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Whether by injury or disease, paralysis has afflicted humans through the ages.
Only now have science and technology converged to a point where scientists can contemplate a day when computers and the human mind can communicate directly to restore a certain degree of independence to people with debilitating spinal injuries and other physical conditions that impede or prevent movement.
Electrical engineer Krishna Shenoy is an expert in such brain-computer interfaces and has built machinery by which humans can control the movement of computer cursors with mere thoughts. Using small chips implanted in the brain itself, Shenoy “listens intelligently” to the electrical “chatter” among a hundred or so of the 100 billion neurons of the brain’s motor cortex and then translates the meaning into language a computer can understand. In this way, Shenoy has allowed a man with paralysis to “write” his thoughts at some 17 words per minute, a record more than double the previous standard.
Work remains, but the future of brain-computer interfaces is on the horizon as Krishna Shenoy tells us on this episode of Stanford Engineering’s The Future of Everything podcast with host Russ Altman. Listen and subscribe here.
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Sam Wineburg, a research psychologist at Stanford’s Graduate School of Education, recently conducted a nationwide study of the fact-checking skills of thousands of American high school students.
He didn’t go about it with a survey asking the kids to self-report their own behaviors. Instead, he devised a live experiment that charged the 3,000 students in the study to determine the veracity of a now-famous bit of fake news from the 2016 election. Wineburg and team were then able to follow along as students tried to find the true source of the video, which had been produced in Russia as part of a disinformation campaign.
In the end, just three students – one-tenth of one percent – arrived at the right answer. Rather than blame the kids, however, Wineburg says fault lies with the tools they are using, which have changed so dramatically in speed and scope that their fact-checking skills have had trouble keeping up.
All is not lost, he promises, but fixing the problem will require changing not just what information students consume, but the way they think about it, as Wineburg tells host Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here.
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Many have now become familiar with the term herd immunity, an idea few outside the infectious disease community knew just a few short months ago.
It’s an elusive concept to comprehend, and harder still to achieve, but Stanford epidemiologist Dr. Julie Parsonnet says it’s important to understand just what herd immunity does – and doesn’t – mean for today’s pandemic.
Broadly speaking, herd immunity is reached when enough people have either recovered from or have been fully vaccinated against an infectious disease and there are no longer enough susceptible people in the entire population (the herd) to sustain transmission. Herd immunity doesn’t mean there won’t be cases, only that when they crop up, they will then die out. Parsonnet says this term is meant for epidemiologists to model what things will and won’t work; herd immunity is never really a public health goal in and of itself. Parsonnet also says that, in models, there are many obstacles to attaining herd immunity, including vaccine hesitancy, especially in people most likely to transmit the infection (young adults); imperfect effectiveness of the vaccine; movement of people; carriage of the virus in non-human hosts; and the continuous appearance of variants.
Importantly, Parsonnet says, herd immunity is unlikely to be permanent. Society must remain vigilant, continuously limiting the number of susceptible people to keep the herd safe. She therefore counsels deemphasizing the concept and instead bringing the diversity of communities into the conversation to achieve high levels of protection in the U.S. and globally. She says every vaccine given is a step in the direction of “normal.”
In this episode of Stanford Engineering’s The Future of Everything podcast, host Russ Altman and Parsonnet also talk about her other research showing that average human body temperature is on the decline worldwide. Listen and subscribe here.
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Imagine typing words into a text editor and watching on a nearby television as a well-known celebrity speaks those words within seconds.
Computer graphics expert Maneesh Agrawala has imagined it and has created a video editing software that can do it, too. Given enough raw video, Agrawala’s application can produce polished, photorealistic video of any person saying virtually anything he types in.
While he acknowledges concerns about manufactured “deep fakes” of political leaders or others speaking words they never said, Agrawala chooses to focus on the profound upside. He envisions the television and film industries using his technology to forgo costly reshoots, for instance, or medical professionals helping people with damaged vocal cords regain their natural voices.
In the end, while ethical and legal frameworks are being developed to address deep fakes with all due seriousness they deserve, Agrawala says the benefits of the technology, and his passion for it, gets at the most basic of all human endeavors — better communication. Agrawala tells host Russ Altman all about it in this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here.
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Biology is not typically considered a mathematically intensive science, says Noah Rosenberg, an expert in genetics, but all that is about to change.
Math, statistics, data and computer science have coalesced into a growing interest in applying quantitative skills to this traditionally qualitative field.
The result will be better and more accurate models of life, ranging from genetic inheritance to the entirety of human society. The yield will be a greater understanding and, quite possibly, revolutionary interventions into disease, ecology, demography, and even evolution itself. The tools of mathematical biology have never been more apparent, Rosenberg says, as mathematical models of the spread of infectious disease have been central around the world in the response to the COVID-19 pandemic.
With applications in health care, forensic genetics, and human evolution, the tools of mathematical biology are proving more relevant and more needed than ever, as Noah Rosenberg tells Stanford Engineering’s The Future of Everything podcast, with host bioengineer Russ Altman.
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Slowly but surely, the highly centralized, industrial electric grid that supplies power to the vast majority of American homes and business is changing.
Our existing system of massive power plants and huge networks of high-voltage wires is giving way to a much leaner, decentralized system of small-scale power generation on a more personal, neighborhood- or residence-level scale.
In other words, we’re going from an “infrastructure-centric” model to a “human-centric” one, says grid expert Ram Rajagopal. He says that the new grid will be much smarter, more inclusive and better able to adapt to the individual needs of users, helping them to schedule power-intensive tasks, like laundry or charging of electrical vehicles, to off-peak times of the day.
Before that day can come, however, Rajagopal says we’ll need new sorts of sensors and algorithms that will provide much more data about who, how and when people are using power, as he tells listeners to Stanford Engineering’s The Future of Everything podcast with host bioengineer Russ Altman. Listen and subscribe here.
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The world’s once linear — take it, treat it, use it, dispose it — model of freshwater usage is changing fast.
Despite two-thirds of Earth being covered in water, just 2.5% of it is fit for human consumption. And that share is dwindling by the day, says civil and environmental engineer and expert in water treatment and distribution systems Meagan Mauter. With a rapidly increasing population and climate change disrupting traditional weather and distribution patterns, access to freshwater is headed for, if not already amid, a worldwide crisis.
Avoiding calamity will require industrial scale desalination and other technologies that can separate precious freshwater from other less desirable substances in the water, but also a shift to a more circular model where every drop of water is treasured and reused.
Doing that, Mauter says, will demand doing away with not only inefficient practices but also the very notion of “waste” water, as she tells us in this episode of Stanford Engineering’s The Future of Everything podcast with host bioengineer Russ Altman. Listen and subscribe here.
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Humankind has long harnessed the wind to its advantage. From ancient mariners to millers grinding grist, the wind has been an ally for millennia, but only now do engineers have at their disposal advanced computer simulations to better understand the details of wind flow and to optimize designs.
Catherine Gorle is one such engineer who has made it her career to design better built environments able to improve walkability, temper extreme winds, shuffle air pollution far away and dissipate heat islands arising from so much sun-beaten concrete in our cities.
Once, that work had to take place in wind tunnels, but now transpires through advanced computer simulations that both speed her work and add critical detail to her understanding of the close interrelationship between wind and human society. Join us as Catherine Gorle tells host bioengineer Russ Altman all about the future of wind on this episode Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here.
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As the world moves to more efficient and cleaner energy solutions, there is a growing divide between the clean-energy haves and have-nots, says Anthony Kinslow II, PhD, a lecturer in civil and environmental engineering. Too often the divide falls along racial and socio-economic lines, as minority and low-income communities do not benefit from clean energy to the degree that whiter and wealthier communities do.
The problem is founded in history and in the federal government’s askew system of financing and incentivizing clean and renewable energy systems. The money flows to certain communities and not to others, Dr. Kinslow says.
Fixing the problem won’t be easy, but solutions might begin with energy audits of minority and low-income homes and communities to better understand where the gaps are and how wide they have become, as well as greater diversity in federal appointments to energy and finance positions in government. With audits will come opportunities for low-interest loans and other financing to transition to greater efficiency, as Dr. Kinslow tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here.
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Electrical engineer Kunle Olukotun has built a career out of building computer chips for the world. These days his attention is focused on new-age chips that will broaden the reach of artificial intelligence to new uses and new audiences—making AI more democratic.
The future will be dominated by AI, he says, and one key to that change rests in the hardware that makes it all possible—faster, smaller, more powerful computer chips. He imagines a world filled with highly efficient, specialized chips built for specific purposes, versus the relatively inefficient but broadly applicable chips of today.
Making that vision a reality will require hardware that focuses less on computation and more on streamlining the movement of data back and forth, a function that now claims 90% of computing power, as Olukotun tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here.
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