ΑΙhub.org
 

The Machine Ethics podcast: Responsible AI strategy with Olivia Gambelin


by
07 January 2025



share this:

Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology’s impact on society.

Responsible AI strategy with Olivia Gambelin

We chat about Olivia’s book on responsible AI, scalable AI strategy, AI ethics and responsible AI (RAI), bad innovation, values for RAI, risk and innovation mindsets, who owns the RAI strategy, why one would work with an external consultant, agentic AI, predictions for the next two years, and more…

Listen to the episode here:


One of the first movers in Responsible AI, Olivia Gambelin is a world-renowned expert in AI Ethics and product innovation whose experience in utilising ethics-by-design has empowered hundreds of business leaders to achieve their desired impact on the cutting edge of AI development. Olivia works directly with product teams to drive AI innovation through human value alignment, as well as executive teams on the operational and strategic development of responsible AI.

As the founder of Ethical Intelligence, the world’s largest network of Responsible AI practitioners, Olivia offers unparalleled insight into how leaders can embrace the strength of human values to drive holistic business success. She is the author of the book Responsible AI: Implement an Ethical Approach in Your Organization with Kogan Page Publishing, the creator of The Values Canvas, which can be found at www.thevaluescanvas.com, and co-founder of Women Shaping the Future of Responsible AI (WSFR.AI).


About The Machine Ethics podcast

This podcast was created and is run by Ben Byford and collaborators. The podcast, and other content was first created to extend Ben’s growing interest in both the AI domain and in the associated ethics. Over the last few years the podcast has grown into a place of discussion and dissemination of important ideas, not only in AI but in tech ethics generally. As the interviews unfold on they often veer into current affairs, the future of work, environmental issues, and more. Though the core is still AI and AI Ethics, we release content that is broader and therefore hopefully more useful to the general public and practitioners.

The hope for the podcast is for it to promote debate concerning technology and society, and to foster the production of technology (and in particular, decision making algorithms) that promote human ideals.

Join in the conversation by getting in touch via email here or following us on Twitter and Instagram.




The Machine Ethics Podcast

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

Disappearing lakes and AI are helping scientists map Arctic permafrost thaw in near‑real time

  18 Sep 2026
Researchers created an interactive website to track permafrost thaw across the Arctic.

How much can fair budget-division rules resist manipulation?

The authors write about their award-winning IJCAI-ECAI paper: "Approximate Strategyproofness in Approval-based Budget Division".

AI dives into a sea of data, from plankton to pollution

  16 Sep 2026
“Faster and cheaper monitoring means problems like plankton decline, litter accumulation, oil spills and coral degradation can be picked up and acted on sooner."

Interview with Yash Saxena: how is external knowledge used in AI systems?

  15 Sep 2026
What happens to information from external sources as it moves through an AI system?

When AI art has no author: Study finds generated images often can’t be traced to training data

  14 Sep 2026
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.

AI in nature conservation: powerful tool or dangerous shortcut?

  11 Sep 2026
AI provides opportunity for future biodiversity conservation but introduces risks .

Improving the process for large-scale recommender systems: an interview with Haruka Kiyohara

  10 Sep 2026
Credit-assigned policy gradient for early stage retrieval in two-stage ranking.

The Machine Ethics podcast: Data Collective with E.M. Lewis-Jong

Ben chats to E.M. Lewis-Jong about the promise of AI and making human connection easier, speech recognition and supporting linguistic diversity, making useful technologies that have a purpose, and more.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence