Technology

The In-Between Tech and Trust Podcast

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”.

Latest Episodes:

Translating Ethics: Trust, Compliance & the Culture of Responsibility - EP03 Aug 07, 2025

Show notes

with Paula Cipierre, Responsible AI Expert & Strategist

In this episode of the in-between trust podcast, Eva Simone Lihotzky speaks with Paula Cipierre, one of the leading responsible AI strategists with a profound background in law, policy, and tech, about what it means to translate legal and ethical principles into organizational practice - and how trust must be built not just through systems, but through culture, clarity, and human connection.

Together, they explore:

Why trust needs control, not just promises
How to create a culture of compliance that doesn’t collapse into checkboxes
The tension between data governance and intelligent systems
What it takes to operationalize values across teams, languages, and sectors
Why interdisciplinary thinking and empathy are foundational leadership skills in the age of AI

With insight from law, humanities, and hands-on tech policy work, Paula brings a rare perspective to ethical AI - one rooted in systems and storytelling.

🔑 Takeaways

Trust in AI depends on both transparency and institutional reliability
Compliance isn’t the goal - culture is
Regulation can enable innovation if done with clarity
Data governance and bias mitigation start long before AI
AI literacy is critical to confident, responsible use
Responsibility requires interdisciplinary skill and local ownership
Leadership means acting with explainability, not just authority
People follow people - trust starts with example

🎙️ Quote Highlights

“Trust is good, but control is better.”
“We need a much more integrated approach.”
“Lead by example; people follow people.”

⏱️ Chapters

00:00 – From Humanities to Ethical AI
03:06 – Trust in Technology: The Role of Control
06:03 – Translating Ethics into Practice
09:01 – Compliance vs. Responsibility
11:45 – Cross-Sector Collaboration
14:39 – Regulation as a Tool for Innovation
17:43 – Data Governance in AI
20:42 – AI Literacy and Employee Empowerment
23:29 – Future Skills in AI Governance
26:48 – Sustainability and System Awareness
29:30 – Leading by Example

Links

https://www.linkedin.com/in/paula-kift/

https://www.linkedin.com/company/in-between-trust-podcast/

Staying in the Driver’s Seat: Ethical AI and Leadership in Practice - EP02 Jul 31, 2025

Show notes

“Slow trust builds faster futures.”

with Stefan Schoepfel, Founder of the Value AI Institute

In 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.

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🔑 Takeaways

Trust 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.”

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⏱️ Chapters

00:00 – Introduction to Trust and AI
02:21 – The Value AI Institute: Mission and Goals
05:28 – The Importance of Trust in AI
09:46 – Ethical Principles and Responsible AI Design
11:20 – Implementing Ethical AI in Organizations
14:06 – The Role of Leadership in AI Systems
16:20 – Building Trust in Teams and Systems
18:07 – Navigating Leadership Challenges with AI
19:24 – The Impact of AI on Ethical Usage
22:50 – AI for Societal Good and Sustainability
25:45 – Unlearning Linear Thinking in AI
28:19 – Embracing Ambiguity in AI Leadership
29:33 – Key Takeaways on Technology and Trust

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🧩 Keywords

AI, trust, ethical AI, Value AI Institute, leadership, responsible tech, societal good, emotional intelligence, organizational culture, ambiguity, unlearning, governance

Trust by Code: AI Governance and the Human Layer - EP01 Jul 22, 2025

Show notes

‚Truth by code is a strong asset‘ -

with Anna Spitznagel, CEO of trail.ai

In the first episode of the in-between trust podcast, Eva Simone Lihotzky speaks with Anna Spitznagel—co-founder and CEO of trail.ai—about building trust at the heart of AI governance. Anna shares her journey designing a “co-pilot” for responsible AI systems, and explores how transparency, organizational culture, and technical rigor intersect in shaping trustworthy innovation.

Together, they dive into what it means to build “truth by code,” how compliance can enable—not hinder—progress, and why literacy, leadership, and lived experience are essential in navigating the AI era. Anna also opens questions about the future of trust across ecosystems—from upstream model providers to everyday users.

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🔑 Takeaways

Trust is the starting point for meaningful AI adoption.
Transparency and quality must be designed into both code and culture.
Responsible leadership requires communication, clarity, and tolerance for mistakes.
Literacy in AI is not optional—it’s foundational to ethical use.
Governance can be a growth engine, not just a constraint.
The best AI use cases start with real problems, not hype.
80% of AI projects don’t reach production—trust structures can change that.
Trust builds through use, experience, and critical questioning.
Future trust will require cooperation across the AI supply chain.

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🎙️ Sound Bites

“Trust is my personal highest value.”

“Truth by code is a strong asset.”

“Literacy is key to understanding AI.”

“Governance is not a blocker—it’s an enabler of scale.”

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⏱️ Chapters

00:00 – Introduction to AI Governance and Trust

01:38 – Defining Trust in AI

04:27 – Building Trust in Organizations

10:13 – The Role of Leadership in AI

12:51 – Designing for Transparency

18:58 – Navigating Use Cases & Compliance

23:14 – The Future of Trust in AI

30:45 – Unanswered Questions That Remain

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🧩 Keywords

AI governance, trust, transparency, leadership, compliance, data privacy, organizational culture, literacy, AI use cases, critical reasoning, automation, future of AI

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