role in Strengthening Trust39:42 In-Between Moments and Conclusion🔭 Keywordstrust, agency, technology, decision making, tech essentialism, complexity, AI, leadership, communication, resilience💻 Linksin-between trust on Instagram: @inbetween_trustMore about the disruptive futures institute: https://www.disruptivefutures.org/

🎙️ With Andrea Schlüter – Head of Strategy, Operations and PartnershipsSummaryIn this episode of the in-between trust podcast, Eva Simone Lihotzky speaks with Andrea Schlüter about the evolving relationship between trust and technology, with a special focus on AI systems, certification, and governance. They explore how trust is designed into systems, how regulation can become a foundation for innovation, and the challenges of aligning technical complexity with cultural context. Andrea shares insights from her work at the TÜV AI Lab, where building frameworks for trustworthiness in AI is more than compliance—it’s about shaping the future of safe, transparent, and ethical technology.🔑 TakeawaysTrust is about consistency between claims and outcomesAI requires verifiable trust, not just promisesCertification provides measurable trust and a market advantageRegulation can enable innovation by reducing fear and ambiguityCultural dimensions shape how we interpret and build trust in techA common language is crucial for aligning diverse stakeholdersEurope has an opportunity to lead in trustworthy AI frameworksTransparency and ethics must be embedded by designGovernance is a cultural task as much as a technical oneBuilding trust in AI is an ongoing, collective responsibility🎙️ Sound Bites"Trust is a lot about consistency.""Trustworthiness by design is key.""We need a common language among experts."⏱️ Chapters00:00 Understanding Trust in Technology03:09 The Role of AI in Trustworthiness06:10 Building Trust through Certification08:59 Navigating the AI Ecosystem12:05 The Challenge of Trust in AI Systems14:48 Cultural Aspects of Trust in AI17:41 Establishing a Common Language for AI20:44 The Importance of Diverse Perspectives23:58 Practical Benefits of AI Taxonomy26:41 Reflections on Trust and Innovation🔭 Keywordstrust, technology, AI, certification, trustworthiness, TÜV, AI Act, innovation, ethics, culture💻 Linksin-between trust on Instagram: @inbetween_trustMore about TÜV AI Lab: https://www.tuev-lab.aiMore about Andrea Schlüter: https://www.linkedin.com/in/andrea-schlueter/

SummaryIn this episode of the in-between trust podcast, Eva Simone Lihotzky explores innovation sovereignty with the generative AI and cloud expert Sergiu Petean. Their conversation moves through topics about bravery in decision-making, technological sovereignty, and the potential of open-source solutions to drive European collaboration. Together, the speakers reflect on how trust underpins innovation, leadership, and value creation — and why we must treat technology not as a commodity, but as a shared, strategic asset. This episode is a call to act with urgency, integrity, and clarity in shaping the digital and political systems of tomorrow.🔑 TakeawaysTrust is the foundation of quality in relationshipsBuilding a culture of trust requires hard conversationsBravery enables authentic decisions and personal growthSovereignty is key to innovation and digital self-determinationOpen source can foster collaboration and shared progress in EuropeRegulation helps shape ethical tech innovationTrust is essential for European collaborationTechnology can be connective — or divisiveLeaders need technological literacy for future decisionsEurope must act now on digital sovereignty🎙️ Sound Bites"Trust for me is the foundation of quality.""We need to be more courageous."⏱️ Chapters00:00 The Foundation of Trust05:11 Understanding Sovereignty09:13 Cultural Sovereignty and Innovation11:06 The Role of Regulation in Sovereignty13:09 Building Trust in Europe15:10 Technology as a Connector or Divider17:37 The Power of Open Source19:27 Creating Communities in Open Source22:42 Leadership for the Future26:27 The Value of Technology in Organizations29:39 In-Between Moments and Reflections💻 Linksin-between trust on Instagram: @inbetween_trustMore about [Guest Name or Organization]: [insert link]🔭 Keywordstrust, bravery, sovereignty, innovation, open source, regulation, technology, collaboration, leadership, value creation

with Julia Löffler – Scientist in Molecular Medicine, Neuroscience & Science Communication at the Charité in BerlinSummaryIn this episode of the in-between trust podcast, Eva Simone Lihotzky speaks with Julia Löffler about the biological, neurological, and relational foundations of trust — and why trust is as much a somatic experience as it is a cognitive one. They explore Julia’s journey from molecular medicine into neuroscience and science communication, the role of empathy in scientific work, and how biology and technology move on fundamentally different timelines. The conversation dives into the chemistry of trust, the tension between innovation speed and human adaptation, and the importance of translating science into language people can understand and act on. Julia shares why dynamic relationships, transparency, and adaptive learning are key to building trust in both medicine and technology.🔑 TakeawaysTrust is the essential currency in science and medicine.Biology and neurochemistry — from oxytocin to cortisol — shape trust.Communication is a core skill in translating science into action.Technology must adapt to the natural pace of biology.Trust is dynamic and built over time through relationships.Advancing knowledge does not guarantee immediate understanding.Digital and physical systems must both account for human trust needs.Adaptive learning is essential for responding to uncertainty.🎙️ Sound bites“Trust is built on dynamic relationships.”“Biology runs on its own time.”“Advancing knowledge does not always mean immediate understanding.”⏱️ Chapters00:00 Introduction to Biology, Neuroscience & Trust03:12 Julia’s Journey from Molecular Medicine to Communication06:24 The Neurochemistry of Trust09:15 Bridging Gaps Between Science, Patients & the Public13:02 Technology vs. Biological Timelines16:38 Trust as an Adaptive, Dynamic Process20:05 The Role of Empathy in Scientific Work23:27 Translating Complexity into Accessible Language27:41 Future of Trust in Science and Technology30:15 In-Between Moments and Reflections💻 Linksin-between trust on Instagram: @inbetween_trust More about Julia Löffler: https://www.linkedin.com/in/julia-loeffler/🔭 Keywordstrust in science, neuroscience, molecular medicine, science communication, neurochemistry of trust, oxytocin, cortisol, adaptive learning, empathy in science, bridging disciplines, technology and biology, trust in medicine

“Slow trust builds faster futures.”with Stefan Schoepfel, Founder of the Value AI InstituteIn this episode of the in-between trust podcast, Eva Simone Lihotzky speaks with Stefan Schoepfel, founder of the Value AI Institute, about how we lead—and trust—in an era shaped by intelligent systems. They explore what it means to embed ethical principles, emotional intelligence, and leadership clarity into AI development and deployment.Stefan shares why trust must take a much larger space in the conversation, how unlearning linear thinking unlocks innovation, and how responsibility must move beyond compliance toward genuine accountability. From governance to culture, this episode is a call to stay human—and stay in the driver’s seat.___🔑 TakeawaysTrust is foundational for user acceptance and systemic success.Ethical principles must guide both design and deployment.AI leadership requires emotional intelligence and clear oversight.Organizations must embed ethics into processes—not just policies.Responsible tech can support sustainability and the societal good.Unlearning linear thinking is key to adapting and leading.Ongoing trust-building requires visibility and cultural buy-in.AI systems must always include human-in-the-loop safeguards.Compliance should enable—not hinder—innovation.Don’t let tech steer blindly—stay in control.__🎙️ Sound Bites“Trust needs to take a much larger space.”“AI must comply with ethical principles.”“Stay in the driver's seat with technology.”“Unlearning is as vital as innovation.”“Leadership in AI means embracing ambiguity.”____⏱️ Chapters00:00 – Introduction to Trust and AI02:21 – The Value AI Institute: Mission and Goals05:28 – The Importance of Trust in AI09:46 – Ethical Principles and Responsible AI Design11:20 – Implementing Ethical AI in Organizations14:06 – The Role of Leadership in AI Systems16:20 – Building Trust in Teams and Systems18:07 – Navigating Leadership Challenges with AI19:24 – The Impact of AI on Ethical Usage22:50 – AI for Societal Good and Sustainability25:45 – Unlearning Linear Thinking in AI28:19 – Embracing Ambiguity in AI Leadership29:33 – Key Takeaways on Technology and Trust___🧩 KeywordsAI, trust, ethical AI, Value AI Institute, leadership, responsible tech, societal good, emotional intelligence, organizational culture, ambiguity, unlearning, governance