Fixing the Future

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5G Cellular Spectrum Auction—Can’t Tell the Players Without a Scorecard Dec 08, 2020

Show notes

The Federal Communications Commission's very first cellular spectrum allocation was a messy affair. The U.S. was divided up into 120 cellular markets, with two licenses each, and in some cases, hundreds of bidders. By 1984, the FCC had switched over to a lottery system. Unsurprisingly, people gamed the system. The barriers to enter the lottery were low, and many of the 37,000 applications—yes, 37,000 applications—simply wanted to flip the spectrum for a profit if they won.

The FCC would soon move to an auction system. Overnight, the barrier to entry went from very low to very high. One observer noted that these auctions were not “for the weak of heart or those with shallow pockets.”

Cellular adoption grew at a pace no one could anticipate. In 1990 there were 12 million mobile subscriptions worldwide and no data services. Twenty-five years later, there were more than 7 billion subscriber accounts sending and receiving about 50 exabytes per day and accounting for something like four percent of global GDP.

Historically, cellular has occupied a chunk of the radio spectrum that had television transmissions on the one side and satellite use on the other. It should come as no surprise that to meet all that demand, our cellular systems have been muscling out their neighbors for some time.

The FCC is on the verge of yet another auction, to start on December 8. Some observers think this will be the last great auction, for at least a while. It’s for the lower portion of what’s called the C-band, which stretches from 3.7–4.2 gigahertz.

To sort out the who, what, when, why, and a bit of the how of this auction our guest today is Mark Gibson, Senior Director for Business Development and Spectrum Policy at CommScope, a North-Carolina-based manufacturer of cellular and other telecommunications equipment.

Polling Is Too Hard—for Humans Dec 01, 2020

Show notes

In 1936, after polling its readers, the Literary Digest famously predicted a landslide victory for Alf Landon. On 2 November 1948, based on widespread polling that all pointed in one direction, the Chicago Tribune famously headlined its early edition, “Dewey Defeats Truman.”

Polls have been making mistakes ever since, and it’s always, fundamentally, the same mistake. They’re based on a representative sample of the electorate that isn’t sufficiently representative.

After the election of 2016, in which the polling was not only wrong but itself might have inspired decisions that affected the outcome—where the Clinton campaign shepherded its resources; whether James Comey would hold a press conference—pollsters looked inward, re-weighted various variables, assured us that the errors of 2016 had been identified and addressed, and then proceeded to systematically mis-predict the 2020 presidential election much as they had four years earlier.

After a century of often-wrong results, it would be reasonable to conclude that polling is just too difficult for humans to get right.

But what about software? Amazon, Netflix, and Google do a remarkable job of predicting consumer sentiment, preferences, and behavior. Could artificial intelligence predict voter sentiment, preferences, and behavior?

Well, it’s not as if they haven’t tried. And results in 2020 were mixed. One system predicted Biden’s lead in the popular vote to be large, but his electoral college margin small—not quite the actual outcome. Another system was even further from the mark, giving Biden wins in Florida, Texas, and Ohio—adding up to a wildly off-base electoral college margin.

One system, though, did remarkably well. As a headline in Fortune magazine put it the morning of election day, “The polls are wrong. The U.S. presidential race is a near dead heat, this AI ‘sentiment analysis’ tool says.” The AI tool predicted the popular vote almost perfectly.

That AI company is called Expert.ai, and its Chief Technology Officer, Marco Varone, is our guest today.

Can Detroit Catch Tesla? Nov 24, 2020

Show notes

If any cars are mobile phones with wheels, it’s electric cars. And just as the switch from landline phones to mobile phones was quick, and from computers to smartphones was even quicker, the shift from engines to motors, from internal combustion cars to electric cars, is starting to gain momentum and when it reaches scale, it will happen quickly.

How quickly? Pandemic aside, Tesla would be on track to sell half a million cars in 2020, all of them electric. By contrast, GM sold almost 3 million cars last year, almost none of them electric. But by 2025 or so, GM plans to sell a million electric cars, a year that the company plans to be its tipping point toward electrics.

Of course, to do that, you need amazing batteries, and an amazing capacity to produce batteries—both of which are at the heart of the company’s plans. A new GM battery factory, in partnership with LG Chem, will dwarf Tesla’s Gigafactory and power, pun intended, its drive, pun again intended, to that 2025 goal of a million electric cars.

Telemedicine Comes to the Operating Room Nov 10, 2020

Show notes

A modern hospital operating room often has someone you never see on television: a medical device company representative. The device might be a special saw or probe or other tool for the surgeon to use. It might be an artificial hip or knee—or a mandible or a pacemaker.

The surgeon may be using the device and its toolkit for the first time. The medical device company representative often knows more about the device and its insertion than anyone on the surgical team.

Even in non-Covid times, it’s a plus to have as few people in the OR as possible. And it’s inefficient to fly these company reps around the country to advise an operation that might only take an hour.

And so, in a handful of ORs, you’ll see something else—one or more cameras, mounted strategically, and a flat-panel screen on a console, connected to a remote console. The medical device rep—or a consulting surgeon—can be a thousand kilometers away, controlling the cameras, looking at an MRI scan, and making notations on their tablet that can be seen on the one in the operating room.

It’s telemedicine for the OR, and it’s the brainchild of our guest today.

The Battle for Videogame Culture Isn’t Playstation vs Xbox Nov 05, 2020

Show notes

November is a big month for the millions of people who devote their time and money to computer games. Within a two-day period Sony will be releasing its fifth-generation Playstation, and its main competitor, Microsoft’s newest Xbox, comes out as well. So it’s a good month to look at the culture of gaming and how it reflects the broader culture; how it reinforces it; and how it could potentially be a force for freeing us from some of the worse angels of our nature—or for trapping us further into them. Is there anyone better to ask than Megan Condis? She a professor at Texas Tech University and is the author of the 2018 book, Gaming Masculinity: Trolls, Fake Geeks, and the Gendered Battle for Online Culture.

5G, Robotics, AVs, and the Eternal Problem of Latency Nov 03, 2020

Show notes

Engineers will tell you that for an orchestra to rehearse remotely, it would need at least 500 megabits per second to avoid throwing off the synchronicity of a concert performance. But that’s using high bandwidth as a proxy for latency. Why not work on reducing latency directly? Because it’s hard. Nonetheless, at the cutting edge of network engineering, researchers are working on it. And not for orchestras. Autonomous vehicles, factory robots, virtual reality, piloting drones, robotic surgery, and even advanced prosthetics all require latency to get down toward one millisecond. So says our guest today, Shivendra Panwar, author of an article in November’s IEEE Spectrum magazine, “Breaking the Latency Barrier.”

Are Electronic Media Any Good at Getting Out the Vote? Oct 29, 2020

Show notes

In Get Out the Vote, co-authors Donald Green and Alan Gerber argue that political consultants and campaign managers have underappreciated boots-on-the-ground canvassing in person and on the phone, in favor of less personal, more easily-scaled methods—radio and TV advertising, robocalling, mass mailings, and the like. Unlike campaign professionals, they base their case with real data, based on experimental research. Donald Green is a political scientist at Columbia University focusing on such issues as voting behavior and partisanship, and most importantly, methodologies for studying politics and elections.

Going Carbon-Negative—Starting with Vodka Oct 20, 2020

Show notes

In 2014, two Google engineers, writing in the pages of IEEE Spectrum, noted that “if all power plants and industrial facilities switch over to zero-carbon energy sources right now, we’ll still be left with a ruinous amount of CO2 in the atmosphere.”

One alternative is to stuff carbon dioxide underground. People have been talking about this for well over a decade. But just look at Exxon-Mobil’s website and see how much progress hasn’t been made. In 2015, a bunch of mostly Canadian energy producers decided on a different route. They funded what came to be called the Carbon XPRIZE to turn “CO2 molecules into products with higher added value.”

One of the more unlikely finalists emerged from the hipsterish Bushwick neighborhood of Brooklyn, N.Y. Their solution to climate change: vodka. The startup, the Air Company, takes liquified CO2 and distills it into ethanol, and then fine-tunes it into vodka. The resulting product is not only carbon-neutral but carbon negative.

The Problem of Filter Bubbles Hasn’t Gone Away Oct 15, 2020

Show notes

In 2011, the former executive director of MoveOn gave a widely-viewed TED talk, “Beware Online Filter Bubbles“ that became a 2012 book and a startup. In all the talk of fake news these days, many of us have forgotten the unseen power of filter bubbles in determining the ways in which we think about politics, culture, and society. That startup tried to get people to read news they might otherwise not see by repackaging them with new headlines.

A recent app, called Ground News, has a different approach. It lets you look up a topic and see how it’s covered by media outlets with identifiably left-leaning or right-leaning slants. You can read the coverage itself, right–left–moderate or internationally; look at its distribution; or track a story’s coverage over time. Most fundamentally, it’s a way of seeing stories that you wouldn’t ordinarily come across.

Our guest today is Sukh Singh, the chief technology officer of Ground News and one of its co-founders.

Fake News Is a Huge Problem, Unless It’s Not Oct 13, 2020

Show notes

Despite what you think, fake news is a tiny fraction of our news diet, according to Jennifer Allen, a Ph.D. student at the MIT Sloan School of Management and the MIT Initiative on the Digital Economy, and lead author of the research study, “Evaluating the Fake News Problem at the Scale of the Information Ecosystem."

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