The Future of Everything

Law professor Julian Nyarko has drawn attention for his studies using large language models to investigate and improve legal education and explore AI’s biases. He hopes AI can become a reliable, always-on legal learning and assistance tool to lower costs and expand access to legal services. In one recent study, he asked a group of law professors to evaluate written answers to student questions. Three-quarters of the time, the professors preferred AI-generated answers to those of their human colleagues. “AI is good at law,” Nyarko says, the challenge now is to use it most effectively, he tells host Russ Altman in 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 question. You can send questions to thefutureofeverything@stanford.edu.

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Julian Nyarko, a professor of law at Stanford University.

(00:02:31) Path into AI and Law

How Nyarko’s early work led him to legal AI.

(00:05:03) Law, Economics, and Computation

How Nyarko’s training, methods, and self-taught coding shaped his research.

(00:07:23) Building the LIFT Lab

Why a law professor started a lab.

(00:09:06) Evaluating Legal AI

How AI raises fundamental questions about what counts as good lawyering.

(00:10:22) Improving Legal Services

Using AI to work faster, reduce errors, and make informed decisions.

(00:10:57) Rethinking Legal Education

How AI may change the way future lawyers learn 

(00:11:51) AI in Office Hours

How AI answers law students’ questions compared with human professors.

(00:15:18) Surprising Results

Why AI answers were often preferred 

(00:16:16) What the Study Shows

The findings support AI tutoring, but don’t prove AI improves learning.

(00:18:48) Limits of One-Shot Answers

Why real teaching often depends on dialogue, clarification, and productive struggle.

(00:20:59) AI for Social Science

How AI can become both an object of study and a tool.

(00:22:43) Research Agents

Using AI to test claims and make previously impossible research scalable.

(00:24:51) Agentic AI in the Lab

How Socratic dialogue with AI can sharpen research ideas.

(00:26:07) Fairness and Bias

How computational tools can be audited for bias and used to audit decision-making.

(00:27:29) Discrimination in Models

Exploring bias and how it can be reduced.

(00:30:16) Disparate Impact

How policies and systems disadvantage groups even without explicit intent.

(00:32:53) From Evidence to Policy

How Nyarko’s lab works with stakeholders to surface disparities.

(00:34:49) Future In a Minute

Rapid-fire Q&A: justice, talent, and the future of legal AI.

(00:36:57) Conclusion

 

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In the western United States and Canada, this time of year is the beginning of peak wildfire season, a reality that's become impossible to ignore. In light of this, we're re-releasing my conversation with energy and climate policy expert Michael Wara on the future of wildfire management. Michael walks us through how we got here, why fires are burning bigger and more frequently, and what a smarter, more proactive approach to managing our landscapes might look like. Whether you're in a fire-prone region or simply paying attention to the changing climate around you, this one is well worth another listen.

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 question. You can send questions to thefutureofeverything@stanford.edu.

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Stanford Profile: Michael Wara

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Michael Wara, a wildfire expert and professor of law at Stanford University.

(00:02:05) Journey to Wildfire Research

How Michael’s clean energy work led to wildfire research.

(00:03:36) Communities at the Frontlines

The community-level challenges and responsibilities in fire prevention.

(00:05:53) Shifting Community Perspectives

How awareness is rising but state efforts remain misaligned.

(00:08:17) Legacy Homes, Modern Risk

Why older homes pose a major risk and retrofitting is crucial.

(00:09:55) Utility-Led Safety Limitations

The significant but insufficient progress utilities have made.

(00:13:23) Targeting High-Risk Areas

How utilities now prioritize high-risk areas for safety upgrades.

(00:14:30) Insurance Industry Realities

Why insurers can't price risk without crashing markets.

(00:17:19) Urban Wildfires

How today's major fires in suburbs are mostly fueled by homes.

(00:22:12) The Climate Change Multiplier

The impact of atmospheric dryness and fuel moisture on fire risk.

(00:24:45) New Fire Regulations

Recent mandates that have been implemented to decrease fire risk.

(00:28:17) Rethinking Wildfire Communication

Why better messaging is key to changing homeowner behavior.

(00:31:52) Conclusion

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“Stories … are powerful tools that can help us make sense of our lives,” says physician-scientist Maya Adam. She now combines visual storytelling and health education to create animations that go beyond the barriers of language and culture to convey important health messages. The subject matter ranges from vaccine acceptance and addiction to mental health and nutrition. These emotionally engaging narratives – often without a single spoken word – are more effective than traditional pamphlets and lectures, Adam says. Visual stories have the potential to achieve “near-universal understanding” that can support better health outcomes, she 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 question. You can send questions to thefutureofeverything@stanford.edu.

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Stanford Profile: Maya Adam

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Maya Adam, a professor of pediatrics and infectious disease from Stanford University.

(00:03:43) From Ballet to Medicine

How Adam’s background shaped her approach to health education.

(00:05:02) Why Stories Work

Why lived experience makes evidence-based health recommendations more meaningful.

(00:06:17) The Story Creation Process

Adam’s techniques for creating effective scalable health stories on any topic

(00:09:20) Real World Stories

Adam shares some particularly challenging topics the team has created stories for

(00:11:10) Global Accessibility

Designing stories and characters that can resonate across cultures and contexts.

(00:12:38) Measuring Impact

Using technology to run trials to test and measure impact

(00:15:23) Iterating the Message

Adapting and changing approaches to create the most effective message

(00:17:53) AI and Storytelling

How AI is beginning to affect health communication and creative production.

(00:19:45) Testing Human vs. AI Art

A trial comparing responses to human-created and AI-generated health storytelling.

(00:25:42) Human-in-the-Loop AI

How AI may best support artists and clinicians by reducing burden rather than replacing

(00:27:43) Future In a Minute

Rapid-fire Q&A: stories, collaboration, media, and the future of health communication.

(00:29:44) Conclusion

 

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The World Cup is here, and while we watch some of the world's greatest athletes competing on a global stage, it's fascinating to consider what effect this intense activity may have on the human body. With that in mind, we're re-releasing our conversation with Stanford biochemist Jonathan Long on the future of exercise. Jonathan studies the chemistry of what happens inside your body when you move, and his findings are pointing toward some genuinely surprising possibilities — including treatments for obesity, diabetes, and even, someday, an exercise pill. If the athleticism on the pitch has you feeling inspired, this one is well worth another listen.

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 question. You can send questions to thefutureofeverything@stanford.edu.

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Stanford Profile: Jonathan Long

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Jonathan Long, a professor of pathology from Stanford University.

(00:02:02) Effective Weight Loss Drugs

The history and development of GLP-1 receptor agonists.

(00:04:04) Understanding Metabolism and Exercise

Why Long’s lab starts with molecules to understand metabolism and physical activity.

(00:05:10) Animal Models in Exercise Studies

The use of animal models in exercise studies and the discovery of Lac-Phe.

(00:06:47) Psychological Preparation for Exercise

The psychological aspects of exercise and the involvement of endocannabinoids in exercise motivation.

(00:09:00) Lac-Phe's Role and Mechanism

The role of Lac-Phe and its production in the gut.

(00:12:08) Differences in Exercise Response

Differences in exercise response between trained athletes and untrained individuals.

(00:12:57) Diabetes and Metabolic Diseases

The relationship between diabetes, exercise, and metabolic diseases.

(00:15:01) Lac-Phe as a Potential Therapeutic

The potential of Lac-Phe as a weight loss drug, and parallels to GLP-1 drug development.

(00:16:21) Importance of How Weight is Lost

Whether the method of weight loss matters, and the importance of preserving lean muscle mass.

(00:18:37) Exercise as Medicine

The concept of exercise as medicine, and defining physical activity at the same resolution as modern medicines.

(00:22:11) Metformin and Exercise Pathways

The unexpected connection between metformin and the Lac-Phe pathway.

(00:24:01) Prospects of an Exercise Pill

The future of an exercise pill, and the challenges associated with its development.

(00:27:05) Conclusion

Final thoughts on the future of exercise.

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Professor of ophthalmology Daniel Palanker is a physicist who has combined his skills in optics and electronics to create PRIMA – the Photovoltaic Retinal Implant. Inserted beneath the retina, it restores vision to patients blinded by retinal degeneration, allowing them to read and write – and with the next-generation software, to recognize faces. PRIMA’s photovoltaic pixels act like tiny solar panels, converting light into electricity to stimulate the remaining retinal neurons. Better yet, the growing field of brain-computer interfaces may have implications beyond ophthalmology. “Unlike medicine, where the road ends with curing a disease or restoring lost function, the prospects for brain-machine interfaces may be infinite,” Palanker 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 question. You can send questions to thefutureofeverything@stanford.edu.

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Stanford Profile: Daniel Palanker

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Daniel Palanker, a professor of ophthalmology and electrical engineering at Stanford University.

(00:03:17) Path into Ophthalmology

How Palanker’s background in physics and optics led him to vision research.

(00:04:33) How Vision Works

A primer on the eye, retina, photoreceptors, and the neural code of sight.

(00:08:50) Retinal Degeneration

How diseases like macular degeneration and inherited retinal disorders damage vision.

(00:13:18) The PRIMA Implant

How a photovoltaic retinal implant converts light into electrical stimulation.

(00:15:05) Augmented Reality Glasses

How camera-equipped glasses amplify and project images to power the implant.

(00:17:42) From Reading to Face Recognition

Why grayscale vision is the next step toward recognizing faces.

(00:20:18) Implanting the Device

How the wireless chip is placed under the retina and powered by light.

(00:21:45) Replaceable Vision Technology

How future generations of implants could be swapped in for higher resolution.

(00:22:28) Limits of Resolution

Why geometry and proximity to neurons determine how small pixels can get.

(00:24:00) Moving to 3D Electrodes

How pillar-shaped electrodes help neurons move closer to the implant.

(00:26:28) Clinical Path Forward

The status of European trials, FDA discussions, and future patient access.

(00:28:10) Safety and Real-World Use

What trials reveal about surgical risks, durability, and patients using implants at home.

(00:30:11) Future In a Minute

Rapid-fire Q&A: neural coding, brain-machine interfaces, and restoring vision.

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