AI Co-Therapists with Alison Cerezo
In this episode of the Behavioral Design Podcast, hosts Aline and Samuel talk with Dr. Alison Cerezo, a clinical psychologist, professor, and Senior Vice President of Research at Mpathic, a company developing AI tools that support therapists in delivering more empathetic and precise care.

They explore the growing role of AI in mental health, from real-time feedback during therapy sessions to tools that help clinicians detect risk, stay aligned with best practices, and reduce bias. Alison describes how Mpathic works as a co-therapist—supporting rather than replacing the human element of therapy.

The conversation also digs into larger questions:

• Can AI feel more empathetic than humans?
• How do we avoid over-reliance on machines for emotional support?
• And what does it really mean to design AI that complements rather than competes with people?

This episode is a must-listen for anyone interested in the future of therapy, empathy, and AI—and what it looks like to build systems that enhance human care, not undermine it.

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Empathic Machines with Michael Inzlicht
In this episode of the Behavioral Design Podcast, hosts Aline and Samuel are joined by Michael Inzlicht, professor of psychology at the University of Toronto and co-host of the podcast Two Psychologists Four Beers. Together, they explore the surprisingly effortful nature of empathy—and what happens when artificial intelligence starts doing it better than we do.

Michael shares insights from his research into empathic AI, including findings that people often rate AI-generated empathy as more thoughtful, emotionally satisfying, and effortful than human responses—yet still prefer to receive empathy from a human. They unpack the paradox behind this preference, what it tells us about trust and connection, and whether relying on AI for emotional support could deskill us over time.

This conversation is essential listening for anyone interested in the intersection of psychology, emotion, and emerging AI tools—especially as machines get better at sounding like they care.

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Interesting in collaborating with Nuance? If you’d like to become one of our special projects, email us at hello@nuancebehavior.com or book a call directly on our website: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠nuancebehavior.com.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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How Do You Build a Moral AI? with Jana Schaich Borg

In this episode of the Behavioral Design Podcast, hosts Aline and Samuel are joined by Jana Schaich Borg, Associate Research Professor at Duke University and co-author of the book “Moral AI and How We Get There”. Together they explore one of the thorniest and most important questions in the AI age: How do you encode human morality into machines—and should you even try?

Drawing from neuroscience, philosophy, and machine learning, Jana walks us through bottom-up and top-down approaches to moral alignment, why current models fall short, and how her team’s hybrid framework may offer a better path. Along the way, they dive into the messy nature of human values, the challenges of AI ethics in organizations, and how AI could help us become more moral—not just more efficient.

This conversation blends practical tools with philosophical inquiry and leaves us with a cautiously hopeful perspective: that we can, and should, teach machines to care.

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 Topics Covered:

• What AI alignment really means (and why it’s so hard)

• Bottom-up vs. top-down moral AI systems

• How organizations get ethical AI wrong—and what to do instead

• The messy reality of human values and decision making

• Translational ethics and the need for AI KPIs

• Personalizing AI to match your values

• When moral self-reflection becomes a design feature

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Timestamps:

00:00  Intro: AI Alignment — Mission Impossible?
04:00  Why Moral AI Is So Hard (and Necessary)
07:00  The “Spec” Story & Reinforcement Gone Wrong
10:00  Anthropomorphizing AI — Helpful or Misleading?
12:00  Introducing Jana & the Moral AI Project
15:00  What “Moral AI” Really Means
18:00  Interdisciplinary Collaboration (and Friction)
21:00  Bottom-Up vs. Top-Down Approaches
27:00  Why Human Morality Is Messy
31:00  Building a Hybrid Moral AI System
41:00  Case Study: Kidney Donation Decisions
47:00  From Models to Moral Reflection
52:00  Embedding Ethics Inside Organizations
56:00  Moral Growth Mindset & Training the Workforce
01:03:00  Why Trust & Culture Matter Most
01:06:00  Comparing AI Labs: OpenAI vs. Anthropic vs. Meta
01:10:00  What We Still Don’t Know
01:11:00  Quickfire: To AI or Not To AI
01:16:00  Jana’s Most Controversial Take
01:19:00  Can AI Make Us Better Humans?

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