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Contenuto fornito da Samuel Salzer and Aline Holzwarth, Samuel Salzer, and Aline Holzwarth. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Samuel Salzer and Aline Holzwarth, Samuel Salzer, and Aline Holzwarth o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
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Recommender Systems with Carey Morewedge

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Manage episode 446494487 series 2821307
Contenuto fornito da Samuel Salzer and Aline Holzwarth, Samuel Salzer, and Aline Holzwarth. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Samuel Salzer and Aline Holzwarth, Samuel Salzer, and Aline Holzwarth o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

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:

Understanding AI Recommender Systems:

--

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 hello@nuancebehavior.com 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 ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠podcast@habitweekly.com⁠⁠⁠⁠⁠

The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

  continue reading

61 episodi

Artwork
iconCondividi
 
Manage episode 446494487 series 2821307
Contenuto fornito da Samuel Salzer and Aline Holzwarth, Samuel Salzer, and Aline Holzwarth. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Samuel Salzer and Aline Holzwarth, Samuel Salzer, and Aline Holzwarth o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

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:

Understanding AI Recommender Systems:

--

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 hello@nuancebehavior.com 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 ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠podcast@habitweekly.com⁠⁠⁠⁠⁠

The song used is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Murgatroyd by David Pizarro⁠

  continue reading

61 episodi

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