Stanford Radio

Modern day fashion says a lot about who we are and the image we project. Join Stanford Law Professor Richard Thompson Ford for this episode for a discussion about his new book, Dress Codes, and the history of fashion and its social and political implications.

Originally aired on SiriusXM on March 13, 2021.

The Future of Everything with Russ Altman:

E141 | Julie Owono: How local voices will shape the global internet

An expert in international law and digital content explains why she thinks the future of the worldwide internet is very much in local hands.

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.

The Future of Everything with Russ Altman:

E141 | Dan Jurafsky: How AI is changing our understanding of language

A linguist and computer scientist explores how AI is expanding from capturing individual words and sentences to modeling the social nature of language.

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.

Stanford alum Carlos Watson, entrepreneur, Emmy-winning journalist and TV host, and co-founder and CEO of Ozy, a media company that's ahead of its time.

Carlos Watson has an insatiable appetite for learning and talks about life growing up, entrepreneurial success and building a media brand focused on the new and the next.

Originally aired on SiriusXM on March 6, 2021.

Sociologist Matt Snipp talks about how he teaches about race and racism in America, providing tips for other educators.

Originally aired on SiriusXM on February 27, 2021.

Why are some schools open for in-person learning while others aren’t? Stanford Law Professor Bill Koski talks about the challenges to re-opening schools, from legal issues to infrastructure problems, and who (or what) is to blame for those that remain shuttered to students.

Originally aired on SiriusXM on February 27, 2021.

The Future of Everything with Russ Altman:

E139 | Riitta Katila: How diversity drives innovation

An expert in entrepreneurship argues that greater diversity is the key to corporate creativity.

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.

The Future of Everything with Russ Altman:

E138 | David Miller: How light could transform computing

An expert in photonics explains the remarkable potential of using light instead of electricity in computation.

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.

The Future of Everything with Russ Altman:

E137 | Jin Hyung Lee: How can we systematically cure brain diseases?

Lee uses artificial intelligence to determine what healthy and diseased brain circuits look like in order to better diagnose Alzheimer’s, Parkinson’s and other brain disorders.

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.

Christopher Thomas, a former advisor to the World Bank, makes the case for international cooperation in education.

Originally aired on SiriusXM on January 30, 2021.