Guest James Landay is an expert in human-centered artificial intelligence, a field all about optimizing technology for human and societal good. Landay says one of the most promising intersections is in education and AI, where the technology excels as a coaching and tutoring tool. His Smart Primer and Acorn apps use augmented reality and AI to engage children in outdoor, hands-on environmental science, and his GPT Coach is an AI-powered fitness planning tool. When it comes to AI and education, things are wide open and only just getting started, Landay tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your quest. You can send questions to thefutureofeverything@stanford.edu.

Episode Reference Links:

• Stanford Profile: James Landay
• Smart Primer

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest James Landay, a professor of computer science at Stanford University.

(00:02:04) Evolving AI Applications

How large language models can replicate personal coaching experiences.

(00:06:44) Role of Health Experts in AI

Integrating insights from medical professionals into AI coaching systems.

(00:10:21) Personalization in AI Coaching

How AI coaches can adapt personalities and avatars to cater to user preferences.

(00:12:51) Group Dynamics in AI Coaching

Pros and cons of adding social features and group support to AI coaching systems.

(00:14:08) Ambient Awareness in Technology

Ambient awareness and how it enhances user engagement without active attention.

(00:17:44) Using AI in Elementary Education

Narrative-driven tutoring systems to inspire kids' learning and creativity.

(00:22:59) Encouraging Student Writing with AI

Using LLMs to motivate students to write through personalized feedback.

(00:23:52) Scaling AI Educational Tools

The ACORN project and creating dynamic, scalable learning experiences.

(00:27:58) Human-Centered AI

The concept of human-centered AI and its focus on designing for society.

(00:30:34) Conclusion

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Episode Transcripts >>> The Future of Everything Website

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Climate change authority Noah Diffenbaugh says that the effects of climate change are no longer theoretical but apparent in everyday, tangible ways. Still, he says, it is not too late to better understand the effects of climate change, to mitigate them through reductions in greenhouse gas emissions and other measures, and to adapt how we live in the face of a warmer planet. Society is falling behind in its ability to deal with increasingly extreme climate events but solutions are not out of reach, Diffenbaugh tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your quest. You can send questions to thefutureofeverything@stanford.edu.

Episode Reference Links:

• Stanford Profile: Noah Diffenbaugh

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Noah Diffenbaugh, a professor of Earth System Science at Stanford University.

(00:02:34) Global Impact of Climate Change

The major areas where climate change is having the greatest impact globally.

(00:03:27) Climate Phenomena and Humans

Connecting climate science with localized human impacts

(00:06:16) Understanding Climate Forcing

The concept of "climate forcing" and its significance in Noah’s research.

(00:10:00) Geoengineering and Climate Interventions

The potential and risks of intentional climate interventions.

(00:21:18) Adaptation to Climate Change

How humans are adapting to climate change and why we might be falling behind.

(00:25:19) Increase in Extreme Events

Why extreme climate events are becoming exponentially more frequent and severe.

(00:28:34) AI in Climate Research

How AI is revolutionizing climate research by enabling predictive capabilities.

(00:32:26) Conclusion

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Climate modeler Aditi Sheshadri says that while weather forecasting and climate projection are based on similar science, they are very different disciplines. Forecasting is about looking at next week, while projection is about looking at the next century. Sheshadri tells host Russ Altman how new data and techniques, like low-cost high-altitude balloons and AI, are reshaping the future of climate projection on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your quest. You can send questions to thefutureofeverything@stanford.edu.

Episode Reference Links:

• Stanford Profile: Aditi Sheshadri

Connect With Us:

• Episode Transcripts >>> The Future of Everything Website
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• Connect with School of Engineering >>> Twitter/X

Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Aditi Sheshadri, a professor of Earth systems science at Stanford University.

(00:02:58) Climate Projection vs. Weather Forecasting

The differences between climate projection and weather forecasting.

(00:04:58) The Window of Chaos

The concept of the "window of chaos" in climate modeling.

(00:06:11) Scale of Climate Models

The limitations and scale of climate model boxes.

(00:08:19) Computational Constraints

Computational limitations on grid size and time steps in climate modeling.

(00:10:56) Parameters in Climate Modeling

Essential parameters measured, such as density, temperature, and water vapor.

(00:12:18) Oceans in Climate Models

The role of oceans in climate modeling and their integration into projections.

(00:14:35) Atmospheric Gravity Waves

Atmospheric gravity waves and their impact on weather patterns.

(00:18:51) Polar Vortex and Cyclones

Research on the polar vortex and on tropical cyclone frequency.

(00:21:53) Climate Research and Public Awareness

Communicating climate model findings to relevant audiences.

(00:23:33) New Data Sources

How unexpected data from a Google project aids climate research,

(00:25:09) Geoengineering Considerations

Geoengineering and the need for thorough modeling before intervention.

(00:28:19) Conclusion

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