The Future of Everything

Julie Owono is a lawyer, executive director of Internet Sans Frontières and a fellow at the Stanford Center on Philanthropy and Civil Society. She wants the world to know that the internet is the not the same for every person, everywhere. Born in Cameroon, and having grown up in Russia, she understands firsthand that every nation sets and maintains its own content standards.Owono has dedicated her career to establishing and securing basic digital rights, but also to developing standards by which social media giants—like Facebook, Google and Twitter—can distinguish hate speech from free speech. In many ways, Owono says, the global internet is a local endeavor.Owono tells Stanford Engineering’s The Future of Everything podcast and host Russ Altman that this dynamic means local voices will be critical to fairly determining standards of speech and, by extension, to charting the future of the global internet. You can listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Words are a window into human psychology, society, and culture, says Stanford linguist and computer scientist Dan Jurafsky. The words we choose reveal what we think, how we feel and even what our biases are. And, more and more, computers are being trained to comprehend those words, a fact easily apparent in voice-recognition apps like Siri, Alexa and Cortana.Jurafsky says that his field, known as natural language processing (NLP), is now in the midst of a shift from simply trying to understanding the literal meaning of words to digging into the human emotions and the social meanings behind those words. In the social sciences, our great digital dialog is being analyzed to tell us who we are. And, by looking at the language of the past, language analysis promises to reveal who we once were. Meanwhile, in fields such as medicine, NLP is being used to help doctors diagnose mental illnesses, like schizophrenia, and to measure how those patients respond to treatment.The next generation of NLP-driven applications must not only hear what we say, but understand and even reply in more human ways, as Dan Jurafsky explains in his own words to host Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

When Riitta Katila looks at old photos or movies about the space program of the 1960s, she sees one common thread among the people depicted there — homogeneity. The engineers and technicians who first put humans on the moon were, almost without exception, white and male.While society has come a long way in the decades since, Katila, who is an expert in technology strategy and organizational learning, says there’s still a long way to go. She notes that companies need innovation not only to reach the top, but to stay there. And now more than ever, innovative companies should be hiring, promoting, and listening to a broader range of voices.The good news is that innovation can be taught. It’s like a recipe, says Katila, who encourages entrepreneurs — even those who have already built successful companies — to seek out mentors who can help them navigate the future. More important, those same entrepreneurs need to proactively identify mentors who can empower their team members to think like innovators too, as Katila tells Stanford Engineering’s The Future of Everything podcast, hosted by bioengineer Russ Altman. You can listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

As the silicon chip embarks upon its second half-century of dominance in computing and communications, the field is confronting fundamental boundaries that threaten to halt that progress in its tracks.The transistor cannot get much better or smaller and the copper wires that connect them cannot carry much more data than they do now. But, says electrical engineer David Miller, an alternative technology that uses light instead of electricity has the potential to transmit vastly more data than present technologies. It’s known as photonics.“A silicon chip these days looks like six Manhattan grids stacked atop one another,” Miller says of the challenge facing today’s technology. Photonics holds the promise of more powerful computing by beaming tiny packets of photons through light-bearing conduits that carry 100,000 times more data than today’s comparable wires, and it can do it using far less energy, too.Before that day can arrive, however, Miller says photonic components need to become much smaller and less expensive to compete with the sheer scale advantages silicon enjoys, and that will require investment. But, for once, a way forward is there for the asking, as Miller tells bioengineer Russ Altman, host of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In recent decades, medical and biological science have advanced by leaps and bounds using technologies that allow us to peer into the brain in myriad new and insightful ways — MRI, CT, PET, EEG, etc.However, Stanford electrical engineer Jin Hyung Lee says, we are still missing critical insights that could lead to a cure for currently incurable brain diseases like Alzheimer’s, Parkinson’s, epilepsy and others.Even in diagnosis, we still rely on “diagnosis of exclusion,” where tests are used to exclude other conditions that are relatively easy to identify, such as a tumor. However, there is still no way, for instance, to directly test why one’s memory is failing or why motor functions decline and lead to tremors.Lee’s approach is to directly identify the brain’s underlying algorithms and to enable quantitative diagnosis of its malfunctions in order to design approaches to cure brain diseases. She employs optogenetic MRI and various measurement tools at different scales, which she then uses to reconstruct the algorithms of brain function using artificial intelligence. Lee defines healthy circuitry and function, which in turn allows identification of the characteristics of dysfunction. Her approach has put Lee on the cusp of new understanding and new treatments for epilepsy, for instance, as she tells Stanford Engineering’s The Future of Everything podcast, hosted by bioengineer Russ Altman. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Stanford’s Mark Schnitzer says several of the more exciting recent advances in his field of applied physics have come through developing new imaging technologies that peer into the brain as never before. What’s more, Schnitzer says the insights gained have put the world closer to solving long-vexing brain diseases, like Parkinson’s and others, where the circuitry of the brain seems to be malfunctioning.Schnitzer says that these new imaging methods are helping medical science discern the specific functions of various cells that make up the brain’s complex communications systems. No longer is the brain seen as a monolith of neurons, but instead as a complex organ made up of numerous cell types, each with its own role to play in proper function.Best of all, medical science is starting to move toward manipulating these cells with new drugs and other treatments that could lead to a cure or effective treatment for previously untreatable diseases and chronic pain, as Schnitzer tells Stanford Engineering’s The Future of Everything podcast and host, bioengineer Russ Altman. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The old maxim holds that a lie spreads much faster than a truth, but it has taken the global reach and lightning speed of social media to lay it bare before the world.One problem of the age of misinformation, says sociologist and former journalist Mutale Nkonde, a fellow at the Stanford Center on Philanthropy and Civil Society (PACS), is that the artificial intelligence algorithms used to profile users and disseminate information to them, whether truthful or not, are inherently biased against minority groups, because they are underrepresented in the historical data upon which the algorithms are based.Now, Nkonde and others like her are holding social media’s feet to the fire, so to speak, to get them to root out bias from their algorithms. One approach she promotes is the Algorithmic Accountability Act, which would authorize the Federal Trade Commission (FTC) to create regulations requiring companies under its jurisdiction to assess the impact of new and existing automated decision systems. Another approach she has favored is called “Strategic Silence,” which seeks to deny untruthful users and groups the media exposure that amplifies their false claims and helps them attract new adherents.Nkonde explores the hidden biases of the age of misinformation in this episode of Stanford Engineering’s The Future of Everything podcast, hosted by bioengineer Russ Altman. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Stanford’s Karen Liu is a computer scientist who works in robotics. She hopes that someday machines might take on caregiving roles, like helping medical patients get dressed and undressed each day. That quest has provided her a special insight into just what a monumental challenge such seemingly simple tasks are. After all, she points out, it takes a human child several years to learn to dress themselves — imagine what it takes to teach a robot to help a person who is frail or physically compromised?Liu is among a growing coterie of scientists who are promoting “physics-based simulations” that are speeding up the learning process for robots. That is, rather than building actual robots and refining them as they go, she’s using computer simulations to improve how robots sense the physical world around them and to make intelligent decisions under changes and perturbations in the real world, like those involved in tasks like getting dressed for the day.To do that, a robot must understand the physical characteristics of human flesh and bone as well as the movements and underlying human intention to be able to comprehend when a garment is or is not going on as expected.The stakes are high. The downside consequence could be physical harm to the patient, as Liu tells Stanford Engineering’s The Future of Everything podcast hosted by bioengineer Russ Altman. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

It has been said that batteries hold the key to a sustainable future.But so-called “clean energy” does not come without environmental costs. For instance, says Stanford geoscientist Jef Caers, the batteries in a single Tesla contain some 4.5 kilograms — about 10 pounds — of cobalt, in addition to plenty of lithium and nickel, too. With some 300 million cars in the U.S. right now, a full transition to electric vehicles would be impossible without new resources. But, finding new deposits and getting them safely out of the ground is an expensive and environmentally fraught proposition. Half of all cobalt reserves and most of current production come from just one unregulated country, Congo. To close the gap using environmentally and labor-regulated resources, Caers says we need AI to rapidly explore countries with stricter safeguards.To help, geoscientists like Caers are turning to data science and artificial intelligence to quickly identify new resources, to get the most out of those we already know about and to improve refining processes to leave as small an environmental footprint as possible. Their success, he says, could be key to America’s environmental future and its long-term energy independence. Learn more on this episode of Stanford Engineering’s The Future of Everything podcast, hosted by Stanford bioengineer Russ Altman. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Evan Reed and a team of scientists recently identified a promising solid material that could replace highly flammable liquid electrolytes in lithium-ion batteries.The trick? Reed didn’t discover the material the old-fashioned way, using trial and error to narrow down a list of candidates. Instead, he used computers to do the legwork for him. He says that until recent advances in computer science, the seemingly never-ending search for new materials was more like a quest for unicorns. Breakthrough materials must possess that rarest of combinations: precise physical characteristics with few if any downsides.It's exacting and time-consuming work, Reed says, but computers are accelerating the pace of discovery. He now believes the future of materials science lies at the heart of a computer algorithm, as he tells listeners in this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Renée DiResta is research manager at the Stanford Internet Observatory, a multi-disciplinary center that focuses on abuses of information technology, particularly social media. She’s an expert in the role technology platforms and their “curatorial” algorithms play in the rise and spread of misinformation and disinformation.Fresh off an intense period keeping watch over the 2020 U.S. elections for disinformation as part of the Election Integrity Partnership, DiResta says the campaign became one of the most closely observed political dramas in American history.She says that whether it comes from the top down or the bottom up, bad information can be spotted and beaten, but overcoming falsehoods in the future will require vigilance and a commitment to the truth. She explains more on Stanford Engineering’s The Future of Everything podcast, with host Russ Altman. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Once the bathwater is drained, the toilet flushed or the laundry done, few give a passing thought to the wastewater that leaves our homes. But chemical engineer Will Tarpeh might change your mind, if you give him the chance.Tarpeh says that that water is a literal mine of valuable chemicals. Chemicals like nitrogen, phosphorus and potassium make great fertilizers. Lithium can be used in lithium ion batteries. And even pharmaceuticals could be recovered and reused. In fact, Tarpeh points out that if we could harvest all the world’s urine, it could supplant 20–30% of our nitrogen needs — and in some places can be cheaper to do than existing production and transport methods.Waste, Tarpeh says, is just a state of mind. His “pipe dream,” he says, is to develop next-generation treatment plants on the neighborhood or even household scale able to extract the valuable chemicals in water most would rather send down the drain. Tarpeh tells bioengineer Russ Altman all about it in this the latest episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Bioengineer Kwabena Boahen builds highly efficient “neuromorphic” supercomputers modeled on the human brain. He hopes they will drive the artificial intelligence future. He uses an analogy when describing the goal of his work: “It’s LA versus Manhattan.” Boahen means structurally. Today’s chips are two dimensional — flat and spread out, like LA. Tomorrow’s chips will be stacked, like the floors of the skyscrapers on a New York block. In this analogy, the humans are the electrons shuffling data back and forth. The shorter distances they have to travel to work, and the more they can accomplish before traveling home, will drive profound leaps in energy efficiency. The consequences could not be greater. Boahen says that the lean chips he imagines could prove tens-of-thousands times less expensive to operate than today’s power hogs. To learn how it works, listen in as Kwabena Boahen describes neuromorphic computing to fellow bioengineer Russ Altman in the latest episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In a world where a drug takes years and billions of dollars to develop, just one in 20 candidates makes it to market. Daphne Koller is betting artificial intelligence can change that dynamic.Twenty years ago, when she first started using artificial intelligence to venture into medicine and biology, Koller was stymied by a lack of data. There wasn’t enough of it and what there was, was often not well suited to the problems she wanted to solve. Fast-forward 20 years, however, and both the quantity and quality of data, and the tools for studying biology, have advanced so dramatically that the adjunct professor of computer science at Stanford founded a company, insitro, that uses machine learning (a subspecialty of ​artificial intelligence) to explore the causes and potential treatments for some very serious diseases.She tells bioengineer Russ Altman about the lessons she’s learned along the way, and the challenges and rewards of getting diverse teams of experts from many fields to speak the same language. It’s all on this episode of Stanford Engineering’s The Future of Everything podcast. Listen here, and subscribe to the podcast here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

When Stanford bioengineer Markus Covert first decided to create a computer model able to simulate the behavior of a single cell, he was held back by more than an incomplete understanding of how a cell functions, but also by a lack of computer power. His early models would take more than 10 hours to churn through a single simulation and that was when using a supercomputer capable of billions of calculations per second.Nevertheless, in his quest toward what had been deemed "a grand challenge of the 21st century," Covert pressed on and eventually published a paper announcing his success in building a model of just one microbe: E. coli, a popular subject in biological research. The model would allow researchers to run experiments not on living bacteria in a lab, but on a simulated cell on a computer.After all was said and done, however, the greatest takeaway for Covert was that a cell is a very, very complex thing. There were fits and starts and at least one transcendent conceptual leap — which Covert has dubbed “deep curation” — needed to make it all happen, but he found a way. As Covert points out, no model is perfect, but some are useful. And that is how usefulness, not perfection, became the goal of his work, as he tells fellow bioengineer Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast. Listen here, and subscribe to the podcast here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

COVID-19 is changing how many scientists, like Stanford sleep expert Rafael Pelayo, MD, view their field. First off, the shift to telemedicine is providing Pelayo, author of the new book How to Sleep, an unprecedented glimpse into the sleep environments of his patients. “I’m making house calls for the first time,” he says.Second, surprisingly, some of his patients, unburdened of long commutes, say they are sleeping and dreaming more than ever. But, others are not so fortunate, reporting increased trouble sleeping and more nightmares. Pandemic-induced or not, the consequences of lost sleep are universal and readily apparent in the country’s diminished productivity, in the rates of stroke, heart attacks and car accidents, and in the pervasive irritable mood many can’t seem to escape.To get a better night’s sleep, Pelayo says, put the screens away, consider that continuous positive airway pressure (CPAP) machine if you snore (it could save your life, he says), and find a way to create a personal sleep environment even if you share a bed with someone you love.Join us as Rafael Pelayo and our host, Stanford bioengineer, Russ Altman, talk sleep on this episode of Stanford Engineering’s The Future of Everything podcast. Listen here, and subscribe to the podcast here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Marietje Schaake was a Member of the European Parliament from 2009 to 2019 and now serves as the international policy director at Stanford University’s Cyber Policy Center and international policy fellow at Stanford’s Institute for Human-Centered Artificial Intelligence. As she has watched democracy evolve in the age of instantaneous global communication and hyperconnected social media, she has grown concerned about the resilience of democracy as technology disrupts the status quo. While the technologies—and the often-unregulated companies who created them—claim to be well-meaning, she says democracy is under attack from propagandists and bad actors using these transformative tools in troubling ways. The business models based on surveillance and advertising were never designed with preserving democracy in mind. We now find ourselves at a decisive moment for the future of elective government, she says. America and other democratic nations can expose the meddlers and their techniques or succumb to their approaches. The solutions, she says, begin at the grassroots and with the tech companies. We need real-time and independent monitoring and research to better expose manipulations and to allow for evidence-based policy making. Join Stanford Engineering’s The Future of Everything podcast for an insider’s sobering look at democracy in the digital age. Listen here, and subscribe here to the podcast. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Andrew Huberman is a Stanford neurobiologist and ophthalmologist keenly interested in the biology of stress and ways to manage stress.He’s developed and tested a number of stress-relieving techniques — from specific patterns of breathing to visual tools — and uses virtual reality to help humans control their stress in adaptive ways. He is also testing how people can access better sleep using stress-relief tools. Much of this work is done in collaboration with David Spiegel, MD, associate chair of psychiatry and behavioral sciences at Stanford Medicine.Huberman studies how the nervous system takes in and processes information and uses it to drive reflexive and deliberate behavior. In that regard, humans are largely visual animals. The vast majority of the information we collect about the world comes through the eyes, and those circuits are tied directly to our most primordial “fight or flight” systems. Light, and how our brains process light energy, is closely tied to our stress mechanisms. Our most immediate reaction to stress, he notes, is for our pupils to dilate, which changes how we see the world — literally — in a way that allows us to better respond to threats. Breathing and vision can also be used to control stress.Huberman tells us all about it in this episode of Stanford Engineering’s The Future of Everything podcast, hosted by Stanford bioengineer Russ Altman. Listen and subscribe to the podcast here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Manu Prakash was in France when COVID-19 took hold throughout the world. There, the Stanford bioengineer, famous for “frugal science” like his $1 field microscope made of paper, witnessed the challenges a relatively well-resourced nation experienced holding back the disease. His head was soon filled with visions of the nightmare awaiting developing nations, given that a COVID-19 test in developing countries can cost as much as $400.In a flurry, Prakash jotted down an engineering manifesto of sorts for a worldwide revolution in open-source, inexpensive healthcare solutions. As he saw it, here were three areas of greatest need — diagnostics, protective equipment and critical care.From his lab at Stanford, Prakash, his students and partners in academia, industry and government around the world led a frenzy of invention that yielded an array of transformative products in just months. There was the electricity-free COVID-19 test based on a simple children’s flashlight. There was Pneumask, a full-face, reusable N95 protective equipment for caregivers inspired by the mask Prakash uses in one of his favorite pastimes, snorkeling. And then there was the “N95 factory in a box” Prakash and his lab developed using cotton candy machines to spin N95-quality filtration materials from waste plastics. Finally, to tackle one of the most technical challenges of all, he built a global consortium with manufacturing partners in India, Kenya and Nepal to design an open-source full-feature ICU ventilator, known as Pufferfish (Prakash has a penchant for naming products after marine life) — bringing a low-cost critical care solution to the world. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

With the emergence of touchscreen smartphones, tablets and watches, so much of our lives is spent on our devices that in many ways we are what appears on screen. This “mediatization,” as Byron Reeves, a professor of communication at Stanford University, puts it, sparked a remarkable and unprecedented study of the way we live today.In a series of field studies, Reeves has recorded screen time of his subjects one frame every five seconds for days on end — with promises of absolute privacy, of course. He then uses artificial intelligence to decipher it all — words and images are recorded and analyzed. The portraits that emerge play out like cinema, revealing never-before-imagined insights into how people live in the screen-time world. Reeves says the pervading sense that everyone is multitasking and that attention spans are narrowing is not just a hunch, but demonstrable in the data. Our screens are often filled with radically different content side-by-side and each bit gets consumed in rapid-fire bursts of focus, often no more than 10 to 20 seconds each. Join us for a fascinating look at our screen-time culture on the latest episode of Stanford Engineering’s The Future of Everything podcast. Listen here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

There was a time when all great cities were built near water. Whether for agriculture, aesthetics, energy or just plain drinking, water was a life-affirming, life-sustaining resource. But with the advent of advanced engineering in the form of dams, pumps and pipes, cities like Los Angeles thrived in places with very little fresh water. Now, global climate change is leaving many of those cities in danger of running dry.But there is hope on the horizon, says Newsha Ajami, senior research engineer at the Woods Institute for the Environment and director of urban water policy with Stanford University’s Water in the West program. Just as engineering made it possible to store and pump fresh water great distances, the field is developing new ways to use less water, to store more of this prized resource, to repurpose used “gray water” for non-potable uses like agriculture, and to inform inventive policy approaches to conserve fresh water.It won’t be easy, she says. California alone has over 7,000 independent water agencies that must be wrangled into a cohesive team to make it real, but recent progress has people believing once again that our parched cities can be saved. It’s all here on this episode of Stanford Engineering’s The Future of Everything podcast. Listen here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In recent years, biologists have learned that the vaginal microbiome — the make-up of the bacteria in the vagina — during pregnancy may be the best predictor of pre-term birth. It is a valuable finding that could reshape obstetrics. What is perhaps more revelatory about this emerging knowledge is that biologists have learned it from a surprising source: statistics.Stanford’s Susan Holmes is one such statistician in the rapidly evolving science of using statistics to understand biology. Holmes is now turning her attention to improving our understanding of the remarkable human immune system to help fight cancer and other deadly diseases. She says that the statistician’s greatest contribution to biology may not necessarily reside in analyzing the myriad numbers and data points available these days, but rather in divining and explaining which patterns are replicable and which are not.Join bioengineering Professor Russ Altman for the latest episode of Stanford Engineering’s The Future of Everything podcast to discuss the fascinating and fast-evolving field of statistical biology with a leading proponent of the science, Susan Holmes. Listen here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Mechanical engineer Sheri Sheppard got her start in engineering working on the Corvette for General Motors and later worked for both Ford and Chrysler.Back then, she was among a handful of women engineers in the auto industry, where she learned firsthand the risks a monolithic culture presents.Today, Sheppard is a professor at Stanford University, where she works to encourage diversity in the student body, in the classroom and in the curriculum. She says that engineering needs to reach beyond the traditional disciplines to tap into sociology, history, ethics, psychology and even philosophy to help engineers explore the “peopleness” in the challenges they are trying to solve.In that pursuit, she encourages women and minorities eager to transform their field to become what her colleague Deb Meyerson has dubbed “tempered radicals” — leaders who can rock the boat while remaining in the boat. The result, Sheppard tells Stanford Engineering’s The Future of Everything podcast, is more empathetic engineering that benefits everyone in society. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

We’re all familiar with those algorithms on our favorite e-commerce and streaming services that recommend purchases, books or movies based on what “others like you” have enjoyed. In the industry, they are known as “recommender engines.”Medical doctor Jonathan Chen is an assistant professor of medicine at Stanford and an expert in bioinformatics who wondered if the medical profession might benefit from similar artificial intelligence. He now creates recommender engines for doctors that comb real-world clinical data to help them make key decisions based on steps other doctors have taken with similar patients, empowering individuals with the collective experience of the many.Chen tells Stanford Engineering’s The Future of Everything podcast that such programs will soon be commonplace in exam rooms, helping doctors become better at what they already do and making medical practice a more consistent, universal experience for everyone. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Artificial intelligence can help us design safety-critical systems for aircraft and other vehicles that are more robust to the many sources of uncertainty in the real world, says aerospace professor Mykel Kochenderfer.Building systems that meet the exceptionally high level of safety expected of commercial air transport is challenging, but Kochenderfer says that the key is in modeling the likelihood of the full spectrum of outcomes and planning accordingly. Validating the safety of these systems is also difficult, often requiring billions of simulations. He tells Stanford Engineering’s The Future of Everything how AI, empowered by algorithms such as “dynamic programming,” can make autonomous systems safer. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

With a degree in photography with a concentration in mathematics and boasting high-profile jobs at two of the most influential visual outlets in the last century, National Geographic and Instagram, Pamela Chen knows a bit about the state of modern photography and the algorithms that shape popular tastes.Now, as the Human-Centered Artificial Intelligence and John S. Knight Journalism (HAI-JSK) Fellow at Stanford, she studies how artificial intelligence is shaping the role of photography in society: particularly the rise of memes, which she refers to as “packets of culture.” Chen says mathematics is redefining photography as much as artistic vision, altering both consumer tastes and the creative eye of photographers who want to become – or remain – relevant in a rapidly changing world.Chen joins The Future of Everything host Russ Altman to discuss why artificial intelligence’s influence on photography is only just in its infancy and why lovers of photography still have power to shape AI as much as it shapes us. [Listen here.] Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Stanford engineering alumnus Michael O’Sullivan, now at the University of Auckland, likes to say his business is the “science of decision-making,” and that expertise paid off handsomely in his native New Zealand’s successful response to COVID-19.O’Sullivan pivoted his knowledge of computer modeling, usually reserved for optimizing business processes, to help predict how quickly the disease might have spread through the island nation’s 5 million inhabitants, and to gauge various national response strategies. Based on expert models from a team of researchers that included O’Sullivan, New Zealand’s leadership took an aggressive approach and quelled the disease after just a month of lockdown.O’Sullivan tells Stanford Engineering's The Future of Everything he is now turning his attention to highly detailed geographic models to better understand how COVID-19 could spread geographically if a future outbreak occurs. He is also putting his modeling to work to help analyze how response to the disease will impact the coming flu season and how the lockdown might have had negative effects on the treatment of other illnesses such as the early detection of cancer. Michael O’Sullivan, MS ’97, PhD '01, would like to acknowledge the work of Kevin Ross, MS '01, PhD '04 (Precision Driven Health), and Pieta Brown (Orion Health), who have been instrumental in making a pipeline for the modeling work discussed in this podcast readily available to the New Zealand government. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Megan Palmer, executive director of Biopolicy and Leadership Initiatives at Stanford, joins bioengineer Russ Altman for this episode of Stanford Engineering’s The Future of Everything podcast, to discuss how we can better prepare for future virus outbreaks and how the world could ultimately become a more secure, peaceful and prosperous place as a result of the lessons learned from COVID-19. The key to that future, she says, will be better coordination and communication among world leaders in science, security and policy, who will be charged with foreseeing and preventing the next crisis. Likewise, it will take better cooperation between humankind and the natural world. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

As she tells it, the life of immunologist Catherine Blish has not changed all that much from what it was just a couple months ago.Her lab still studies deadly infectious diseases, but instead of myriad killers like HIV, dengue fever, influenza and the like, her team is now focused solely on the SARS-CoV-2 virus that causes COVID-19. Only a select group of researchers in the world are qualified to work with such serious viruses, and fewer still are properly equipped with the protective gear and sophisticated ventilation systems needed to guarantee the safety in the lab.Blish recently joined Russ Altman for this special COVID-19 edition of Stanford Engineering’s The Future of Everything podcast, to talk about the unique character of the virus, a few surprises she and others have unearthed in their research, and how once-competitive scientists around the world have united to find treatments and a vaccine that are critical to ending the pandemic for good. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Seema Yasmin is a rarity in public health: a medical doctor who is also a journalist. As such, she’s seen a lot, from Ebola in West Africa to SARS and MERS, and now COVID-19, the most serious pandemic in a century.Yasmin is currently director of research and education at the Stanford Center for Health Communication. From her years in the Epidemic Intelligence Service at the U.S. Centers for Disease Control and Prevention — a group widely described as “the disease detectives” — and as a reporter for The Dallas Morning News, Yasmin says that the greatest impediment to halting an outbreak is the rapid spread of bad information, and even abject disinformation, which when abetted by social media can spread faster than the disease itself. To halt the pandemic, she says medical science and public health experts — and the journalists who cover them — must become better storytellers to get ahead of bad information and to “pre-bunk” false claims that lead to bad decision-making. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Child psychiatrist Victor Carrion has dedicated his career to studying and helping people deal with trauma, especially kids. He says that it is understandable that everyone in the family is dealing with some degree of stress due to COVID-19, and that’s okay. The key is to recognize and acknowledge the stress and deal with it head on.In this episode of Stanford Engineering's The Future of Everything with host, bioengineer Russ Altman, Carrion explains that stress manifests differently at different ages. What works for parent may not for child. He also discusses strategies for minimizing the risk of future post-traumatic stress disorder (PTSD). Carrion counsels trying creative outlets like art and mindfulness techniques like yoga to find what works best to beat stress in these very stressful times. Listen here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

When humans roamed as hunters and gatherers, the ability to retain calories likely determined who lived and who died in times of famine.Today, that evolutionary advantage may make us prone to diabetes.Join host Russ Altman, professor of bioengineering, and guest Sanjay Basu, a foremost expert in disease prevention, for a broad-ranging discussion of what works, what doesn’t and what new approaches—including an emphasis on community gardens and healthier diets—are on the horizon as society battles this deadly disease. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Imagine being born with just half a heart. Alison Marsden does, pretty much every day. She is an associate professor of pediatrics specializing in cardiology and also of bioengineering. She works with children born with such dire defects.Fortunately for those kids, Marsden is also an expert in computational modeling of cardiovascular system and developer of SimVascular, software that helps surgeons simulate surgeries on the computer without risk to living patients. The software provides researchers and surgeons a way to propose novel surgical procedures and then simulate the resulting blood flow patterns in order to better understand the potential for a successful outcome.Join host Russ Altman and Alison Marsden for an exploration of the many ways computer simulations are making heart surgery more effective and more personal than ever before.You can listen to the Future of Everything on iTunes, Google Podcasts, SoundCloud, Spotify, Stitcher or via Stanford Engineering Magazine. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jayodita Sanghvi is director of data science at Grand Rounds, a startup that connects members to high-quality health care. Grace Tang is a data scientist at LinkedIn. Both are alumnae of Stanford bioengineering.While the connection between big data and bioengineering may not be readily apparent, Sanghvi and Tang say that the connection couldn’t be more clear or timely than right now when big data is now firmly entrenched in big business.From applications that help diagnose and guide people to relevant care to programs that suss out bad actors on social media, the challenges of harnessing big data and the consequences of incorrect or improper use are raising important questions for those charged with making big data work. The challenges range from finding correct answers in messy or missing data to the deep ethical and privacy dilemmas inherent in the breadth and quantity of information available today.Join host Russ Altman and big data experts Jayodita Sanghvi and Grace Tang for a deeper look into the challenges arising when big data meets big business.You can listen to the Future of Everything on iTunes, Google Podcasts, SoundCloud, Spotify, Stitcher or via Stanford Engineering Magazine. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Stanford materials engineer William Chueh got interested in battery design as way to battle climate change. He looked across the energy landscape and understood that a future filled with renewable solar and wind energy will require more and better batteries to even out the troughs when the sun is not shining or the wind is not blowing.Chueh says battery design has come a long way in the last 10 years. But sating the energy needs of a future filled with countless smartphones, laptops, electric cars and wearable devices will drive a profound transition in the battery industry. Today’s $50 billion battery market will blossom to a trillion dollars in the next 15 years, he predicts.Chueh says the grid of the future will be a network of diverse smaller-scale energy-storage options that guarantees a steady supply of electricity with no single point of failure — a model that takes its inspiration from the way the internet delivers information without fail. The result will be a more efficient and resilient grid for all, Chueh says. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Days after COVID-19 broke out in the United States, Russ Altman and colleagues at Stanford's Institute for Human-Centered Artificial Intelligence (HAI) scrambled to organize a full-day online conference to replace the in-person meeting they were planning for spring 2020. Their topic: using AI to defeat the deadly new virus behind COVID-19 and, in particular, analyze how countries were responding; developing new ways of tracking and anticipating its spread; reshape the search for treatments and a vaccine; and, last but not least, to battling “infodemics” — the tendency for information overload to hinder scientific progress. With thousands from around the world tuning in for the live event and 60,000-plus views of the recordings since, the conference illustrated in real terms how an entire field pivoted in a matter of weeks to address the pandemic in new and promising ways. In this episode of Stanford Engineering's The Future of Everything, guest host Howard Wolf turns the tables on Altman — a medical doctor, an expert in bioinformatics and the HAI associate director who helped lead the conference — and digs deep on AI’s response to COVID-19. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The co-director of Stanford’s Institute for Human-Centered Artificial Intelligence discusses how AI can reach its potential to enhance human capabilities and enrich human lives. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

An expert in bioinformatics describes how better information and modeling can help caregivers stay a step ahead of the new virus. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

New research explores how physical pushing and pulling between cells helps them differentiate into the myriad cell types in the body. Have you ever pondered how the cells in your hand knew to become a hand and not, say, a foot or a heart or an ear? Alex Dunn is a chemical engineer who thinks about such things a lot. He has always marveled at the way — from brain to blood to bone — the many cells that make up our bodies derive from just a single cell created when sperm meets egg. He says that process of differentiation comes down to far more than genetics or biochemistry can explain. Dunn counts himself as among an emerging field known as “mechanobiology” that is exploring how physical forces — the tugging and nudging that goes on between cells — play a very important part in how cells differentiate and self-organize into the complex systems that make up the human body. Dunn says there’s still a lot we don’t know about mechanobiology, but the process of observing and analyzing the behavior of invisible molecules inside a cell is not unlike trying to understand how a bakery works by peering in the window. For a glimpse inside the inner workings of human cells and the very latest science of cell differentiation, join chemical-engineer-turned-mechanobiologist Alex Dunn for the latest episode of The Future of Everything podcast from Sirius XM with bioengineer and host Russ Altman. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

A marine scientist travels the world to understand whether and how the ocean will respond to climate change, overfishing and other challenges. Fiorenza “Fio” Micheli grew up on the Mediterranean Sea, where she fell in love with the ocean and made it the object of her scientific career. Now a marine ecologist and co-director of Stanford’s Center for Ocean Solutions, her research spans the spectrum of marine science. She has studied the overfishing of sharks and how their absence affects coral reef ecosystems; she has explored the influence of marine protected areas on biodiversity below the waves; she has studied the impacts of the many ways in which we use the ocean — through fishing to farming to recreation — on its ecosystems, and how to more sustainably support these crucial services. And, for lessons on how undersea life might respond to climate change, she traveled to Italy, her home country, to investigate life near undersea volcanic vents that jet carbon dioxide into the seawater like a Jacuzzi. In all of Micheli’s varied research, she returns to a constant theme: The ocean is a magical place, worthy of awe and wonder, but it is in trouble. It is time to act before it is too late. In the latest episode of Stanford Engineering’s The Future of Everything podcast, Micheli takes host and bioengineer Russ Altman — and listeners — on a deep dive into ocean science and global efforts to protect this valuable resource. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

A civil engineer explains how new insights gleaned from the flight of birds may one day be applied to fields as far-ranging as autonomous cars and crowd control. Anyone who has ever observed a large flock of starlings in flight – darting and swirling as if the entire flock were one big beautiful being – cannot help but marvel and wonder at how all those birds keep from crashing into one another. Nick Ouellette is studying the in-flight behavior of birds to draw lessons he can apply to engineering. He says that birds are not alone in their tightly coordinated patterns of movement; such behaviors can be observed at every scale of nature, from bacteria to bees to beluga whales. Ouellette is doing sophisticated video measurements of flocks in flight to understand just how it is that birds can pull off their beautiful balletics without total chaos. He says the secret is that nature favors decentralized, bottom-up control of groups versus the top-down, leader-follower approach favored by humans. Ouellette, a civil engineer and birdwatcher extraordinaire, discusses his research on the latest episode of Stanford Engineering’s The Future of Everything podcast with bioengineer and host Russ Altman. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

How a revealing father-daughter conversation led to a career dedicated to studying and treating severe trauma and stress-related disorders. Shaili Jain first got interested in studying post-traumatic stress disorder (PTSD) on an East Coast road trip listening to her father describe his experiences during the 1947 Partition of British India. As she listened to details of his trauma and losses, many revealed to her only for the first time, Jain realized she had a deep personal connection to trauma survivors that had, until now, been hidden. This realization spurred a new career, committed to specializing in PTSD and advancing the science of traumatic stress. PTSD became Jain’s life’s work as a medical doctor and a researcher. She would eventually go on to pen a 2019 book, The Unspeakable Mind. Her book combines vividly recounted patient stories, cutting-edge neuroscience, interviews with some of the world ’s top trauma scientists and Jain’s professional expertise, and offers a textured portrait of a widely misunderstood condition. PTSD has historically been hidden in plain sight, she says, and it is typically tough to diagnose and often goes hand in hand with anxiety, mood and substance abuse disorders. But now, she says, researchers are making great strides at understanding trauma and treating PTSD effectively. In the latest episode of Stanford Engineering’s “The Future of Everything” podcast, Jain discusses the hopeful prognosis for traumatic stress disorders with host and bioengineer Russ Altman. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

A rapidly shifting legal debate is raging in healthcare over patient data and privacy. One legal expert says that even though regulations have lagged, a reckoning is due. How much control should patients have over who sees their medical records? How readily should researchers share patient-level data from their clinical studies? In today’s world, should the answers to these questions depend on whether the data are “anonymized?” These are but a few of the ethical and legal conundrums that Michelle Mello, Stanford professor of law and of health research and policy, grapples with on a daily basis. She says that rapidly evolving ways to gather and share medical data are exposing the limitations of laws that protect patient privacy. Meanwhile, the value of sharing patient and clinical data is growing by the day. Data from multiple studies can be pooled to study subgroups or explore rare conditions that were once out of reach. It could help lower drug prices, too, or identify ways to treat patients with greater precision and efficiency. Mello says that reaping these benefits will require a national conversation about what patients are willing to trade off in terms of privacy and control over their personal health information. Join Michelle Mello and host Russ Altman for a wide-ranging discussion of the ethical and legal challenges in healthcare on Stanford Engineering’s The Future of Everything. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

An expert in infectious diseases says that vaccinations are more powerful than ever, but better communication by the medical community is needed to combat misinformation. Stanford professor Yvonne “Bonnie” Maldonado is a medical doctor and an expert in pediatric infectious diseases. She has been fighting and preventing disease her entire career. She says that vaccinations have made remarkable progress in recent years and yet, despite well-known programs that have virtually wiped out once-dreaded diseases like measles, smallpox and polio, a more insidious foe than these diseases has appeared — misinformation that sows confusion, fear and distrust of vaccines in the general public. The result has been a worrying reappearance of some of the diseases society has worked so hard to eradicate. But the science is clear: Vaccinations save lives and carry very little to no risk for the vaccinated. Meanwhile, scientific advances are making vaccines more effective and less risky by the day. There is no magic solution, Maldonado says, but evidence suggests that a more personalized communication approach could help by avoiding stigmatizing naysayers in favor of greater understanding and cooperation with dubious audiences. In working with the public, she says, medical providers remain the first and best line of communication with both the scientific knowledge and the public trust to deliver these life-saving messages. In this episode of Stanford Engineering’s “The Future of Everything” podcast, Russ Altman and vaccination expert Bonnie Maldonado for a clear-eyed look at the future of vaccines. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

The geostationary satellites used for communication and weather forecasting today are very large and very expensive — and most are still functioning perfectly when they must be disposed of because they run out of fuel. In their place, Stanford astronautics professor Simone D’Amico imagines an new era of smaller, less expensive, more efficient satellites that work in tandem to accomplish things their bigger brethren never imagined. He calls it distributed space systems — formations or “swarms” of small satellites.Distributed space systems have breakthrough applications in earth and planetary science, astronomy, and astrophysics, as well as in-orbit servicing and space infrastructure. One task D’Amico foresees for what he calls “The Swarm” is a sort of janitorial role. These “garbage trucks in space” would remove, repair or refuel the thousands of unused satellites orbiting the earth. He says The Swarm could also improve our knowledge of the Sun and its interaction with the upper layers of the atmosphere, leading to better space weather predictions or achieve other important scientific objectives — like detecting life on other planets.Before this space age can be made real, however, D’Amico and his compatriots in astronautics must figure out how to control these distributed space systems with the required precision in safety, and help develop a new set of “galactic” rules to make space traffic sustainable in the long run.Join host Russ Altman and astronautics professor Simone D’Amico for a look at “The Swarm” — the changing face of satellites in space — on the latest episode of The Future of Everything. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Photonics engineers are working toward a day when fast, energy efficient computers do their mathematics using photons — packets of light — instead of electrons. Experts estimate that computers gobble up as much as 10% of global electricity. They predict that that share will only grow as data centers expand and the internet of things brings scads of new computer-controlled devices to the world. Jelena Vuckovic is an electrical engineer who sees a light on the horizon — quite literally. She is building computers that calculate and communicate more with photons than electrons. These “photonic” devices could cut energy consumption in half and empower exciting new technologies, like quantum computing, in the process. Before that day can come, however, Vuckovic and other proponents of photonics — the science of using light for practical purposes — will have to design smaller devices and improve manufacturing techniques to compete with today’s ultra-small electronics. To hasten that arrival, Vuckovic is turning to artificial intelligence to develop new device designs and new materials that could usher in the age of photonics. Join Russ Altman and engineer Jelena Vuckovic for a discussion of the power and promise of photonics on The Future of Everything. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Computer programs that purport to help humans learn have been around almost as long as there have been computer programs, but their track record for success has been less than impressive. Emma Brunskill, an expert on artificial intelligence and machine learning, thinks that less-than-stellar record is about to change and has dedicated her career to finding new and better ways to teach computers to teach humans. Her research creates innovative "reinforcement learning" algorithms in which computers learn through experience to get better at teaching humans. In the process, the algorithms lead people to make better, more-informed decisions that produce better outcomes in the long run. To Brunskill this is no schoolroom affair, but an endeavor where the stakes are high. She says that better education is key to big societal challenges, like alleviating poverty. She believes that better training of new workers — or retraining of older ones — can yield better paying jobs for more people. What’s more, she’s turning her attention to other fields, namely healthcare, where better decisions can have life-or-death implications. Join host Russ Altman and Stanford computer scientist Emma Brunskill for a deep exploration of the new age of computer-assisted learning and decision-making. You can listen to The Future of Everything on Sirius XM Insight Channel 121, iTunes, Google Play, SoundCloud, Spotify, Stitcher or via Stanford Engineering Magazine. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

A biomechanical engineer explains how new diagnostics and improved understanding of human movement are yielding great leaps forward in the treatment of motor dysfunction. Engineer Scott Delp first got interested in the details of human movement when he was injured in a skiing accident and spent five years trying to recover. Back then, today’s powerful diagnostic tools, like MRI, weren’t generally available, and Delp experienced many roadblocks and false starts in his recovery. Delp turned that challenging experience into a career studying and developing new approaches to motor dysfunction that he puts to use helping people with conditions like osteoarthritis and cerebral palsy to walk, run and move more easily and without pain. His multidisciplinary team includes surgeons, neurologists, roboticists, engineers and computer scientists who use sophisticated computer models to analyze movement dysfunction and to counteract them through surgery, robotics, neurostimulation and other techniques, including the use of Botox. Delp’s latest focus is on discovering approaches that inspire patients to see better movement as key to better health and view physical rehab not merely as necessary, but actually enjoyable. Join host Russ Altman and expert in the biomechanics of human movement Scott Delp for a “moving” discussion about the joys and the benefits of motion here on The Future of Everything radio show from Sirius XM. You can listen to The Future of Everything on Sirius XM Insight Channel 121, iTunes, Google Play, SoundCloud, Spotify, Stitcher or via Stanford Engineering Magazine. Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Russ Altman: Today on The Future of Everything, the future of detecting DNA in your blood.Now DNA is the building block of life. It is a relatively simple long molecule or polymer made out of four components or DNA bases which have one letter abbreviations, the famous ATCG, which stand for their chemical names. It’s like a string of beans, beads, beads, but it is long. A human genome is made of about three billion DNA bases, divided into 23 chromosomes. So if you add up the beads in each chromosome, you get about three billion. You get a genome from mom and you get one from dad. So you have two copies of the genome, mostly the same but obviously not identical, or six billion total.Now DNA contains the blueprints for how your cells live, how they grow, how they interact with other cells, and like a computer program, it allows the cell to perform simple computations to make decisions about when and where things happen.If this goes wrong, you can get cancer. Mutations in the DNA cause the computations and decisions to go wrong.Other things can happen too. In the last ten years, researchers have learned that they can detect DNA in the blood. Now we knew that the cells in the blood had DNA, so that was not surprising, but what was surprising is that there is sometimes DNA from other cells in the body, often cells that have died and just released their DNA into the bloodstream. This is sometimes called cell-free DNA because it is floating in the blood and it’s not really part of a cell. Although this may seem like it’s junk, it offers evidence of lots of other processes going on in the body, processes diverse as cancer, pregnancy, stress on organs, or even death and many others.Dr. Stephen Quake is a professor of Bioengineering, Applied Physics and Physics and Stanford University. Steve pioneered the detection of DNA in the blood and some its first applications.Steve, what drove your interest in detecting DNA, and what was the first demonstration that this would actually be useful?Stephen Quake: Well, my interest came actually when I became a father. My wife and I were in to see the doctor, and the doctor says you guys should think about getting amniocentesis. And it was seemed like a theoretical question and something we have time to think about. We said yeah, okay, that sounds like the right thing if recommending it.Russ Altman: And this is a super risky procedure in many ways. A needle goes into the uterus near the baby to extract fluids.Stephen Quake: Big needle right in the mom’s belly, right next to the fetus to try to grab a few cells, and so to do genetic testing. And we said yeah, it sounds like a good idea, thinking we schedule another appointment for it. Next thing we knew, the guy was turning around with a giant needle, plunges it right into my wife’s belly,Russ Altman: Whoa.Stephen Quake: Yeah, whoa, exactly. That was our response. And it’s the response of many people who undergo that certain invasive testing. And not surprisingly, there’s risk associated with doing that testing. Sometimes, you lose the baby and other health problems that might happen.Russ Altman: How far into the pregnancy were you?Stephen Quake: That’s typically done, I don’t know, around 14 weeks, something like that, 15 weeks, somewhere around there. And so that sensitized me to holy cow, there’s a problem here that you’re asking a diagnostic question, and there’s a lot of risk associated with it. And so I began to think are there ways to ask these genetic questions and do diagnostics without adding risk? And I eventually stumbled upon this old scientific literature about this cell-free DNA that you were mentioning, which, as it turns out, was first discovered as a phenomenon in 1948.Russ Altman: That’s before Watson and Crick even articulated the importance of DNA for genetics.Stephen Quake: It’s before the structure, and it’s before people knew. It’s roughly contemporary people first realized that DNA was the molecule of inheritance.Russ Altman: Right.Stephen Quake: Oswald Avery just that same year was working that out. So it was blood chemistry to those guys who did it. But the field stayed alive, and it was mostly people doing cancer research. And eventually, it was figured out that when you’re pregnant, some of the DNA in your blood comes from the fetus, and that was worked out in the late 1970s. And –Russ Altman: And so this is not a large amount, I’m guessing.Stephen Quake: It’s not much, just a few percent of what’s there, so it’s a very challenging measurement problem and the decade-long search to try to figure out how to really use that to build a diagnostic that would allow you to understand the genetics of the baby without having to risk the baby’s life. And we saw that at Stanford, and it was through the work of a really terrific graduate student in my lab when the bioengineering department was young, Christina Fan. And that has now been the first real clinical application of cell-free DNA in diagnostics, and that’s