59 集

We’ve entered a new era. The creation and collection of information play an ever-increasing — yet often hidden — role in our lives. Algorithms filter all sorts of experiences, from the mundane to the monumental. The fuel that powers and curates these experiences is…data. Data are the new oil; whoever controls data has power. Is this making things better? Worse? Raw Data is a show about how information becomes power. What are the implications for all of us, now that mountains of data are more accessible and malleable than ever?

Episodes post on Thursdays. From Stanford and PRX.

Hosted by Andrea Mustain and Mike Osborne.

We love hearing from you! Please email us at hello@rawdatapodcast.com

Raw Data Stanford and PRX

    • 科技

We’ve entered a new era. The creation and collection of information play an ever-increasing — yet often hidden — role in our lives. Algorithms filter all sorts of experiences, from the mundane to the monumental. The fuel that powers and curates these experiences is…data. Data are the new oil; whoever controls data has power. Is this making things better? Worse? Raw Data is a show about how information becomes power. What are the implications for all of us, now that mountains of data are more accessible and malleable than ever?

Episodes post on Thursdays. From Stanford and PRX.

Hosted by Andrea Mustain and Mike Osborne.

We love hearing from you! Please email us at hello@rawdatapodcast.com

    Technically Sweet

    Technically Sweet

    Chocolate is beloved by...well, most humans, it would seem. But this sweet treat that, for many of us, brings instant happiness, has a nasty secret: most of the world’s cocoa comes from a place where child labor, and sometimes even enslavement, is rampant. For decades, the giant companies that dominate the chocolate industry have said that it was impossible to know if their cocoa was tainted by labor abuses — the supply chain is too long, how can you possibly track cocoa beans back to a small farm in West Africa? Enter technology. But, it turns out, technology may not truly offer the answer to the intractable problem of child labor. The solution may, in fact, be lurking in plain sight. We talk to Nathan Hodge, of Raaka Chocolate; Charity Ryerson, of Corporate Accountability Lab; and Frans Pannekoek, of Tony’s Chocolonely. 



    Find out more at rawdatapodcast.com

    • 27 分鐘
    Training Computers to See

    Training Computers to See

    Over the past few decades, computer vision has held the promise of making the world a better place, from aiding the blind to helping doctors better analyze medical imagery. But as it turns out, teaching computers to see has some unintended consequences. Joseph Redmon, a researcher at the University of Washington and computer vision researcher, tells the story of the history of this quickly evolving technology, as well as his own experience seeing a something he built be put to uses he’d never envisioned — applications that might, quite literally, be used to kill. 



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    • 17 分鐘
    The Worst Cyber Attack (For now)

    The Worst Cyber Attack (For now)

    In June 2017, something weird — and very alarming — started happening at a company in Copenhagen. It seemed that hackers had shut down the company’s network, and were demanding a ransom. But it turned out this was no ordinary cyberattack. What unfolded was the most devastating cyberattack in history — one that brought operations to a screeching halt in companies across the world, and cost billions of dollars. Andy Greenberg, writer at Wired Magazine and author of the book Sandworm, tells the behind-the-scenes story of the attack, dubbed NotPetya — which, in its aftermath, was revealed to be not a sophisticated tool to steal money, but instead, a weapon designed to destroy a nation.  



    Find out more at rawdatapodcast.com

    • 19 分鐘
    How We Found Ourselves

    How We Found Ourselves

    Get out your smartphone, and you can almost instantaneously know where you are — and find out how to get where you want to go. Which, when you think back on the history of human navigation is...pretty astounding. How did we come to hold such immense power in our hands? It’s all thanks to GPS, a technology born from the Cold War and the Space Race, and delivered into our personal pocket computers thanks to a series of dramatic, sometimes tragic events, and at least one war. Our guide is Paul Ceruzzi, a former curator at the Smithsonian and author of the book GPS. And Jordan Frith, a professor at Clemson University, talks about it means now that, for better or worse, we never have to get lost ever again.

    • 24 分鐘
    About Us, But Not For Us (Repost)

    About Us, But Not For Us (Repost)

    Originally broadcast in April 2019. As we approach the end of 2019, the Financial Times recognizes Shoshana Zuboff's "The Age of Surveillance Capitalism" as one of the best business books of the year.

    Shoshana Zuboff doesn’t mince words when it comes to the data economy. According to Zuboff, author of the recent book *The Age of Surveillance Capitalism, *our very souls are at stake. But the seeds of surveillance capitalism were planted rather innocently, back in the heady days of the dotcom bubble. As Zuboff tells it, it all began with Google. When the young company entered crisis mode, they needed to find new ways to make money. And a whole new economic logic was born — one that has now spread across every sector of the economy, and has invaded every facet of our online lives. Zuboff warns that surveillance capitalism threatens much more than just our privacy.



    Find out more at rawdatapodcast.com

    • 29 分鐘
    Prediction (BYTE)

    Prediction (BYTE)

    When humans predict something, it’s basically an educated guess, based on our experiences. When a machine makes a prediction, it uses data and math. And we are increasingly relying on machine prediction to help make decisions in everything from banking to insurance to education. But Meredith Broussard, a professor from New York University, argues that this has all gone too far, especially when you look at what data are being used in machine predictions. And that the “futures” that machines predict should be taken with large grains of salt.



    Find out more at rawdatapodcast.com

    • 10 分鐘

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