Chatbots, Synthetic Users and AI for User Research with Hassan Aleem

Behavior Change Score with Roos van Duijnhoven In this special episode of the Behavioral Design Podcast, host Samuel continues the mini-series featuring expert practitioners from the Nuance Behavior team. This week’s guest is Roos van Duijnhoven, a behavioral scientist with a deep passion for designing human-centered digital solutions that drive meaningful behavior change. Samuel and Roos explore a wide range of topics, including the Behavior Change Score Framework, strategies for improving onboarding and retention in digital health products, and the importance of focusing on real-world behavior (‘big E’ engagement) versus in-app behavior (‘little e’ engagement). They also dive into insights from Nuance Behavior’s ‘Behavior Change Score Report,’ which evaluates fitness apps and provides actionable lessons for designing more effective digital interventions. This episode offers a treasure trove of insights for anyone interested in applying behavioral science to digital product design and health interventions! LINKS: ⁠⁠Roos's LinkedIn⁠ The Behavior Change Score Report ⁠Nuance Behavior Website⁠ Engagement with Heather Cole-Lewis TIMESTAMPS 00:36 Meet Roos van Duijnhoven 01:06 Recap of Susan Murhpy episode 07:31 Insights from the Behavior Change Score Report 20:14 Big E vs. Little e Engagement: Real-World vs. In-App Behavior 26:31 Controversial Opinions: Electric Bicycles 29:32 Conclusion and Farewell -- 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.⁠⁠⁠⁠⁠⁠ Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

Real-Time Behavior Change Algorithms with Susan Murphy In this thought-provoking episode of the Behavioral Design Podcast, hosts Aline and Samuel explore the cutting edge of AI in behavioral science with Professor Susan Murphy, a world-renowned expert in statistics and behavioral research. The conversation dives into Susan's groundbreaking work on micro-randomized trials and just-in-time adaptive interventions (JITAI) to create personalized, real-time behavior change algorithms. Together, they explore the role of reinforcement learning in adapting interventions over time, tackling ethical challenges, and sustaining user engagement in a rapidly evolving world. This episode also includes a fun "To AI or Not to AI" quickfire round and Susan’s reflections on the "frontier" nature of behavioral science today, making this a must-listen for anyone passionate about technology, psychology, and innovation. LINKS: ⁠Susan Murphy's Faculty Page⁠ ⁠Learn more about JITAI Heart Steps Study⁠ ⁠Nuance Behavior Website TIMESTAMPS 01:00 – AI Voice Assistants in Everyday Life 07:22 – Introduction to Susan Murphy 08:06 – Micro-Randomized Trials Explained 11:08 – Just-in-Time Adaptive Interventions (JITAI) 27:19 – Reinforcement Learning and Behavioral Science 35:15 – Adaptive Algorithms for Personalized Support 40:30 – Micro-Randomization and Personalized Interventions 45:19 – Maintaining Engagement in Digital Interventions 49:51 – The Frontier Nature of Behavioral Science 51:39 – Quickfire Round: To AI or Not to AI 57:13 – Ethical Considerations in AI and Behavioral Science -- 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.⁠⁠⁠⁠⁠⁠ Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

AI Chatbots and Synthetic Users with Hassan Aleem In this special episode of the Behavioral Design Podcast, host Samuel kicks off a new mini-series featuring expert practitioners from the Nuance Behavior team. This week’s guest is Hassan Aleem, a respected behavioral practitioner with a Ph.D. in neuroscience and extensive experience in industries like fintech, health wearables, and public health. Together, Samuel and Hassan explore the fascinating intersection of AI and behavioral science. They discuss AI’s impact on user research, the opportunities and challenges of AI-powered chatbots, the role of synthetic users in behavioral research, and the potential of AI to streamline literature reviews. The conversation culminates in a thought-provoking discussion: can AI truly understand and design for beauty? This episode is packed with insights on how AI can enhance behavioral science practice while emphasizing the irreplaceable value of human expertise. TIMESTAMPS 00:00 Introduction to the Behavioral Design Podcast02:00 Meet Hassan Aleem: Neuroscientist and Behavioral Practitioner02:37 Exploring AI in Behavioral Science03:42 The Role of AI in User Research10:21 Chatbots and Behavioral Design18:50 AI in Literature Reviews and Research34:59 Can AI Understand Beauty?40:48 Conclusion and Final Thoughts LINKS: ⁠Hassan's LinkedIn Nuance Behavior Website -- 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.⁠⁠⁠⁠⁠ Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠⁠⁠⁠⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

Using AI to Change Human Behavior In this episode of the Behavioral Design Podcast, hosts Aline Holzwarth and Samuel Salzer explore the fascinating intersection of AI and behavioral science with Amy Bucher, Chief Behavior Officer at Lirio. Together, they dive into the challenges and opportunities of integrating AI with behavioral science for health interventions, focusing on the critical need to design AI tools with human behavior in mind. Key topics include the role of reinforcement learning and precision nudging in behavior change, the importance of grounded behavioral insights to cut through AI hype, and Amy’s experiences with personalized health interventions. Amy also sheds light on the effectiveness of digital tools in behavior change and shares her vision for the future of AI in behavioral health. Tune in for an insightful discussion on how behavioral science can shape the next generation of AI-driven health interventions! LINKS: Amy Bucher Lirio Website LinkedIn Profile Further Reading on AI and Behavioral Science: ⁠How Machine Learning and Artificial Intelligence are Used in Digital Behavior Change Interventions: A Scoping Review⁠ The Power of Large Behavior Models in Healthcare Consumer Engagement Moral Agents for Sustainable Transitions Personalized Digital Health Communications to Increase COVID-19 Vaccination in Underserved Populations: A Double Diamond Approach to Behavioral Design The Patient Experience of the Future is Personalized: Using Technology to Scale an N of 1 Approach Digital Twins and the Emerging Science of Self: Implications for Digital Health Experience Design and “Small” Data Feasibility of a Reinforcement Learning–Enabled Digital Health Intervention to Promote Mammograms Precision Nudging and Health Interventions Reinforcement Learning in Behavior Change TIMESTAMPS: 00:30 Behavioral Science and AI: A Crucial Intersection 07:44 Introducing Amy Bucher 10:43 Scoping Review on AI in Behavior Change 16:05 Challenges and Misconceptions in AI 22:07 Reinforcement Learning and AI Agents 28:40 Designing Interventions with AI and Behavioral Science 31:32 Operationalizing Behavior Change Techniques 35:25 Challenges in Measuring Engagement 42:43 The Role of Behavioral Science in AI 46:53 Quickfire Round: To AI or Not to AI 49:25 Controversial Opinions on AI 53:52 Closing Thoughts and Acknowledgements -- 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.⁠⁠⁠⁠ Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly newsletter⁠⁠⁠⁠⁠⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠⁠⁠⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

Debunkbot and Other Tools Against Misinformation In this follow-up episode of the Behavioral Design Podcast, hosts Aline Holzwarth and Samuel Salzer welcome back Gordon Pennycook, psychology professor at Cornell University, to continue their deep dive into the battle against misinformation. Building on their previous conversation around misinformation’s impact on democratic participation and the role of AI in spreading and combating falsehoods, this episode focuses on actionable strategies and interventions to combat misinformation effectively. Gordon discusses evidence-based approaches, including nudges, accuracy prompts, and psychological inoculation (or prebunking) techniques, that empower individuals to better evaluate the information they encounter. The conversation highlights recent advancements in using AI to debunk conspiracy theories and examines how AI-generated evidence can influence belief systems. They also tackle the role of social media platforms in moderating content, the ethical balance between free speech and misinformation, and practical steps that can make platforms safer without stifling expression. This episode provides valuable insights for anyone interested in understanding how to counter misinformation through behavioral science and AI. LINKS: Gordon Pennycook: ⁠Google Scholar Profile⁠ ⁠Twitter⁠ ⁠Personal Website⁠ ⁠Cornell University Faculty Page⁠ Further Reading on Misinformation: Debunkbot - The AI That Reduces Belief in Conspiracy Theories Interventions Toolbox - Strategies to Combat Misinformation TIMESTAMPS: 01:27 Intro and Early Voting06:45 Welcome back, Gordon!07:52 Strategies to Combat Misinformation11:10 Nudges and Behavioral Interventions14:21 Comparing Intervention Strategies19:08 Psychological Inoculation and Prebunking32:21 Echo Chambers and Online Misinformation34:13 Individual vs. Policy Interventions36:21 If You Owned a Social Media Company37:49 Algorithm Changes and Platform Quality38:42 Community Notes and Fact-Checking39:30 Reddit’s Moderation System42:07 Generative AI and Fact-Checking43:16 AI Debunking Conspiracy Theories45:26 Effectiveness of AI in Changing Beliefs51:32 Potential Misuse of AI55:13 Final Thoughts and Reflections -- 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.⁠⁠⁠ Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠⁠⁠⁠⁠Habit Weekly newsletter⁠⁠⁠⁠⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠⁠⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

The Role of Misinformation and AI in the US Election with Gordon Pennycook In this episode of the Behavioral Design Podcast, hosts Aline and Samuel explore the complex world of misinformation in the context of the U.S. elections with special guest Gordon Pennycook, a psychology professor at Cornell University. The episode covers the effects of misinformation on democratic participation, and how behavioral science sheds light on reasoning errors that drive belief in falsehoods. Gordon shares insights from his groundbreaking research on misinformation, exploring how falsehoods gain traction and the role AI can play in both spreading and mitigating misinformation. The conversation also tackles the evolution of misinformation, including the impact of social media and disinformation campaigns that blur the line between truth and fiction. Tune in to hear why certain falsehoods spread faster than truths, the psychological appeal of conspiracy theories, and how humor can amplify the reach of misinformation in surprising ways. LINKS: Gordon Pennycook: Google Scholar Profile Twitter Personal Website Cornell University Faculty Page Further Reading on Misinformation: Brandolini’s Law and the Spread of Falsehoods Role of AI in Misinformation The Psychology of Conspiracy Theories TIMESTAMPS: 00:00 Introduction 03:14 Behavioral Science and Misinformation 05:28 Introducing Gordon Pennycook 10:02 The Evolution of Misinformation 12:46 AI’s Role in Misinformation 14:51 Impact of Misinformation on Elections 21:43 COVID-19 and Vaccine Misinformation 26:32 Technological Advancements in Misinformation 33:50 Conspiracy Theories 35:39 Misinformation and Social Media 42:35 The Role of Humor in Misinformation 48:08 Quickfire Round: To AI or Not to AI -- 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.⁠⁠ Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠⁠⁠⁠Habit Weekly newsletter⁠⁠⁠⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

In this spine-chilling Halloween special of the Behavioral Design Podcast, co-hosts Aline Holzwarth and Samuel Salzer take listeners on a journey into the eerie intersection of AI and behavioral science. They explore the potential ethical and social consequences of AI, from our urge to anthropomorphize machines to the creeping influence of human biases in AI engineering. The episode kicks off with the hosts sharing their favorite Halloween costumes and family traditions before delving into the broader theme of Frankenstein as an apt metaphor for AI. They discuss the human inclination to attribute human qualities to non-human entities and the ethical implications of creating machines that mirror humanity. The conversation deepens with reflections on biases in AI development, risks of ‘playing God,’ and the tension between technological progress and human oversight. In a thrilling twist, the hosts read a co-authored sci-fi story written with ChatGPT, illustrating the potential dark consequences of unchecked AI advancement. The episode wraps up with Halloween-themed wishes, encouraging listeners to ponder the boundaries between human and machine as they celebrate the holiday. Timestamps: 03:38 – Frankenstein: Revisiting the original story 09:09 – Frankenstein’s Modern AI Metaphor: Parallels to today’s technology 18:06 – Reflections on AI and Anthropomorphism: The urge to humanize machines 36:31 – Exploring Human Biases in AI Development: How biases shape AI 42:06 – Trust in AI: Human vs. algorithmic decision-making 46:45 – The Personalization of AI Systems: Pros and cons of tailored experiences 49:10 – The Ethics of Playing God with AI: Examining the risks 55:56 – Concluding Thoughts and Halloween Wishes: Reflecting on AI’s duality -- 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.⁠ Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠⁠⁠Habit Weekly newsletter⁠⁠⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

In this episode of the Behavioral Design Podcast, we delve into the world of AI recommender systems with special guest Carey Morewedge, a leading expert in behavioral science and AI. The discussion covers the fundamental mechanics behind AI recommendation systems, including content-based filtering, collaborative filtering, and hybrid models. Carey explains how platforms like Netflix, Twitter, and TikTok use implicit data to make predictions about user preferences, and how these systems often prioritize short-term engagement over long-term satisfaction. The episode also touches on ethical concerns, such as the gap between revealed and normative preferences, and the risks of relying too much on algorithms without considering the full context of human behavior. Join co-hosts Aline Holzwarth and Samuel Salzer as they together with Carey explore the delicate balance between human preferences and algorithmic influence. This episode is a must-listen for anyone interested in understanding the complexities of AI-driven recommendations! -- LINKS: Carey Morewedge: Google Scholar Profile Carey Morewedge - LinkedIn Boston University Faculty Page Personal Website Understanding AI Recommender Systems: How Netflix’s Recommendation System Works Implicit Feedback for Recommender Systems (Research Paper) Why People Don’t Trust Algorithms (Harvard Business Review) ⁠Nuance Behavior Website⁠ -- TIMESTAMPS: 00:00 The 'Do But Not Recommend' Game 07:53 The Complexity of Recommender Systems 08:58 Types of Recommender Systems 12:08 Introducing Carey Morewedge 14:13 Understanding Decision Making in AI 17:00 Challenges in AI Recommendations 32:13 Long-Term Impact on User Behavior 33:00 Understanding User Preferences 35:03 Challenges with A/B Testing 40:06 Algorithm Aversion 46:51 Quickfire Round: To AI or Not to AI 52:55 The Future of AI and Human Relationships -- 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.⁠ Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠⁠⁠Habit Weekly newsletter⁠⁠⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

In the latest episode of the Behavioral Design Podcast, we are excited to launch Season 4 with an in-depth exploration of how behavioral science and AI converge, setting the stage for an engaging and thought-provoking season. This episode tackles big questions around AI’s growing influence, offering insights into both its promise and its challenges, especially as they relate to human behavior and decision-making. Join co-hosts Aline Holzwarth and Samuel Salzer as they introduce key themes for the season, including the profound implications of AI on behavioral science and society at large. The episode opens with breaking news from the AI world, such as the significance of neural networks, which serve as the foundation of modern AI systems. The hosts explain how neural networks work and contrast them with the extraordinary complexity of the human brain. The episode covers essential concepts for behavioral scientists, including large language models (LLMs), the backbone of generative AI, as well as prompt engineering and AI agents. These tools are transforming fields from healthcare to customer service, and the hosts break down their real-world applications, highlighting how they are used to enhance decision-making, automate workflows, and drive personalized interventions. Samuel and Aline debunk several common myths about AI, such as whether generative AI truly enhances creativity or if more complex models are always better. They also explore algorithmic bias versus human bias, discussing how AI can both amplify and address societal inequities depending on how it is designed and implemented. In “To AI or Not to AI”, this season’s quickfire round, the hosts weigh in on whether they’d trust AI for tasks like driving their kids to daycare or offering relationship advice, sparking a thought-provoking discussion on AI’s role in everyday life. This episode is a must-listen for anyone curious about the evolving relationship between behavioral science and AI, offering both high-level insights and detailed explorations of the real-world implications of these technologies. -- TIMESTAMPS: 00:00 Introduction to the Behavioral Design Podcast 02:36 Breaking News 04:30 Understanding Neural Networks 09:38 The Beauty and Complexity of the Human Brain 17:37 Season Preview 21:53 Meet Your Hosts 29:00 Nuanced Behavior 30:43 AI 101 for Behavioral Scientists 44:14 Debunking AI Myths 01:02:15 To AI or Not to AI: Quickfire Round 01:14:45 Final Thoughts LINKS: Geoffrey Hinton’s Talk on AI and John Hopfield’s Contributions to Neural Networks Sherry Turkle’s Memoir “The Empathy Diaries” Marvin Minsky and the Concept of the Brain as a Machine Cassie Kozyrkov’s Blog on Machine Learning Sendhil Mullainathan’s Paper on Algorithmic Fairness Generative AI enhances individual creativity but reduces the collective diversity of novel content Superintelligence: Paths, Dangers, Strategies Biased Algorithms Are Easier to Fix Than Biased People Nuance Behavior Website -- 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. Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠⁠Habit Weekly newsletter⁠⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

We've reached the end of Season 3! 🎉 In this finale, we give you the inside scoop on topics behavioral design from 2023. From our favorite resources to AI to films, we explore all things behavioral design, so you too are in the inside scoop! All resources are linked below. Enjoy! From the bottom of our hearts, thank you for supporting us throughout the year! We appreciate you! 🙏 🙌 Gratitude: A systematic review of the strength of evidence for the most commonly recommended happiness strategies in mainstream media | Nature Human Behaviour (Dunigan Folk & Elizabeth Dunn) No Sweat book - Michelle Segar Preregistering, transparency, and large samples boost psychology studies’ replication rate to nearly 90% | Science High replicability of newly discovered social-behavioural findings is achievable | Nature Human Behaviour Favorite Resources: BehaviorBytes Women in Behavioral Science and the Women in Behavioral Science LinkedIn group – Darcie Piechowski Lesson on Fraud and Whistleblowing – Zoe Ziani Choice Overload: It’s not about the number – Hassan & Roos 7 Routes to Applied Behavioural Science Experimentation and Observation – Affective + OECD Mapping Behavioural Journeys – Common Thread A Manifesto for Applying Behavioral Science – The Behavioural Insights Team Behavioral Science as a Specialization – Connor Joyce The Science of Context – Jared Peterson Top 10 films: Fallen leaves Close Passages Luxembourg, Luxembourg Past Lives Beau Is Afraid One Fine Morning Barbie Oppenheimer Infinity Pool -- Support the podcast by joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Habit Weekly Pro⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 🚀. Members get access to extensive content databases, calls with field leaders, exclusive offers and discounts, and so much more. Every Monday our ⁠⁠⁠Habit Weekly newsletter⁠⁠⁠ shares the best articles, videos, podcasts, and exclusive premium content from the world of behavioral science and business.  Get in touch via ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[email protected]⁠⁠⁠ The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠