As artificial intelligence takes on a growing role in decisions about education, jobs, housing, loans, healthcare, and criminal justice, concerns about fairness have become urgent. Because AI systems are trained on data that reflect historical inequalities, they often reproduce or even amplify those disparities. In his book “AI Fairness: Designing Equal Opportunity Algorithms” Professor Derek Leben draws on classic philosophical theories of justice—especially John Rawls’s work—to propose a framework for evaluating the fairness of AI systems. This framework offers a way to think systematically about algorithmic justice: how automated decisions can align with ethical principles of equality and fairness. The book examines the trade-offs among competing fairness metrics and shows that it is often impossible to satisfy them all at once. As a result, organizations must decide which definitions of fairness to prioritize, and regulators must determine how existing laws should apply to AI. In this episode of Bridging the Gaps, I speak with Derek Leben.
Derek Leben is Professor of Business Ethics at the Tepper School of Business at Carnegie Mellon University. As founder of the consulting group Ethical Algorithms, he has worked with governments and companies to develop policies on fairness and benefit for AI and autonomous systems.
I begin our discussion by asking Derek what “AI” means in the context of his work and how fairness fits into that picture. From there, we explore why fairness matters as AI systems increasingly influence critical decisions about employment, education, housing, loans, healthcare, and criminal justice.
We discuss how historical inequalities in training data lead to biased outcomes, giving listeners a deeper understanding of the problem. While some view AI fairness as a purely technical issue that engineers can fix, the book argues that it is also a moral and political challenge—one that requires insights from philosophy and ethics. We then examine the difficulty of balancing multiple fairness metrics, which often cannot all be satisfied simultaneously, and discuss how organizations might prioritize among them. Derek explains his theory of algorithmic justice, inspired by John Rawls’s philosophy, and we unpack its key ideas.
Later, we touch on questions of urgency versus long-term reform, exploring the idea of longtermism, and discuss the tension between fairness and accuracy. Finally, we consider how businesses can balance commercial goals with their broader social responsibilities.
Overall, it is an informative and thought-provoking conversation about how we can make AI systems more just.
Complement this discussion with ““The Line: AI and the Future of Personhood” with Professor James Boyle” available at:
https://www.bridgingthegaps.ie/2025/04/the-line-ai-and-the-future-of-personhood-with-professor-james-boyle/
And then listen to “Reclaiming Human Intelligence and “How to Stay Smart in a Smart World” with Prof. Gerd Gigerenzer” available at:
https://www.bridgingthegaps.ie/2023/04/reclaiming-human-intelligence-and-how-to-stay-smart-in-a-smart-world-with-prof-gerd-gigerenzer/
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As artificial intelligence takes on a growing role in decisions about education, jobs, housing, loans, healthcare, and criminal justice, concerns about fairness have become urgent. Because AI systems are trained on data that reflect historical inequalities, they often reproduce or even amplify those disparities. In his book “AI Fairness: Designing Equal Opportunity Algorithms” Professor Derek Leben draws on classic philosophical theories of justice—especially John Rawls’s work—to propose a framework for evaluating the fairness of AI systems. This framework offers a way to think systematically about algorithmic justice: how automated decisions can align with ethical principles of equality and fairness. The book examines the trade-offs among competing fairness metrics and shows that it is often impossible to satisfy them all at once. As a result, organizations must decide which definitions of fairness to prioritize, and regulators must determine how existing laws should apply to AI. In this episode of Bridging the Gaps, I speak with Derek Leben.
Derek Leben is Professor of Business Ethics at the Tepper School of Business at Carnegie Mellon University. As founder of the consulting group Ethical Algorithms, he has worked with governments and companies to develop policies on fairness and benefit for AI and autonomous systems.
I begin our discussion by asking Derek what “AI” means in the context of his work and how fairness fits into that picture. From there, we explore why fairness matters as AI systems increasingly influence critical decisions about employment, education, housing, loans, healthcare, and criminal justice.
We discuss how historical inequalities in training data lead to biased outcomes, giving listeners a deeper understanding of the problem. While some view AI fairness as a purely technical issue that engineers can fix, the book argues that it is also a moral and political challenge—one that requires insights from philosophy and ethics. We then examine the difficulty of balancing multiple fairness metrics, which often cannot all be satisfied simultaneously, and discuss how organizations might prioritize among them. Derek explains his theory of algorithmic justice, inspired by John Rawls’s philosophy, and we unpack its key ideas.
Later, we touch on questions of urgency versus long-term reform, exploring the idea of longtermism, and discuss the tension between fairness and accuracy. Finally, we consider how businesses can balance commercial goals with their broader social responsibilities.
Overall, it is an informative and thought-provoking conversation about how we can make AI systems more just.
Complement this discussion with ““The Line: AI and the Future of Personhood” with Professor James Boyle” available at:
https://www.bridgingthegaps.ie/2025/04/the-line-ai-and-the-future-of-personhood-with-professor-james-boyle/
And then listen to “Reclaiming Human Intelligence and “How to Stay Smart in a Smart World” with Prof. Gerd Gigerenzer” available at:
https://www.bridgingthegaps.ie/2023/04/reclaiming-human-intelligence-and-how-to-stay-smart-in-a-smart-world-with-prof-gerd-gigerenzer/
“The AI Playbook: Mastering the Rare Art of Machine Learning Deployment” with Eric Siegel
Bridging the Gaps: A Portal for Curious Minds
45 minutes 7 seconds
1 year ago
“The AI Playbook: Mastering the Rare Art of Machine Learning Deployment” with Eric Siegel
The most powerful tool often comes with the greatest challenges. In recent times Machine learning has emerged as the world's leading general-purpose technology, yet its implementation remains notably complex. Beyond the realm of Big Tech and a select few leading enterprises, many machine learning initiatives don’t succeed, failing to deliver on their potential. What's lacking? A specialised business approach and development & deployment strategy tailored for widespread adoption. In his recent book “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment” acclaimed author Eric Siegel introduces a comprehensive six-step methodology for guiding machine learning projects from inception to implementation. The book showcases the methodology through both successful and unsuccessful anecdotes, featuring insightful case studies from renowned companies such as UPS, FICO, and prominent dot-coms. In this episode of Bridging the Gaps, I speak with Eric Siege. We discuss this disciplined approach that empowers business professionals, and establishes a sorely needed strategic framework for data professionals.
Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI World, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker.
We begin our discussion by addressing Eric's notable observation, highlighted both in his presentations and book, that the “AI Hype” is a distraction for companies. Eric elaborates on this notion, providing detailed insights. Additionally, we explore the suggestion to shift focus from the broad term "AI" to the more specific "Machine Learning." Our conversation then delves into the challenges faced by companies and professionals in conceptualising and deploying AI-driven ideas and solutions. This then leads to the consideration of whether forming specialised teams and developing focused strategies are necessary to address these challenges effectively. Next, we delve into the intricacies of the six-step BizML process introduced by Eric in his book, comparing it to the concept of MLOps. We then thoroughly examine the BizML process, dissecting its components and implications. Overall, this has been a highly enlightening and informative discussion.
Complement this discussion with ““Working with AI: Real Stories of Human-Machine Collaboration” with Professor Thomas Davenport and Professor Steven Miller” available at:
https://www.bridgingthegaps.ie/2022/10/working-with-ai-real-stories-of-human-machine-collaboration-thomas-davenport-steven-miller/
And then listen to ““Machines like Us: TOWARD AI WITH COMMON SENSE” with Professor Ronald Brachman” available at:
https://www.bridgingthegaps.ie/2022/06/machines-like-us-toward-ai-with-common-sense-with-professor-ronald-brachman/
Bridging the Gaps: A Portal for Curious Minds
As artificial intelligence takes on a growing role in decisions about education, jobs, housing, loans, healthcare, and criminal justice, concerns about fairness have become urgent. Because AI systems are trained on data that reflect historical inequalities, they often reproduce or even amplify those disparities. In his book “AI Fairness: Designing Equal Opportunity Algorithms” Professor Derek Leben draws on classic philosophical theories of justice—especially John Rawls’s work—to propose a framework for evaluating the fairness of AI systems. This framework offers a way to think systematically about algorithmic justice: how automated decisions can align with ethical principles of equality and fairness. The book examines the trade-offs among competing fairness metrics and shows that it is often impossible to satisfy them all at once. As a result, organizations must decide which definitions of fairness to prioritize, and regulators must determine how existing laws should apply to AI. In this episode of Bridging the Gaps, I speak with Derek Leben.
Derek Leben is Professor of Business Ethics at the Tepper School of Business at Carnegie Mellon University. As founder of the consulting group Ethical Algorithms, he has worked with governments and companies to develop policies on fairness and benefit for AI and autonomous systems.
I begin our discussion by asking Derek what “AI” means in the context of his work and how fairness fits into that picture. From there, we explore why fairness matters as AI systems increasingly influence critical decisions about employment, education, housing, loans, healthcare, and criminal justice.
We discuss how historical inequalities in training data lead to biased outcomes, giving listeners a deeper understanding of the problem. While some view AI fairness as a purely technical issue that engineers can fix, the book argues that it is also a moral and political challenge—one that requires insights from philosophy and ethics. We then examine the difficulty of balancing multiple fairness metrics, which often cannot all be satisfied simultaneously, and discuss how organizations might prioritize among them. Derek explains his theory of algorithmic justice, inspired by John Rawls’s philosophy, and we unpack its key ideas.
Later, we touch on questions of urgency versus long-term reform, exploring the idea of longtermism, and discuss the tension between fairness and accuracy. Finally, we consider how businesses can balance commercial goals with their broader social responsibilities.
Overall, it is an informative and thought-provoking conversation about how we can make AI systems more just.
Complement this discussion with ““The Line: AI and the Future of Personhood” with Professor James Boyle” available at:
https://www.bridgingthegaps.ie/2025/04/the-line-ai-and-the-future-of-personhood-with-professor-james-boyle/
And then listen to “Reclaiming Human Intelligence and “How to Stay Smart in a Smart World” with Prof. Gerd Gigerenzer” available at:
https://www.bridgingthegaps.ie/2023/04/reclaiming-human-intelligence-and-how-to-stay-smart-in-a-smart-world-with-prof-gerd-gigerenzer/
