Episode 29: Beyond Optimization: Building Better AI for People

Are you ready for a new era of business transformation, driven by empathy and ethics? Lukas Egger invites Joel Lehman to spotlight the transformative potential, and risks, of AI as it becomes a trusted partner in our daily lives. This episode unpacks how AI can foster connection, enhance trust, and change the very nature of customer engagement. Joel shares visionary ideas on responsible AI, human flourishing, and the evolving dynamics between people and technology. Listen in for practical inspiration and compelling arguments on building a future where AI genuinely serves humanity.

Guest:

Joel Lehman

ML Research Scientist

Joel Lehman is a machine learning researcher and author, and is currently a research fellow with the Cosmos Institute. He has previously researched open-ended AI at OpenAI, Uber AI Labs, and Geometric Intelligence, and was previously a professor at the IT University of Copenhagen. He is co-author of the popular science book, Why Greatness Cannot Be Planned, and has won several best paper awards, as well as awards for impactful papers (the SIGEVO impact award and the ISAL Outstanding Paper of 2020 award).

Host:

Lukas N. P. Egger

Head of the Innovation Office & Strategic Projects team at SAP Signavio

Lukas leads a team of experts, steering innovation projects. His approach blends a strong technical understanding with a keen eye for product discovery and digital transformation. Lukas regularly contributes to discussions and panels, sharing his perspectives on AI, the digital zeitgeist, and philosophy. Lukas funded multiple startups, published a humorous philosophy book, and received silver screen quotation for special effects work for an animated movie.

If you want to learn more about:

• Our guest: LinkedIn | Personal Website | Google Scholar | Book: Why Greatness Cannot Be Planned
• SAP Signavio: https://www.signavio.com

If you have questions or comments, email: [email protected]

Additional downloads:

• Download transcript as PDF file