Season 4 Finale: Our Most Controversial AI Takes

We wrap up Season 4 of the Behavioral Design Podcast with a different kind of conversation. Instead of looking outward at our guests’ insights, Aline and Samuel turn the mic on themselves, reflecting on the season, what we’ve learned, and the boldest, most controversial opinions we hold about AI.

From questions about whether AI can truly emulate human qualities to fears of a future where we slowly de-skill ourselves by over-relying on machines, this episode is part reflection, part confessional.

Highlights include:

• A look back at the season’s most surprising and provocative guest takes on AI

• Why AI optimism often lives closest to where experts work—and where skepticism still lingers

• The heated debate over AI companions: comforting helpers or human connection killers?

• Our personal, unfiltered takes on AI’s hidden risks, including cognitive offloading and the myth of collaboration

• The strange and perhaps surprisingly useful role of AI “oracles” in our own lives

This is the perfect sendoff for Season 4: A candid, wide-ranging discussion about the future of AI, human behavior, and what it all means for how we live, think, and connect.

--

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Season 4 Recap: Can AI Capture a Whole Season?

In this special recap episode of the Behavioral Design Podcast, hosts Aline and Samuel reflect on the ambitious arc of Season 4—our deep dive into the intersection of behavioral science and artificial intelligence. From empathic chatbots to algorithmic sameness, AI co-therapists to synthetic friendships, we explored how AI is reshaping human behavior, relationships, and decision-making.

But here’s the twist: the second half of this episode isn’t hosted by us. It’s AI. Using transcripts from every conversation this season, we asked our AI co-hosts to generate a narrated summary of the biggest ideas and themes that emerged across episodes. Can AI recap a whole season better than we can? Is this the beginning of our own replacement?

Along the way, we revisit:

• How AI is changing the emotional landscape of our lives

• Why automation and personalization are both liberating and limiting

• What happens when algorithms replace—not just supplement—human judgment

• The ethical fault lines of psychological targeting, autonomy, and consent

• Whether behavioral science can keep up with the pace and power of AI

If you missed any episodes or want a distilled tour of the season, this is the one to listen to.

Next up: our Season Finale, featuring Aline and Samuel’s most controversial takes on AI 🍿

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Productivity in the Age of AI with Oliver Burkeman

In this episode of the Behavioral Design Podcast, hosts Aline and Samuel are joined by Oliver Burkeman, journalist and bestselling author of Four Thousand Weeks, to explore what it means to live and work meaningfully in an era of accelerating AI.

Together, they examine how AI tools are reshaping our relationship with time, focus, and control—from email-writing assistants to algorithmic scheduling and optimization. Oliver shares his thoughts on how these technologies, while promising to save us time, often pull us deeper into compulsive productivity loops and distract us from the deeper questions: What are we optimizing for? And what does it mean to spend our time well?

The conversation covers:

• The seduction of infinite optionality and why AI might make it worse

• Whether AI-generated outputs dull our creative instincts or free them

• Why doing fewer things might become even more important in the AI era

• The psychological cost of outsourcing decisions to machines

• How behavioral science can help people reclaim agency and meaning in a world of hyper-efficiency

This episode is a must-listen for anyone navigating the tension between automation and intention—especially those wondering how to stay human in the loop.

--

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

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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.

--

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

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The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

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.

--

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

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The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

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.

—

 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

—

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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Understanding AI Risks with Peter Slattery

In this episode of the Behavioral Design Podcast, hosts Aline and Samuel are joined by Peter Slattery, behavioral scientist and lead researcher at MIT’s FutureTech lab, where he spearheads the groundbreaking AI Risk Repository project. Together, they dive into the complex and often overlooked risks of artificial intelligence—ranging from misinformation and malicious use to systemic failures and existential threats.

Peter shares the intellectual and emotional journey behind categorizing over 1,000 documented AI risks, how his team built a risk taxonomy from 17,000+ sources, and why shared understanding and behavioral science are critical for navigating the future of AI.

This one is a must-listen for anyone curious about AI safety, behavioral science, and the future of technology that’s moving faster than most of us can track.

--

LINKS:

• Peter's LinkedIn Profile
• MIT FutureTech Lab: futuretech.mit.edu
• AI Risk Repository

--

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

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The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

Enter the AI Lab: Insights from LinkedIn Polls and AI Literature Reviews

In this episode of the Behavioral Design Podcast, hosts Samuel Salzer and Aline Holzwarth explore how AI is shaping behavioral design processes—from discovery to testing. They revisit insights from past LinkedIn polls, analyzing audience perspectives on which phases of behavioral design are best suited for AI augmentation and where human expertise remains crucial.

The discussion then shifts to AI-driven literature reviews, comparing the effectiveness of various AI tools for synthesizing research. Samuel and Aline assess the strengths and weaknesses of different platforms, diving into key performance metrics like quality, speed, and cost, and debating the risks of over-reliance on AI-generated research without human oversight.

The episode also introduces Nuance’s AI Lab, highlighting upcoming projects focused on AI-driven behavioral science innovations. The conversation concludes with a Behavioral Redesign series case study on Peloton, offering a fresh take on how AI and behavioral insights can reshape product experiences.

If you're interested in the intersection of AI, behavioral science, and research methodologies, this episode is packed with insights on where AI is excelling—and where caution is needed.

LINKS:

• Nuance AI Lab: Website

TIMESTAMPS:
00:00 Introduction and Recap of Last Year's AI Polls
06:27 AI's Strengths in Literature Review
15:12 Emerging AI Tools for Research
19:31 Evaluating AI Tools for Literature Reviews
23:57 Comparing Chinese and American AI Tools
26:01 Evaluating Literature Review Outputs
28:12 Critical Analysis and Human Oversight
35:19 The Worst Performing Model
37:21 Introducing Nuance's AI Lab
38:51 Behavioral Redesign Series: Peloton Example
45:21 Podcast Highlights and Future Guests

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When to AI, and When Not to AI with Eric Hekler

"People are different. Context matters. Things change."

In this episode of the Behavioral Design Podcast, Aline is joined by Eric Hekler, professor at UC San Diego, to explore the nuances of AI in behavioral science and health interventions. Eric’s mantra—emphasizing the importance of individual differences, context, and change—serves as a foundation for the conversation as they discuss when AI enhances behavioral interventions and when human judgment is indispensable.

The discussion explores just-in-time adaptive interventions (JITAI), the efficiency trap of AI, and the jagged frontier of AI adoption—where machine learning excels and where it falls short. Eric shares his expertise on control systems engineering, human-AI collaboration, and the real-world challenges of scaling adaptive health interventions. The episode also explores teachable moments, the importance of domain knowledge, and the need for AI to support rather than replace human decision-making.

The conversation wraps up with a quickfire round, where Eric debates AI’s role in health coaching, mental health interventions, and optimizing human routines.

LINKS:

• Eric Hekler:

TIMESTAMPS:
02:01 Introduction and Correction
05:21 The Efficiency Trap of AI
08:02 Human-AI Collaboration
11:04 Conversation with Eric Hekler
14:12 Just-in-Time Adaptive Interventions
15:19 System Identification Experiment
28:27 Control Systems vs. Machine Learning
39:44 Challenges with Classical Machine Learning
43:16 Translating Research to Real-World Applications
49:49 Community-Based Research and Context Matters
59:46 Quickfire Round: To AI or Not to AI
01:08:27 Final Thoughts on AI and Human Evolution

--

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

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The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

Sci-Fi and AI: Exploring Annie Bot with Sierra Greer

In this episode of the Behavioral Design Podcast, hosts Aline and Samuel dive into the ethical, emotional, and societal complexities of AI companionship with special guest Sierra Greer, author of Annie Bot. This thought-provoking novel explores AI-human relationships, autonomy, and the blurred line between artificial intelligence and the human experience.

Sierra shares her inspiration for Annie Bot and how sci-fi can serve as a lens to explore real-world ethical dilemmas in AI development.

• The conversation covers the concept of reinforcement learning in AI and how it mirrors human conditioning
• The gender dynamics embedded in AI design, and the ethical implications of AI companions.
• The discussion also examines real-life cases of people forming deep emotional bonds with AI chatbots

The episode rounds out with a lively quickfire round, where Sierra debates whether AI should replace lost loved ones, act as conversational assistants for introverts, or intervene in human arguments.

This is a must-listen for fans of sci-fi, behavioral science, and those fascinated by the future of AI companionship and emotional intelligence.

LINKS:

• Sierra Greer website
• Annie Bot – Official Book Page
• Goodreads Profile

TIMESTAMPS:

01:43 AI Companions: A Controversial Opinion

05:48 Exploring Sci-Fi and AI in Literature

07:42 Introducing Sierra Greer and Her Book

09:12 Reinforcement Learning Explained

15:47 Diving into the World of Annie Bot

23:17 Power Dynamics and Human-Robot Relationships

32:31 Humanity and Artificial Intelligence

41:31 Autonomy vs. Agreeableness in Relationships

43:20 Reinforcement Learning in AI and Humans

46:13 Ethics and Gaslighting in AI

48:57 Gender Dynamics in AI Design

57:18 AI Companions and Human Relationships

01:06:45 Quickfire Round: To AI or Not to AI

01:12:39 Final Thoughts and Controversial Opinions

--

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

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The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠