Stanford Radio

As deaths from COVID-19 surge to the half million mark, health law expert and Stanford Professor Michelle Mello joins Pam and Joe to discuss the many challenges facing the new Biden administration in getting control of the pandemic in the U.S.

Originally aired on SiriusXM on January 30, 2021.

The Future of Everything with Russ Altman

Episode 135 | Mark Schnitzer: How to better understand the brain

Midway through the 12-year, $5 billion nationwide “Brain Initiative,” a brain scientist explains how technology is producing profound insights into how the brain works—or doesn’t.

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.

The Future of Everything with Russ Altman:

E135 | Mutale Nkonde: How to get more truth from social media

A sociologist and former journalist warns that the artificial intelligence behind much of today’s social media is inherently biased, but it’s not too late to do something about it.

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.

After the siege of the Capitol building on January 6, Americans have been left stunned by the breach of security and concerned about new threats from hate groups and the angry mob. National security law expert Shirin Sinnar joins Pam and Joe to discuss critical legal questions about homegrown terrorism—and those accountable for the insurrection.

Originally aired on SiriusXM on January 16, 2021.

President Trump lost the November, 2020 election but has refused to concede, instead stoking the flames of anger in his supporters by spreading false claims of a stolen election. In this episode, voting law expert Nate Persily joins Pam and Joe to discuss the 2020 election—and why it is considered by experts and government officials alike to have been fair and free of fraud.

Originally aired on SiriusXM on January 16, 2021.

The Future of Everything with Russ Altman:

E134 | Karen Liu: How robots perceive the physical world

A specialist in computer animation expounds upon her rapidly evolving specialty, known as physics-based simulation, and how it is helping robots become more physically aware of the world around them.

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.

The Future of Everything with Russ Altman:

E133 | Jef Caers: How better mineral exploration makes better batteries

A geoscientist explains why the use of artificial intelligence in the exploration of rare metals could be the key to America’s environmental and energy future.

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.

The Future of Everything with Russ Altman:

Evan Reed: How to discover a magic material

Want to build a better battery, a stronger airplane, or a faster computer? A materials science expert says your success starts in the atomic structure of the materials you choose.

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.

How can students, parents, and teachers use peacemaking, a framework used by indigenous communities, to resolve conflicts at school and home?

Originally aired on SiriusXM on December 5, 2020.

Tristan Harris, President, Center for Humane Technology and Stanford alum on developing a framework for how technology can ethically realign social media to reverse its negative impacts on humanity.

Ethical challenges and opportunities for creating a radically reimagined 21st century digital infrastructure.

Originally aired on SiriusXM on November 28, 2020.