This episode was first released on May 2, 2023.

We’re excited to announce that we’re working on a new season of How to Fix the Internet, coming in the next few months! But today we want to lift up an earlier episode that has particular significance right now. In 2023, we spoke with our friend Alvaro Bedoya, who was appointed as a Commissioner for the Federal Trade Commission in 2022. In our conversation, we talked about his work there, about why we need to be wary of workplace surveillance, and why it’s so important for everyone that we strengthen our privacy laws. We even talked about Dr. Seuss!

Last week the Trump administration attempted to terminate Alvaro, along with another FTC commissioner, even though Alvaro's appointment doesn't expire until 2029. The law is clear: The president does not have the power to fire FTC commissioners at will. The FTC’s focus on protecting privacy has been particularly important over the last five years; with Alvaro's firing, the Trump Administration has stepped far away from that needed focus to protect all of us as users of digital technologies.

We hope you’ll take some time to listen to this May 2023 conversation with Alvaro about the better digital world he’s been trying to build through his work at the FTC and his previous work as the founding director of the Center on Privacy & Technology at Georgetown University Law Center.

Dr. Seuss wrote a story about a Hawtch-Hawtcher Bee-Watcher whose job it is to watch his town’s one lazy bee, because “a bee that is watched will work harder, you see.” But that doesn’t seem to work, so another Hawtch-Hawtcher is assigned to watch the first, and then another to watch the second... until the whole town is watching each other watch a bee.

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You can also find this episode on the Internet Archive and on YouTube.

To Federal Trade Commissioner Alvaro Bedoya, the story—which long predates the internet—is a great metaphor for why we must be wary of workplace surveillance, and why we need to strengthen our privacy laws. Bedoya has made a career of studying privacy, trust, and competition, and wishes for a world in which we can do, see, and read what we want, living our lives without being held back by our identity, income, faith, or any other attribute. In that world, all our interactions with technology —from social media to job or mortgage applications—are on a level playing field. 

Bedoya speaks with EFF’s Cindy Cohn and Jason Kelley about how fixing the internet should allow all people to live their lives with dignity, pride, and purpose.

In this episode, you’ll learn about: 

• The nuances of work that “bossware,” employee surveillance technology, can’t catch. 
• Why the Health Insurance Portability Accountability Act (HIPAA) isn’t the privacy panacea you might think it is. 
• Making sure that one-size-fits-all privacy rules don’t backfire against new entrants and small competitors. 
• How antitrust fundamentally is about small competitors and working people, like laborers and farmers, deserving fairness in our economy. 

Alvaro Bedoya was nominated by President Joe Biden, confirmed by the U.S. Senate, and sworn in May 16, 2022 as a Commissioner of the Federal Trade Commission; his term expires in 2029. Bedoya was the founding director of the Center on Privacy & Technology at Georgetown University Law Center, where he was also a visiting professor of law. He has been influential in research and policy at the intersection of privacy and civil rights, and co-authored a 2016 report on the use of facial recognition by law enforcement and the risks that it poses. He previously served as the first Chief Counsel to the Senate Judiciary Subcommittee on Privacy, Technology and the Law after its founding in 2011, and as Chief Counsel to former U.S. Sen. Al Franken (D-MN); earlier, he was an associate at the law firm WilmerHale. A naturalized immigrant born in Peru and raised in upstate New York, Bedoya previously co-founded the Esperanza Education Fund, a college scholarship for immigrant students in the District of Columbia, Maryland, and Virginia. He also served on the Board of Directors of the Hispanic Bar Association of the District of Columbia. He graduated summa cum laude from Harvard College and holds a J.D. from Yale Law School, where he served on the Yale Law Journal and received the Paul & Daisy Soros Fellowship for New Americans.

Transcript

ALVARO BEDOYA
One of my favorite Dr. Seuss stories is about this town called Hawtch Hawtch. So, in the town of Hawtch Hawtch, there's a town bee and you know, they presumably make honey, but the Hawtch Hawtcher one day realize that the bee that is watched will work harder you see? And so they hire a Hawtch Hawtcher to be on bee watching watch, but then you know, the bee isn't really doing much more than it normally is doing. And so they think, oh, well, the Hawtch Hawtcher is not watching hard enough. And so they hire another hot hocher to be on bee watcher watcher watch, I think is what Dr. Seuss calls it. And so there's this wonderful drawing of 12 Hawtch Hawtchers, you know, each one and either watching, watching watch, or actually, you know, the first one's watching the bee and, and the whole thing is just completely absurd.

CINDY COHN
That’s FTC Commissioner Alvaro Bedoya describing his favorite Dr. Seuss story – which he says works perfectly as a metaphor for why we need to be wary of workplace surveillance, and strengthen our privacy laws.

I’m Cindy Cohn, the executive director of the Electronic Frontier Foundation.

JASON KELLEY
And I’m Jason Kelley. EFF’s Associate Director of Digital Strategy. This is our podcast, How to Fix the Internet.

Our guest today is Alvaro Bedoya. He’s served as a commissioner for the Federal Trade Commission since May of 2022, and before that he was the founding director of the Center on Privacy & Technology at Georgetown University Law Center, where he was also a visiting professor of law. So he thinks a lot about many of the issues we’re also passionate about at EFF – trust, privacy, competition, for example – and about how these issues are all deeply intertwined

CINDY COHN
We decided to start with our favorite question: What does the world look like if we get this stuff right?

ALVARO BEDOYA
For me, I think it is a world where you wake up in the morning, live your life and your ability to do what you want to do. See what you wanna see. Read what you wanna read and live the life that you want to live is unconnected to who you are in a good way.

In other words, what you look like, what side of the tracks you're from, how much money you have. Your gender, your gender identity, your sexuality, your religious beliefs, that those things don't hold you down in any way, and that you can love those things and have those things be a part of your life. But that they only empower you and help you. I think it's also a world… we see the great parts of technology. You know, one of the annoying things of having worked in privacy for so long is that you're often in this position where you have to talk about how technology hurts people. Technology can be amazing, right?

Mysterious, wonderful, uh, empowering. And so I think this is a world where those interactions are defined by those positive aspects of technology. And so for me, when I think about where those things go wrong, sorry, falling into old tropes here, but thinking about it positively, increasingly, people are applying for jobs online. They're applying for mortgages online. They are doing all these capital letter decisions that are now mediated by technology.

And so this world is also a world where, again, you are treated fairly in those decisions and you don't have to think twice about, hold on a second, I just applied for a loan. I just applied for a job, you know, I just applied for a mortgage. Is my zip code going to be used against me? Is my social media profile, you know, that reveals my interests gonna be used against me. Is my race gonna be used against me? In this world, none of that happens, and you can focus on preparing for that job interview and finding the right house for you and your family, finding the right rental for you and your family.

Now, I think it's also a world where you can start a small business without fear that the simple fact that you're not connected to a bigger platform or a bigger brand won't be used against you, where you have a level playing field to win people over.

CINDY COHN
I think that's great. You know, leveling the playing field is one of the original things that we were hoping, you know, that digital technologies could do. It also makes me think of that old New Yorker thing, you know, on the internet, no one knows you're a dog.

ALVARO BEDOYA
(Laughs) Right.

CINDY COHN
In some ways I think the vision is on the internet. You know, again, I don't think that people should leave the other parts of their lives behind when they go on the internet. Your identity matters, but that it doesn't, the fact that you're a dog doesn't mean you can't play. I'm probably butchering that poor cartoon too much.

ALVARO BEDOYA
No, I don't. I don't think you are, but I don't know why it did, but it reminded me of one other thing, which is in this world, you, you go to a. Whether it's at home in your basement like I am now, you know, or in your car or at an office, uh, uh, at a business. And you have a shot at working with pride and dignity where every minute of your work isn't measured and quantified. Where you have the ability to focus on the work rather than the surveillance of that work and the judgments that other people might make around that minute surveillance and, and you can focus on the work itself. I think too often people don't recognize the strangeness of the fact that when you watch tv, when you watch a streaming site, when you watch cable, when you go shopping, all of that stuff is protected by privacy law. And yet most of us spend a good part of our waking hours working and there are. Really no federal, uh, uh, worker privacy protections. That, for me is, is one of the biggest gaps in our sectoral privacy system that we've yet to confront.

But the world that you wanted me to talk about definitely is a world where you can go to work and do that work with dignity and pride, uh, without minute surveillance of everything you.

CINDY COHN
Yeah. And I think inherent in that is this, you know, this, this observation that, you know, being watched all the time doesn't work as a matter of humanity, right? It's a human rights issue to be watched all the time. I mean, that's why when they build prisons, right, it's the panopticon, right? That's where that idea comes from, is this idea that people who have lost their liberty get watched all the time.

So that has to be a part of building this better future, a space where, you know, we’re not being watched all the time. And I think you're exactly right that we kind of have this gigantic hole in people's lives, which is their work lives where it's not only that people don't have enough freedom right now, it's actually headed in the other direction. I know this is something that we think about a lot, especially Jason does at EFF.

JASON KELLEY
Yeah, I mean we, we write quite a bit about Boss Ware. We've done a variety of research into Boss Ware technology. I wonder if you could talk a little bit about maybe like some concrete examples that you've seen where that technology is sort of coming to fruition, if you will. Like it's being used more and more and, and why we need to, to tackle it, because I think a lot of people probably, uh, listening to this aren't, aren't as familiar with it as they could be.

And at the top of this episode we heard you describe your favorite Dr. Seuss tale – about the bees and the watchers, and the watchers watching the watchers, and so on to absurdity. Now can you tell us why you think that’s such an important image?

ALVARO BEDOYA
I think it's a valuable metaphor for the fact that a lot of this surveillance software may not offer as complete a picture as employers might think it does. It may not have the effect that employers think it does, and it may not ultimately do what people want it to do. And so I think that anyone who is thinking about using the software should ask hard questions about ‘is this actually gonna capture what I'm being told it will capture? Does it account for the 20% tasks of my workers' jobs?’ So, you know, there's always an 80/20 rule and so, you know, as with, as with work, most of what you do is one thing, but there's usually 20% that's another thing. And I think there's a lot of examples where that 20%, like, you know, occasionally using the bathroom right, isn't accounted for by the software. And so it looks like the employee’s slacking, but actually they're just being a human being. And so I would encourage people to ask hard questions about the sophistication of the software and how it maps onto the realities of work.

JASON KELLEY
Yeah. That's a really accurate way for people to start to think about it because I think a lot of people really feel that. Um, if they can measure it, then it must be useful.

ALVARO BEDOYA
Yes!

JASON KELLEY
In my own experience, before I worked at EFF, I worked somewhere where, eventually, a sort of boss ware type tool was installed and it had no connection to the job I was doing.

ALVARO BEDOYA
That’s interesting.

JASON KELLEY
It was literally disconnected.

ALVARO BEDOYA:
Can you share the general industry?

JASON KELLEY
It was software. I worked as a, I was in marketing for a software company and um, I was remote and it was remote way before p the pandemic. So, you know, there's sort of, I think boss ware has increased probably during the pandemic. I think we've seen that because people are worried that if you're not in the office, you're not working.

ALVARO BEDOYA
Right.

JASON KELLEY
There's no evidence, boss wear can't give evidence that that's true. It can just give evidence in, you know, whether you're at your computer –

ALVARO BEDOYA
Right. Whether you're typing.

JASON KELLEY
Whether you're typing. Yeah. And what happened in my scenario without going into too much detail was that it mattered what window I was in. and it didn't always, at first it was just like, are you at your computer for eight hours? And then it was, are you at your computer in these specific windows for eight hours? And then it was, are you typing in those specific windows for eight hours? The screws kept getting twisted, right, until I was actually at my computer for 12 hours to get eight hours of ‘productive’ work in, as it was called.

And so, yeah, I left that job. Obviously, I work at EFF now for a reason. And is was one of the things that I remember when I started at EFF, part of what I like about what we do is that we think about people's humanity in what they're doing and how that interacts with technology.

And I think boss ware is one of those areas where it doesn't, um, because it, it is so common for an employer to sort of disengage from the employee and sort of think of them as like a tool. It's, it's an area where it's easy for to install something or try to install something where that happens. So I'm glad you're working on it. It's definitely an issue.

ALVARO BEDOYA
Well, I'm thinking about it, you know, and it's certainly something I, I care about and, and I think, I think my hope is, My hope is that, um, you know, the pandemic was horrific. Is horrific. My hope is that one of the realizations coming out of it from so many people going remote is the realization that particularly for some jobs, you know, uh, um, a lot of us are lucky to have these jobs where a lot of our time turns.

Being able to think clearly and carefully about a, about something, and that's a luxury. Um, but particularly for those jobs, my, my suspicion is for an even broader range of jobs that this idea of a workday where you sit down, work eight hours and sit up, you know, and, and that is the ideal workday I don't think that's a maximally productive day, and I think there's some really interesting trials around the four-day work week, and my hope is that, you know, when my kids are older, that there will be a recognition that working harder, staying up later, getting up earlier, is not the best way to get the best work from people. And people need time to think. They need time to relax. They need time to process things. And so that is my hope that that is one of the realizations around it. But you're exactly right, Jason, is that one of my concerns around this software is that there's this idea that if it can be measured, it must be important. And I think you use a great example, speaking in general here, that of software that may presume that if you aren't typing, you're not working, or if you're not in a window, you're not working, when actually you might be doing the most important work. You know, jotting down notes, organizing your thoughts, that lets you do the best stuff as it were.

Music transition

JASON KELLEY
I want to jump in for a little mid-show break to say thank you to our sponsor.

“How to Fix the Internet” is supported by The Alfred P. Sloan Foundation’s Program in Public Understanding of Science and Technology. Enriching people’s lives through a keener appreciation of our increasingly technological world and portraying the complex humanity of scientists, engineers, and mathematicians. So a tip of the hat to them for their assistance.

Now back to our conversation with Alvaro Bedoya.

CINDY COHN
Privacy issues are of course near and dear to our hearts at EFF and I know that's really the world you come out of as well. Although your perch is a little, a little different right now. We came to the conclusion that we can't address privacy if we don't address competition and antitrust issues. And I think you've come someplace similar perhaps, and I'd love for you to talk about how you think privacy and questions around competition and antitrust intertwine.

ALVARO BEDOYA
So I will confess, I don't know if I have figured it out, but I can offer a few thoughts. First of all, I think that a lot of the antitrust claims are not what they seem to be. When companies talk about how important it is to have gatekeeping around app stores because of privacy and this is one of the reasons I support the bills, I think it's Blumenthal Blackburn bill to, um, to change the way app stores are, are run and, and, and kick the tires on that gatekeeping model because I am skeptical about a lot of those pro-privacy, anti-antitrust claims, that is one thing. On the other hand, I do think we need to think carefully about the rules that are put in place, backfiring against new entrants and small competitors. And I think a lot of legislators and policy makers in the US and Europe appreciate this and are getting this right and institute a certain set of rules for bigger companies and different ones for smaller ones, I think one of the ways this can go wrong is when it's just about the size of the company rather than the size of the user base.

I think that if you are, you know, suddenly of a hundred million users that you're not a small company, even if you have, you know, a small number of employees, but I, I do think that those concerns are real and that that policy makers and people in my role need to think about the costs of privacy compliance in a way that does not inadvertently create an unlevel playing field for, for small competitors.

I will confess that sometimes things that appear to be, uh, um, antitrust problems are privacy problems in that they reflect legal gaps around the sectoral privacy framework that unfortunately has yet to be updated. So I think I can give one example where there was the recent merger of, uh, Amazon and One Medical, and, well, I can't go into the antitrust analysis that may or may not have occurred at the commission. I wrote a statement on the completion of the merger, which highlighted a gap that we have around the anonymization rule in our health privacy law. For example, people think that HIPAA is actually the Health Information Privacy Act. It's not, it's actually the Health Insurance Portability Accountability Act. And I think that little piece of common wisdom speaks to a broader gap in our understanding of health privacy. So I think a lot of people think HIPAA will protect their data and that it won't be used in other ways by their doctor, by whoever it is that has their HIPAA protected data. Well, it turns out that in 2000 when HHS promulgated. The privacy rule in good faith, it had a provision that said, Hey, look, we want to encourage the improvement in health services. We want to encourage health research and we want to encourage public health. And so we're gonna say that if you remove these, you know, 18 identifiers from health data, that it can be used for other purposes and if you look at the rule that was issued, the justification for it is that they want to promote public health.

Unfortunately, they did not put a use restriction on that. And so now, if any, doctor's practice, anyone covered by HIPAA, and I'm not gonna go into the rabbit hole of who is and who isn't, but if you're covered by HIPAA, All they need to do is remove those identifiers from the data.

And HHS is unfortunately very clear that you can essentially do a whole lot of things that have nothing to do with healthcare as long as you do that. And what I wrote in my statement is that would surprise most consumers. Frankly, it surprised me when I connected the dots.

CINDY COHN
What I'm hearing here, which I think is really important is, first of all, we start off by thinking that some of our privacy problems are really due to antitrust concerns, but what we learn pretty quickly when we're looking at this is, first of all, privacy is used frankly, as a blocker for common sense reforms that we might need, that these giants come in and they say, well, we're gonna protect people's privacy by limiting what apps are in the app store. And, and we need to look closely at that because it doesn't seem to be necessarily true.

So first of all, you have to watch out for the kind of fake privacy argument or the argument that the tech giants need to be protected because they're protecting our privacy and we need to really interrogate that. And at the bottom of it, it often comes down to the fact that we haven't really protected people's privacy as a legal matter, right? We, we, We ground ourselves in Larry Lessig, uh, four pillars of change, right? Code, norms, laws, and markets. And you know, what they're saying is, well, we have to protect, you know, essentially what is a non-market, but the, the tech giants, that markets will protect privacy and so therefore we can't introduce more competition. And I think at the bottom of this, what we find a lot is that it's, you know, the law should be setting the baseline, and then markets can build on top of that. But we've got things a little backwards. And I think that's especially true in health. It's, it's, it's very front and center for those of us who care about reproductive justice, who are looking at the way health insurance companies are now part and parcel of other data analysis companies. And the Amazon/One Medical one is, is another one of those that unless we get the privacy law right, it's gonna be hard to get at some of these other problems.

ALVARO BEDOYA
Yeah. And those are the three things that I think a lot about first, that those propri arguments that seem to cut against, uh, competition concerns are often not what they seem.

Second, that we do need to take into account how one size fits all privacy rules could backfire in a way that hurts, uh, small companies, small competitors, uh, who are the lifeblood of, uh, innovation and employment frankly. And, and lastly, Sometimes what we're actually seeing are gaps in our sectoral privacy system.

CINDY COHN
One of the things that I know you've, you've talked about a little bit is, um, you're calling it a return to fairness, and that's specifically talking about a piece of the FTC’s authority. And I wonder if you could talk about that a little more and how you see that fitting into a, a better world.

ALVARO BEDOYA
Sure. One of the best parts of this job, um, was having this need and opportunity to immerse myself in antitrust. So as a Senate staffer, I did a little bit of work on the Comcast, uh, NBC merger against, against that merger, uh, for my old boss, Senator Franken. But I didn't spend a whole lot of time on competition concerns. And so when I was nominated, I, you know, quite literally, you know, ordered antitrust treatises and read them cover to cover.

CINDY COHN
Wonderful!

ALVARO BEDOYA
Well, sometimes it's wonderful and sometimes it's not. But in this case it was. And what you see is this complete two-sided story where on the one hand you have this really anodyne, efficiency-based description of antitrust, where it is about enforcing abstract laws and maximizing efficiency and the saying, you know antitrust is about protects competition, not competitors, and you so quickly lose sight of why we have antitrust laws and how we got them.

And so I didn't just read treatises on the law. I also read histories. And one of the things that you read and realize when you read those histories is that antitrust isn't about efficiency, antitrust is about people. And yes, it's about protecting competition, but the reason we have it is because of what happened to certain people. And so, you know, the Sherman Act, you listen to those floor debates, it is fascinating because first of all, everyone agrees as to what we want to do, what Congress wanted to do. Congress wanted to reign in the trust they wanted to reign in John Rockefeller, JP Morgan, the beef trust, the sugar trust, the steel trust. Not to mention, you know, the Rockefeller's Oil Trust. The most common concern on the floor of the Senate was what was happening to cattlemen because of concentration in meat packing plants and the prices they were getting when they brought their cattle to processors, and to market. And then you look at, uh, 1914, the Clayton Act again. There was outrage, true outrage about how those antitrust laws, you know, 10 out of the first 12 antitrust injunctions in our, in our country post-Sherman, were targeted at workers and not just any workers. They were targeted at rail car manufacturers in Pullman, where it was an integrated workforce and they were working extremely long hours for a pittance and wages, and they decided to strike.

And some of the first injunctions we saw in this country were used to. Their strike or how it was used against, uh, uh, I think they're called drayage men or dray men in New Orleans, port workers and dock workers in New New Orleans, who again, were working these 12 hour days for, for nothing in wages. And this beautiful thing happened in New Orleans where the entire city went on strike.

It was, I think it was 30 unions. It was like the typographical workers unions. And if you think that that refers to people typing on keyboards, it does. From the people typing on mechanical typewriters to the people, you know, unload loading ships in the dock of, in the port of New Orleans, everyone went on strike and they had this, this organization called the Amalgamated Working Men's Council. And um, and they went, they wanted a 10 hour, uh, uh, workday. They wanted overtime pay, and they wanted, uh, uh, union shops. They got two out of those three things. But, um, but I think it was the trade board was so unhappy with it that they, uh, persuaded federal prosecutors to sue under Sherman.

And it went before Judge Billings. And Judge Billings said, absolutely this is a violation of the antitrust laws. And the curious thing about Judge Billings decision is one of the first German decisions in a federal court, and he didn't cite for the proposition that the strike was a restraint on trade to restrain on trade law. He cited to much older decisions about criminal conspiracies and unions to justify his decision.

And so what I'm trying to say is over and over and over again, whenever, you know, you look at the actual history of antitrust laws, you know, it isn't about efficiency, it's about fairness. It is about how small competitors and working people, farmers, laborers, deserve a level playing field. And in 1890, 1914, 1936, 1950, this was what was front and center for Congress.

CINDY COHN
It's great to end with a deep dive into the original intent of Congress to protect ordinary people and fairness with antitrust laws, especially in this time when history and original intent are so powerful for so many judges. You know, it’s solid grounding for going forward. But I also appreciate how you mapped the history to see how that Congressional intent was perverted by the judicial branch almost from the very start.

This shows us where we need to go to set things right but also that it’s a difficult road. Thanks so much Alvaro.

JASON KELLEY
Well, it's a rare privilege to get to complain about a former employer directly to a sitting FTC commissioner. So that was a very enjoyable conversation for me. It's also rare to learn something new about Dr. Seuss and a Dr. Seuss story, which we got to do. But as far as actual concrete takeaways go from that conversation, Cindy, what did you pull away from that really wide ranging discussion?

CINDY COHN
It’s always fun to talk to Alvaro. I loved his vision of a life lived with dignity and pride as the goal of our fixed internet. I mean those are good solid north stars, and from them we can begin to see how that means that we use technology in a way that, for example, allows workers to just focus on their work. And honestly, while that gives us dignity, it also stops the kind of mistakes we’re seeing like tracking keystrokes, or eye contact as secondary trackers that are feeding all kinds of discrimination.

So I really appreciate him really articulating, you know, what are the kinds of lives we wanna have. I also appreciate his thinking about the privacy gaps that get revealed as technology changes and, and the, the story of healthcare and how HIPAA doesn't protect us in the way that we'd hoped to protect us, in part because I think HIPAA didn't start off at a very good place, but as things have shifted and say, you know, one medical is being bought by Amazon, suddenly we see that the presumption of who your insurance provider was and what they might use that information for, has shifted a lot, and that the privacy law hasn't, hasn't kept up.

So I appreciate thinking about it from, you know, both of those perspectives, both, you know, what the law gets wrong and how technology can reveal gaps in the law.

JASON KELLEY
Yeah. That really stood out for me as well, especially the parts where Alvero was talking about looking into the law in a way that he hadn't had to before. Like you say, because that is kind of what we do at EFF at least part of what we do. And it's nice to hear that we are sort of on the same page and that there are people in government doing that. There are people at EFF doing that. There are people all over, in different areas doing that. And that's what we have to do because technology does change so quickly and so much.

CINDY COHN
Yeah, and I really appreciate the deep dive he's done into antitrust law and, and revealing really the, the, the fairness is a deep, deep part of it. And this idea that it's only about efficiency and especially efficiency for consumers only. It's ahistorical. And that's a good thing for us all to remember since we, especially these days have a Supreme Court that is really, you know, likes history a lot and grounds and limits what it does in history. The history's on our side in terms of, you know, bringing competition law, frankly, to the digital age.

JASON KELLEY
Well that’s it for this episode of How to Fix the Internet.

Thank you so much for listening. If you want to get in touch about the show, you can write to us at podcast@eff.org or check out the EFF website to become a member or donate, or look at hoodies, t-shirts, hats or other merch.

This podcast is licensed Creative Commons Attribution 4.0 International, and includes music licensed Creative Commons Attribution 3.0 Unported by their creators. You can find their names and links to their music in our episode notes, or on our website at eff.org/podcast.

Our theme music is by Nat Keefe of BeatMower with Reed Mathis

And How to Fix the Internet is supported by the Alfred P. Sloan Foundation's program in public understanding of science and technology.

We’ll see you next time.

I’m Jason Kelley…

CINDY COHN
And I’m Cindy Cohn.

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This podcast is licensed Creative Commons Attribution 4.0 International, and includes the following music licensed Creative Commons Attribution 3.0 Unported by its creators:

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In a moment of clarity after initially moving forward a deeply flawed piece of legislation, the French National Assembly has done the right thing: it rejected a dangerous proposal that would have gutted end-to-end encryption in the name of fighting drug trafficking. Despite heavy pressure from the Interior Ministry, lawmakers voted Thursday night (article in French) to strike down a provision that would have forced messaging platforms like Signal and WhatsApp to allow hidden access to private conversations.

The vote is a victory for digital rights, for privacy and security, and for common sense.

The proposed law was a surveillance wishlist disguised as anti-drug legislation. Tucked into its text was a resurrection of the widely discredited "ghost” participant model—a backdoor that pretends not to be one. Under this scheme, law enforcement could silently join encrypted chats, undermining the very idea of private communication. Security experts have condemned the approach, warning it would introduce systemic vulnerabilities, damage trust in secure communication platforms, and create tools ripe for abuse.

The French lawmakers who voted this provision down deserve credit. They listened—not only to French digital rights organizations and technologists, but also to basic principles of cybersecurity and civil liberties. They understood that encryption protects everyone, not just activists and dissidents, but also journalists, medical professionals, abuse survivors, and ordinary citizens trying to live private lives in an increasingly surveilled world.

A Global Signal

France’s rejection of the backdoor provision should send a message to legislatures around the world: you don’t have to sacrifice fundamental rights in the name of public safety. Encryption is not the enemy of justice; it’s a tool that supports our fundamental human rights, including the right to have a private conversation. It is a pillar of modern democracy and cybersecurity.

As governments in the U.S., U.K., Australia, and elsewhere continue to flirt with anti-encryption laws, this decision should serve as a model—and a warning. Undermining encryption doesn’t make society safer. It makes everyone more vulnerable.

This victory was not inevitable. It came after sustained public pressure, expert input, and tireless advocacy from civil society. It shows that pushing back works. But for the foreseeable future, misguided lobbyists for police national security agencies will continue to push similar proposals—perhaps repackaged, or rushed through quieter legislative moments.

Supporters of privacy should celebrate this win today. Tomorrow, we will continue to keep watch.

The U.S. Patent and Trademark Office (USPTO) just made a move that will protect bad patents at the expense of everyone else. In a memo released February 28, the USPTO further restricted access to inter partes review, or IPR—the process Congress created to let the public challenge invalid patents without having to wage million-dollar court battles.

If left unchecked, this decision will shield bad patents from scrutiny, embolden patent trolls, and make it even easier for hedge funds and large corporations to weaponize weak patents against small businesses and developers.

IPR Exists Because the Patent Office Makes Mistakes

The USPTO grants over 300,000 patents a year, but many of them should not have been issued in the first place. Patent examiners spend, on average, around 20 hours per patent, often missing key prior art or granting patents that are overly broad or vague. That’s how bogus patents on basic ideas—like podcasting, online shopping carts, or watching ads online—have ended up in court.

Congress created IPR in 2012 to fix this problem. IPR allows anyone to challenge a patent’s validity based on prior art, and it’s done before specialized judges at the USPTO, where experts can re-evaluate whether a patent was properly granted. It’s faster, cheaper, and often fairer than fighting it out in federal court.

The USPTO is Blocking Patent Challenges—Again

Instead of defending IPR, the USPTO is working to sabotage it. The February 28 memo reinstates a rule that allows for widespread use of “discretionary denials.” That’s when the Patent Trial and Appeal Board (PTAB) refuses to hear an IPR case for procedural reasons—even if the patent is likely invalid. 

The February 28 memo reinstates widespread use of the Apple v. Fintiv rule, under which the USPTO often rejected IPR petitions whenever there’s an ongoing district court case about the same patent. This is backwards. If anything, an active lawsuit is proof that a patent’s validity needs to be reviewed—not an excuse to dodge the issue.

In 2022, former USPTO Director Kathi Vidal issued a memo making clear that the PTAB should hear patent challenges when “a petition presents compelling evidence of unpatentability,” even if there is parallel court litigation. 

That 2022 guidance essentially saved the IPR system. Once PTAB judges were told to consider all petitions that showed “compelling evidence,” the procedural denials dropped to almost nothing. This February 28 memo signals that the USPTO will once again use discretionary denials to sharply limit access to IPR—effectively making patent challenges harder across the board.  

Discretionary Denials Let Patent Trolls Rig the System

The top beneficiary of this decision will be patent trolls, shell companies formed expressly for the purpose of filing patent lawsuits. Often patent trolls seek to extract a quick settlement before a patent can be challenged. With IPR becoming increasingly unavailable, that will be easier than ever. 

Patent owners know that discretionary denials will block IPRs if they file a lawsuit first. That’s why trolls flock to specific courts, like the Western District of Texas, where judges move cases quickly and rarely rule against patent owners.

By filing lawsuits in these troll-friendly courts, patent owners can game the system—forcing companies to pay up rather than risk millions in litigation costs.

The recent USPTO memo makes this problem even worse. Instead of stopping the abuse of discretionary denials, the USPTO is doubling down—undermining one of the most effective ways businesses, developers, and consumers can fight back against bad patents.

Congress Created IPR to Protect the Public—Not Just Patent Owners

The USPTO doesn’t get to rewrite the law. Congress passed IPR to ensure that weak patents don’t become weapons for extortionary lawsuits. By reinforcing discretionary denials with minimal restrictions, and, as a result, blocking access to IPRs, the USPTO is directly undermining what Congress intended.

Leaders at the USPTO should immediately revoke the February 28 memo. If they refuse, as we pointed out the last time IPR denials spiraled out of control, it’s time for Congress to step in and fix this. They must ensure that IPR remains a fast, affordable way to challenge bad patents—not just a tool for the largest corporations. Patent quality matters—because when bad patents stand, we all pay the price.

The Atlantic has a search tool that allows you to search for specific works in the “LibGen” database of copyrighted works that Meta used to train its AI models. (The rest of the article is behind a paywall, but not the search tool.)

It’s impossible to know exactly which parts of LibGen Meta used to train its AI, and which parts it might have decided to exclude; this snapshot was taken in January 2025, after Meta is known to have accessed the database, so some titles here would not have been available to download.

Still…interesting.

Searching my name yields 199 results: all of my books in different versions, plus a bunch of shorter items...

The UK’s National Computer Security Center (part of GCHQ) released a timeline—also see their blog post—for migration to quantum-computer-resistant cryptography.

It even made The Guardian.

The previously undisclosed review could block assistance to millions of undocumented people and deter legal immigrants from seeking help in extreme weather.

The Defense secretary aims to purge climate work from the Pentagon. But critics say his carve-out for weather resiliency misses the point.

Legislators in the state, which leads the nation in building solar and wind, have circulated about 60 proposals to curb renewable development and boost gas.

President Donald Trump on Thursday signed a far-reaching order to ramp up mining and processing of critical minerals and other materials to counter China’s dominance.

Taking aim at the Department of Energy would undercut the agency that took on a bulk of the spending from the Democrats’ massive climate law.

Twelve EU capitals want programs to bring over American scholars.

But the state's highest bench left the door open for a group of young activists to revise their challenge against Utah's promotion of fossil fuels.

The nation’s capital is among dozens of states, cities and counties that have sued the oil industry for misleading consumers about the dangers of fossil fuels.

Saving and greening European steel mills is now a key part of the EU’s defense strategy.

The Commerce Commission is examining the impact of climate targets on banks, including commitments imposed by the Net-Zero Banking Alliance.

This year’s Las Fallas festival has taken on special meaning after over 220 people died in October’s flooding in Spain.

Quantum computers have the potential to solve complex problems that would be impossible for the most powerful classical supercomputer to crack.

Just like a classical computer has separate, yet interconnected, components that must work together, such as a memory chip and a CPU on a motherboard, a quantum computer will need to communicate quantum information between multiple processors.

Current architectures used to interconnect superconducting quantum processors are “point-to-point” in connectivity, meaning they require a series of transfers between network nodes, with compounding error rates.

On the way to overcoming these challenges, MIT researchers developed a new interconnect device that can support scalable, “all-to-all” communication, such that all superconducting quantum processors in a network can communication directly with each other.

They created a network of two quantum processors and used their interconnect to send microwave photons back and forth on demand in a user-defined direction. Photons are particles of light that can carry quantum information.

The device includes a superconducting wire, or waveguide, that shuttles photons between processors and can be routed as far as needed. The researchers can couple any number of modules to it, efficiently transmitting information between a scalable network of processors.

They used this interconnect to demonstrate remote entanglement, a type of correlation between quantum processors that are not physically connected. Remote entanglement is a key step toward developing a powerful, distributed network of many quantum processors.

“In the future, a quantum computer will probably need both local and nonlocal interconnects. Local interconnects are natural in arrays of superconducting qubits. Ours allows for more nonlocal connections. We can send photons at different frequencies, times, and in two propagation directions, which gives our network more flexibility and throughput,” says Aziza Almanakly, an electrical engineering and computer science graduate student in the Engineering Quantum Systems group of the Research Laboratory of Electronics (RLE) and lead author of a paper on the interconnect.

Her co-authors include Beatriz Yankelevich, a graduate student in the EQuS Group; senior author William D. Oliver, the Henry Ellis Warren (1894) Professor of Electrical Engineering and Computer Science (EECS) and professor of Physics, director of the Center for Quantum Engineering, and associate director of RLE; and others at MIT and Lincoln Laboratory. The research appears today in Nature Physics.

A scalable architecture

The researchers previously developed a quantum computing module, which enabled them to send information-carrying microwave photons in either direction along a waveguide.

In the new work, they took that architecture a step further by connecting two modules to a waveguide in order to emit photons in a desired direction and then absorb them at the other end.

Each module is composed of four qubits, which serve as an interface between the waveguide carrying the photons and the larger quantum processors.

The qubits coupled to the waveguide emit and absorb photons, which are then transferred to nearby data qubits.

The researchers use a series of microwave pulses to add energy to a qubit, which then emits a photon. Carefully controlling the phase of those pulses enables a quantum interference effect that allows them to emit the photon in either direction along the waveguide. Reversing the pulses in time enables a qubit in another module any arbitrary distance away to absorb the photon.

“Pitching and catching photons enables us to create a ‘quantum interconnect’ between nonlocal quantum processors, and with quantum interconnects comes remote entanglement,” explains Oliver.

“Generating remote entanglement is a crucial step toward building a large-scale quantum processor from smaller-scale modules. Even after that photon is gone, we have a correlation between two distant, or ‘nonlocal,’ qubits. Remote entanglement allows us to take advantage of these correlations and perform parallel operations between two qubits, even though they are no longer connected and may be far apart,” Yankelevich explains.

However, transferring a photon between two modules is not enough to generate remote entanglement. The researchers need to prepare the qubits and the photon so the modules “share” the photon at the end of the protocol.

Generating entanglement

The team did this by halting the photon emission pulses halfway through their duration. In quantum mechanical terms, the photon is both retained and emitted. Classically, one can think that half-a-photon is retained and half is emitted.

Once the receiver module absorbs that “half-photon,” the two modules become entangled.

But as the photon travels, joints, wire bonds, and connections in the waveguide distort the photon and limit the absorption efficiency of the receiving module.

To generate remote entanglement with high enough fidelity, or accuracy, the researchers needed to maximize how often the photon is absorbed at the other end.

“The challenge in this work was shaping the photon appropriately so we could maximize the absorption efficiency,” Almanakly says.

They used a reinforcement learning algorithm to “predistort” the photon. The algorithm optimized the protocol pulses in order to shape the photon for maximal absorption efficiency.

When they implemented this optimized absorption protocol, they were able to show photon absorption efficiency greater than 60 percent.

This absorption efficiency is high enough to prove that the resulting state at the end of the protocol is entangled, a major milestone in this demonstration.

“We can use this architecture to create a network with all-to-all connectivity. This means we can have multiple modules, all along the same bus, and we can create remote entanglement among any pair of our choosing,” Yankelevich says.

In the future, they could improve the absorption efficiency by optimizing the path over which the photons propagate, perhaps by integrating modules in 3D instead of having a superconducting wire connecting separate microwave packages. They could also make the protocol faster so there are fewer chances for errors to accumulate.

“In principle, our remote entanglement generation protocol can also be expanded to other kinds of quantum computers and bigger quantum internet systems,” Almanakly says.

This work was funded, in part, by the U.S. Army Research Office, the AWS Center for Quantum Computing, and the U.S. Air Force Office of Scientific Research. 

The ability to generate high-quality images quickly is crucial for producing realistic simulated environments that can be used to train self-driving cars to avoid unpredictable hazards, making them safer on real streets.

But the generative artificial intelligence techniques increasingly being used to produce such images have drawbacks. One popular type of model, called a diffusion model, can create stunningly realistic images but is too slow and computationally intensive for many applications. On the other hand, the autoregressive models that power LLMs like ChatGPT are much faster, but they produce poorer-quality images that are often riddled with errors.

Researchers from MIT and NVIDIA developed a new approach that brings together the best of both methods. Their hybrid image-generation tool uses an autoregressive model to quickly capture the big picture and then a small diffusion model to refine the details of the image.

Their tool, known as HART (short for hybrid autoregressive transformer), can generate images that match or exceed the quality of state-of-the-art diffusion models, but do so about nine times faster.

The generation process consumes fewer computational resources than typical diffusion models, enabling HART to run locally on a commercial laptop or smartphone. A user only needs to enter one natural language prompt into the HART interface to generate an image.

HART could have a wide range of applications, such as helping researchers train robots to complete complex real-world tasks and aiding designers in producing striking scenes for video games.

“If you are painting a landscape, and you just paint the entire canvas once, it might not look very good. But if you paint the big picture and then refine the image with smaller brush strokes, your painting could look a lot better. That is the basic idea with HART,” says Haotian Tang SM ’22, PhD ’25, co-lead author of a new paper on HART.

He is joined by co-lead author Yecheng Wu, an undergraduate student at Tsinghua University; senior author Song Han, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), a member of the MIT-IBM Watson AI Lab, and a distinguished scientist of NVIDIA; as well as others at MIT, Tsinghua University, and NVIDIA. The research will be presented at the International Conference on Learning Representations.

The best of both worlds

Popular diffusion models, such as Stable Diffusion and DALL-E, are known to produce highly detailed images. These models generate images through an iterative process where they predict some amount of random noise on each pixel, subtract the noise, then repeat the process of predicting and “de-noising” multiple times until they generate a new image that is completely free of noise.

Because the diffusion model de-noises all pixels in an image at each step, and there may be 30 or more steps, the process is slow and computationally expensive. But because the model has multiple chances to correct details it got wrong, the images are high-quality.

Autoregressive models, commonly used for predicting text, can generate images by predicting patches of an image sequentially, a few pixels at a time. They can’t go back and correct their mistakes, but the sequential prediction process is much faster than diffusion.

These models use representations known as tokens to make predictions. An autoregressive model utilizes an autoencoder to compress raw image pixels into discrete tokens as well as reconstruct the image from predicted tokens. While this boosts the model’s speed, the information loss that occurs during compression causes errors when the model generates a new image.

With HART, the researchers developed a hybrid approach that uses an autoregressive model to predict compressed, discrete image tokens, then a small diffusion model to predict residual tokens. Residual tokens compensate for the model’s information loss by capturing details left out by discrete tokens.

“We can achieve a huge boost in terms of reconstruction quality. Our residual tokens learn high-frequency details, like edges of an object, or a person’s hair, eyes, or mouth. These are places where discrete tokens can make mistakes,” says Tang.

Because the diffusion model only predicts the remaining details after the autoregressive model has done its job, it can accomplish the task in eight steps, instead of the usual 30 or more a standard diffusion model requires to generate an entire image. This minimal overhead of the additional diffusion model allows HART to retain the speed advantage of the autoregressive model while significantly enhancing its ability to generate intricate image details.

“The diffusion model has an easier job to do, which leads to more efficiency,” he adds.

Outperforming larger models

During the development of HART, the researchers encountered challenges in effectively integrating the diffusion model to enhance the autoregressive model. They found that incorporating the diffusion model in the early stages of the autoregressive process resulted in an accumulation of errors. Instead, their final design of applying the diffusion model to predict only residual tokens as the final step significantly improved generation quality.

Their method, which uses a combination of an autoregressive transformer model with 700 million parameters and a lightweight diffusion model with 37 million parameters, can generate images of the same quality as those created by a diffusion model with 2 billion parameters, but it does so about nine times faster. It uses about 31 percent less computation than state-of-the-art models.

Moreover, because HART uses an autoregressive model to do the bulk of the work — the same type of model that powers LLMs — it is more compatible for integration with the new class of unified vision-language generative models. In the future, one could interact with a unified vision-language generative model, perhaps by asking it to show the intermediate steps required to assemble a piece of furniture.

“LLMs are a good interface for all sorts of models, like multimodal models and models that can reason. This is a way to push the intelligence to a new frontier. An efficient image-generation model would unlock a lot of possibilities,” he says.

In the future, the researchers want to go down this path and build vision-language models on top of the HART architecture. Since HART is scalable and generalizable to multiple modalities, they also want to apply it for video generation and audio prediction tasks.

This research was funded, in part, by the MIT-IBM Watson AI Lab, the MIT and Amazon Science Hub, the MIT AI Hardware Program, and the U.S. National Science Foundation. The GPU infrastructure for training this model was donated by NVIDIA. 

Nature Climate Change, Published online: 21 March 2025; doi:10.1038/s41558-025-02288-z

Colonial legacies in tropical forestry hinder good management