The Future of Everything

Prior to becoming an anesthesiologist, Alyssa Burgart trained in bioethics. She now counts herself among a growing number of certified clinical bioethicists who help doctors, nurses, patients, and their families handle ethically complex medical decisions at the bedside. Bioethicists are critical to care, Burgart argues, helping patients facing difficult choices to clarify personal values and weigh a complex array of risks and benefits, as well as emotions and familial, cultural, and religious norms. While much of her work is in pediatrics and maternal-fetal cases, she also studies how moral distress and moral injury impact clinicians, contributing to burnout among doctors and nurses. Having a strong ethical community brings resilience to these challenging environments, Burgart 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 Alyssa Burgart, a professor of anesthesiology and perioperative pain at Stanford University.

(00:03:16) Path into Bioethics & Anesthesiology

How Burgart became a bioethicist and then chose anesthesiology.

(00:05:18) What Bioethics Means

How bioethics helps connect medical decisions to values, risks, and benefits.

(00:07:03) Making Hard Decisions Manageable

How ethics consultation helps clinicians act with integrity.

(00:08:33) Ethics Consults

A detailed explanation of hospital ethics services 

(00:12:23) Pediatric Ethics

Examples of Dr. Burgart’s work with children, families, and clinicians

(00:15:45) Culture, Faith, and Trust

Navigating cultural and religious differences as a bioethicist.

(00:17:57) Family Decision-Making

How ethics consultants help families and care teams honor a patient’s voice.

(00:21:55) Moral Injury

What is moral injury and how do clinicians specifically experience it?

(00:24:52) Institutional Betrayal

Why barriers like policies, laws, and denied approvals can create moral strain.

(00:26:37) Moral Distress

What is moral distress and how does it manifest itself in healthcare.

(00:28:28) Moral Residue

When clinicians experience repeated moral strain and cannot recover between incidents.

(00:29:33) Treating Moral Injury & Distress

Strategies for helping clinicians manage these parts of their work.

(00:33:54) Future In a Minute

Rapid-fire Q&A: clinical bioethics, human dignity, and moral resilience.

(00:36:15) Conclusion

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These days, AI is everywhere, and it’s increasingly hard to separate the gains from the slop. With that in mind, we're re-releasing my conversation with Stanford Law professor Daniel Ho on the future of AI and the law. When we look for applications where AI can deliver measurable benefit, the legal profession stands out, both for its potential gains in efficiency and equity, and for how much is at stake if we get it wrong. Dan's research — from using AI to identify racist property covenants buried in county deed records, to mapping obsolete regulations that waste thousands of hours of government time — shows what's possible when the technology is applied with rigor and purpose. If you’re curious about how AI can serve both justice and good governance, this one is well worth another listen.

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Dan Ho, a professor of law, political science, and computer science at Stanford University.

(00:02:19) Path into Legal AI

How Ho’s background shaped his interest in law, and technology.

(00:03:35) What Lawyers Do

What makes law a complex domain for AI.

(00:05:28) Legal Hallucinations

When AI  performs well and when it fails. 

(00:07:52) Searching Legal Records in California

How AI can help identify outdated, harmful, or legally important material.

(00:10:28) Scaling Redaction

How a model accelerated a process that overwhelmed county recorder offices.

(00:13:04) Legal Reform at Scale

How AI has supported legal reform by scanning massive bodies of law.

(00:15:02) STARA & The City of San Francisco

How AI was used to go through San Francisco’s code and clean up reporting.

(00:20:53) Outdated Obligations

How “regulatory sludge” takes the time & resources of the public service

(00:25:02) Open vs. Closed AI

The differences and associated risks of the different AI systems.

(00:30:58) Legal Chatbots

Why legal chatbots are promising but risky.

(00:33:42) Conclusion

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Dr. Karen Adams, obstetrician/gynecologist and Farwell Family Director of the Stanford Program in Menopause and Healthy Aging, studies menopause and, perhaps more importantly, perimenopause – the critical years preceding it. During this time, hormone-related symptoms like mood instability, sleep disruption, hot flashes, and joint pain can be severe even though periods continue. Adams explains that perimenopausal symptoms are often misdiagnosed and improperly treated. She says hormonal therapies are safe and effective in perimenopause and menopause, and can even have heart and bone benefits. “Menopause is inevitable, but suffering is not,” Adams 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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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Karen Adams, a professor of obstetrics and gynecology at Stanford University.

(00:02:11) Path into Menopause Medicine

How Adams built one of the first clinical programs focused on women over 40.

(00:04:19) Menopause and Perimenopause

What menopause is and how the hormonal transition often begins years earlier.

(00:06:19) Beyond Hot Flashes

The wide range of symptoms that can appear during perimenopause.

(00:11:09) Pregnancy Risk During Perimenopause

Why contraception can still matter until a full year without a period.

(00:11:11) Unpredictable Symptoms

Why perimenopausal symptoms can be harder to recognize than PMS.

(00:13:37) Hormone Therapy

How treatment differs during perimenopause and after menopause.

(00:22:57) The Women’s Health Initiative

What the landmark hormone therapy study showed.

(00:27:53) Sexual Health and Vaginal Estrogen

Why local estrogen can safely treat genitourinary symptoms for many women.

(00:30:36) Future In a Minute

Rapid-fire Q&A: menopause care, women’s health, and better clinical support

(00:32:58) Conclusion

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Biochemist Suzanne Pfeffer is an expert on the molecular roots of Parkinson’s disease. Her work focuses on mutated proteins linked to Parkinson’s risk. She’s discovered, for instance, that drugs inhibiting one of the proteins can help neurons regrow primary cilia and stave off cell death, reversing disease progression. Since similar drugs are in clinical trials, her findings bring great hope for people with a subtype of Parkinson’s and hopefully can be linked to earlier detection through warning signs like REM sleep disruptions and loss of smell. “This is precision medicine,” Pfeffer tells host Russ Altman of the future of Parkinson’s disease 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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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Suzanne Pfeffer, a professor of biochemistry at Stanford University.

(00:03:25) Path into Parkinson’s Research

How Pfeffer’s protein work led to a life-changing work on Parkinson’s disease.

(00:05:28) Parkinson’s Primer

The various causes and the effects of the disease on the brain and body.

(00:10:26) Lewy Bodies and Dementia

How Lewy bodies, synuclein, and dementia relate to Parkinson’s disease.

(00:11:56) Molecular Trafficking

Pfeffer breaks down the effects of LRRK2 and GBA mutations in the brain.

(00:16:10) Early Disease Changes

Some of the early changes in the body and how they show up as symptomatically.

(00:20:04) Current Treatments

The limitations of symptom-focused treatments.

(00:21:46) Treating Earlier

Opportunities for slowing or reversing disease progression when detected earlier.

(00:22:32) Targeting LRRK2

Current research on disease treatment & trial challenges.

(00:27:33) The Value of Basic Science

Why curiosity-driven research can unexpectedly lead to disease breakthroughs.

(00:29:33) Future In a Minute

Rapid-fire Q&A: biomarkers, brain donation, and better Parkinson’s treatments.

(00:31:52) Conclusion

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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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