OVERVIEW

In this episode of The Global Lens, Daniella Sussman sits down with Thilo Stadelmann to explore how artificial intelligence is actually evolving beyond the headlines. The conversation touches on machine learning and the role of science diplomacy while questioning common assumptions about rapid breakthroughs. Together, they focus on what it really takes to build technology that people can trust and that works in service of society.

EPISODE SUMMARY

Thilo Stadelmann challenges dominant narratives around artificial general intelligence, arguing that current AI systems remain fundamentally limited despite rapid progress. The discussion explores how machine learning scaling is reaching diminishing returns and why new paradigms may be needed for meaningful breakthroughs. The episode also dives into AI ethics, digital sovereignty, and the risks of poorly designed human-AI interaction, particularly in relation to mental health and trust. Ultimately, the conversation presents a compelling case for pro-human technology, open-source AI ecosystems, and the role of policy in shaping a more equitable AI-driven future.

In this episode, we discuss:

02:02 - Questioning the plausibility of near-term artificial general intelligence timelines

06:02 - Why scenario based thinking matters more than prediction in AI policy

09:03 - Exploring the limitations of current machine learning systems and scaling laws

12:29 - How AI interaction may reshape human behavior and relationships

27:53 - Digital trust, sovereignty, and the risks of centralized AI ecosystems

33:35 - Open source AI and the future of local innovation and global competition

43:26 - What policymakers and science diplomats can do to support humane AI futures

ABOUT THE GUEST

Thilo Stadelmann is Professor of Artificial Intelligence and Machine Learning at the ZHAW School of Engineering in Switzerland and Founding Director of its Centre for Artificial Intelligence. With over 15 years of experience, he leads research in machine perception and cognition, focusing on representation learning across image, audio, and signal data with real-world applications.

He is a co-founder of Alpine AI AG, the ZHAW Datalab, and the Data Innovation Alliance, and advises on AI policy and governance. He is also the author of Applied Data Science and his 2025 essay AI in 2035 outlines a vision for efficient, open, and trust-centered AI systems.

MENTIONED IN THE EPISODE:

⚇ (Book) Applied Data Science – https://link.springer.com/book/10.1007/978-3-030-11821-1

⚇ (Studies or Research) Assessing Deep Learning – https://link.springer.com/article/10.1007/s43681-023-00408-z

⚇ (Studies or Research) A Guide to AI – https://stdm.github.io/downloads/papers/GRW_2025.pdf

⚇ (Studies or Research) Debate: Evidence-Based AI Risk Assessment for Public Policy – https://www.tandfonline.com/doi/full/10.1080/09540962.2025.2541304

⚇ (Studies or Research) The Stochastic Nature of Machine Learning and Its Implications for High-Consequence AI – https://stdm.github.io/downloads/papers/AIEthics_2026.pdf

⚇ (Video) TEDx Talk on How Not to Fear AI – https://www.youtube.com/watch?v=deVbP-hViMQ

⚇ (Website) AI in 2035 – https://stdm.github.io/AI-in-2035/

⚇ (Website) How Not to Fear AI – https://premium-speakers.com/en/magazin/thilo-stadelmann-how-not-to-fear-artificial-intelligence/

⚇ (Reference) How Bad Are A.I. Delusions? – https://www.nytimes.com/2026/01/26/us/chatgpt-delusions-psychosis.html

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CONNECT WITH THILO STADELMANN:

⚇ Website: https://thilo-stadelmann.com

⚇ LinkedIn: https://www.linkedin.com/in/thilo-stadelmann/

⚇ YouTube: https://www.youtube.com/channel/UCqEjuibTwlVoO9bUW0oI0pA

CONNECT WITH DANIELLA:

⚇ Podcast Website: https://the-global-lens.captivate.fm/

⚇ Global Lens Website: https://glsd.ai

⚇ Global Signals: https://global-signals.ghost.io/

⚇ Book: The Science Diplomacy Playbook – Kindle and Paperback: https://www.amazon.com/author/daniellasussman

⚇ LinkedIn: https://www.linkedin.com/in/daniellasussman/