Speaker 1: Welcome to tech Stuff, a production from I Heart Radio.
Speaker 1: Hey there, and welcome to tech Stuff. I'm your host,
Speaker 1: Jonathan Strickland. I'm an executive producer with I Heart Radio
Speaker 1: and I love all things tech and it is time
Speaker 1: for the news for Thursday, February eleven, twenty one. Let's
Speaker 1: get into it. SI Tech Daily published an article describing
Speaker 1: how computer scientists were able to defeat deep fake detecting
Speaker 1: computer algorithms and systems. So deep fakes, for those who
Speaker 1: aren't really that familiar with the term, are fabricated digital videos.
Speaker 1: They show what appears to be someone, but it's not
Speaker 1: really them. It's been digitally created. And the typical way
Speaker 1: that these are made is by feeding a lot of
Speaker 1: videos of your target person. So it's easier if we
Speaker 1: use an example. Let's say Ronald McDonald. You've got videos
Speaker 1: of Ronald McDonald, and you just feed all those videos
Speaker 1: of Ronald McDonald, the one specific incarnation of Ronald, because
Speaker 1: obviously lots of different actors have played Ronald McDonald, But
Speaker 1: you feed commercial after commercial of a specific actor playing
Speaker 1: Ronald into your deep fake generator. The more videos you have,
Speaker 1: the better, because you are training the digital machine learning
Speaker 1: model on how to represent that person, and then the
Speaker 1: deep fake generator can superimpose your target, Ronald McDonald their
Speaker 1: face on top of another video. So you could take
Speaker 1: a video of a totally different person. Maybe it's someone
Speaker 1: who's doing a credible impression of the target. Maybe it's
Speaker 1: not even that they're just going through various motions, and
Speaker 1: then you use the deep fake generator to overlay the
Speaker 1: digital face of Ronald McDonald on top of the other
Speaker 1: actors face in the video, and it makes it seem
Speaker 1: as though the target, Ronald was doing whatever it was
Speaker 1: the actor was doing the whole time. And detectors tend
Speaker 1: to look for little signs and videos that would indicate
Speaker 1: a deep fake, particularly around the eyes. The eyes are tricky,
Speaker 1: but the scientists who worked on this found that by
Speaker 1: inserting something called an adversarial example, or actually a lot
Speaker 1: of them, into videos, they could fool these detectors. So
Speaker 1: generally the idea is to include tiny signs that force
Speaker 1: these detectors to make mistakes. Now, according to the scientists,
Speaker 1: it's even possible to introduce the sort of adversarial examples
Speaker 1: into a deep fake video without any real knowledge of
Speaker 1: how the detectors actually process the videos in order to
Speaker 1: detect deep fakes, but a little knowledge does go a
Speaker 1: long way. The team tested scenarios in which attackers might
Speaker 1: have complete access to the detector model. In other words,
Speaker 1: they know exactly what the detector is looking for, and
Speaker 1: with that and introducing these adversarial examples, they could have
Speaker 1: a more than success rate in avoiding detection for videos
Speaker 1: that were uncompressed. They also tested scenarios in which hackers
Speaker 1: might only have very limited knowledge of the detector model,
Speaker 1: and even then with uncompressed video they saw an eight
Speaker 1: six percent success rate. Now, the approach used by the
Speaker 1: team preserves those adversarial examples even if a video does
Speaker 1: go through compression or resizing. Typically those are things that
Speaker 1: would remove adversarial examples from images, and under both scenarios
Speaker 1: the method worked at a slightly lower success rate if
Speaker 1: the video had been compressed, It was nearly successful if
Speaker 1: the team had complete knowledge of the detector model, and
Speaker 1: percent even if they didn't have that knowledge, so still
Speaker 1: incredibly reliable. They also chose not to publish the code
Speaker 1: that they were using for their adversarial examples because they said,
Speaker 1: if we did that, then bad guys could take this
Speaker 1: and make it their own and thus use it for
Speaker 1: real zs. So they recommended that teams that are designing
Speaker 1: deep fake detectors incorporate adversarial training when they build out
Speaker 1: their models. I think most teams already do this. Essentially,
Speaker 1: this creates a sort of seesaw effect. So you've got
Speaker 1: one computer system and its job is just to try
Speaker 1: and create the most convincing fakes possible, and you have
Speaker 1: a different system that is attempting to tell the difference
Speaker 1: between real videos and fake videos. So as the detectors
Speaker 1: get better, the faker system tries out new tricks to
Speaker 1: exploit potential weaknesses in the detector, and as the detectors
Speaker 1: fall behind, they begin to adjust their approach to get
Speaker 1: it are at picking out the fakes. And we've seen
Speaker 1: this sort of process in a lot of other areas
Speaker 1: of artificial intelligence. It really plays a big role in
Speaker 1: how AI evolves over time. Earlier this week, I talked
Speaker 1: about Tesla and bitcoin, and I did my normal angry
Speaker 1: old man rant about bitcoin being more of a commodity
Speaker 1: than it is a currency. Well, now I get to
Speaker 1: talk about another thing that irritates me about bitcoin, and
Speaker 1: that's how much juice bitcoin miners are using when they're
Speaker 1: going after those expensive digital coins. So let's get some
Speaker 1: quick explanations in here. You've got your digital currency bitcoin,
Speaker 1: and there are two main ways you can get bitcoin.
Speaker 1: There more than this, but these are the two big ones.
Speaker 1: You can purchase some so you're exchanging some other form
Speaker 1: of currency for some amount of bitcoin, or you can
Speaker 1: try and mine bitcoin. Mining essentially involves using a computer
Speaker 1: to guess the correct answer to a very hard mathematical problem,
Speaker 1: and the Bitcoin system, that is, the overall network that's
Speaker 1: in charge of tracking bitcoin transactions and dispensing mind bitcoins.
Speaker 1: The system determines how hard that mathematical problem should be. Now,
Speaker 1: ideally it should take about ten minutes before some computer
Speaker 1: on the network is able to solve the problem. So
Speaker 1: as more computational power joins this network, the system has
Speaker 1: to make the problems more challenging. Otherwise these screaming fast
Speaker 1: computer systems would solve the problems far too quickly. So
Speaker 1: the goal is to aim for that average amount of
Speaker 1: time that it takes to mind bitcoins, to keep it
Speaker 1: in around ten minutes. There's more to it than that,
Speaker 1: but that's a very basic explanation and since a single
Speaker 1: bitcoin is worth tens of thousands of dollars, nearly fifty
Speaker 1: dollars as I record this, and each successful mining of
Speaker 1: bitcoin pays out six point to five bit coins per go,
Speaker 1: so every ten minutes, another six and a quarter bitcoins
Speaker 1: get mind, that means there's a lot of money to
Speaker 1: be made, but it also means you need incredibly powerful
Speaker 1: computer systems if you're going to stand a chance of
Speaker 1: having the computer that guesses the correct answer to the
Speaker 1: mathematical problem. Otherwise someone else is going to beat you
Speaker 1: to the punch. And so people and groups have built
Speaker 1: out mining computers and really mining computer networks that are
Speaker 1: just trying to be the first to get these math
Speaker 1: problems correct. And these machines require a lot of electricity.
Speaker 1: Cambridge University researchers have estimated that the power consumption is
Speaker 1: in the neighborhood of one d twenty one point thirty
Speaker 1: six tara watt hours per year. That means all the
Speaker 1: bitcoin miners in the world collectively are consuming as much
Speaker 1: electricity as the entire nation of Argentina, and they're just
Speaker 1: behind Norway. Now. The only reason for this is because
Speaker 1: of those huge payouts, right, because if the amount you
Speaker 1: earned was a low amount, whether because you were only
Speaker 1: getting a fraction of a bitcoin every time you mind it,
Speaker 1: or the value of bitcoin had plummeted, or both, then
Speaker 1: it would mean that running your computer systems would actually
Speaker 1: be more expensive than the money you would get from
Speaker 1: mining bitcoins, and that would be a losing proposition, so
Speaker 1: you would quit right. You wouldn't want to keep spending
Speaker 1: money to make back a fraction of what you were spending.
Speaker 1: And maybe that will happen at some point. And if
Speaker 1: it does, and people drop out of the network because
Speaker 1: it costs too much money to continue mining, then the
Speaker 1: system will adjust that difficulty to those mathematical problems. Again,
Speaker 1: if it detects that it's taking more than ten minutes
Speaker 1: to solve the problems, it makes the problems easier. The
Speaker 1: idea of being that no matter what computer power is
Speaker 1: connected to the system, that ten minute to solution time
Speaker 1: remains fairly steady. So it's kind of like if you
Speaker 1: took the top performing students of a math class, but
Speaker 1: you still wanted to have the same you know, average grade,
Speaker 1: then you make the tests a little easier. But the
Speaker 1: energy demands of bitcoin are one of the aspects of
Speaker 1: the cryptocurrency that I find really irritating. Not only is
Speaker 1: it a quote unquote currency with a value that fluctuates
Speaker 1: so much that you can't really use it as a
Speaker 1: currency with confidence, it's also encouraging people to consume way
Speaker 1: more electricity than they would otherwise, and that has further
Speaker 1: consequences depending upon where that electricity is coming from. It
Speaker 1: might mean that bitcoin itself is contributing to climate change
Speaker 1: because people are using so many computer systems that are
Speaker 1: drawing power off a power grid that could be powered
Speaker 1: by coal. And then there are other, admittedly more minor consequences,
Speaker 1: such as not being able to find a decent graphics
Speaker 1: processing unit these days is because cryptocurrency miners keep buying
Speaker 1: them all stupid bitcoin. Cybersecurity researcher Alex Berson recently gave
Speaker 1: us more evidence that supply chain attacks are something that
Speaker 1: companies really need to take seriously, which is a theme
Speaker 1: we've been seeing since the Solar Winds hack. So, in
Speaker 1: this context, a supply chain attack is when a hacker
Speaker 1: is able to inject malware into some sort of product
Speaker 1: from a trusted entity that distributes that product to its
Speaker 1: partners or customers. Or whatever. But and itself sounds a
Speaker 1: bit confusing, so let's use a grim Batman style analogy.
Speaker 1: Let's say the Joker has just about had enough of
Speaker 1: Commissioner Gordon, and he knows that Commissioner Gordon likes pizza,
Speaker 1: So the Joker has one of his goons deliver a
Speaker 1: poisoned pizza to Gordon's house. Now, Gordon might accept the pizza,
Speaker 1: he might decline it, he might accept it but not
Speaker 1: eat it. So in other words, this is a ploy
Speaker 1: that might work, but it might not. So let's say
Speaker 1: instead the Joker decides, ah, I'm going to infiltrate Gordon's
Speaker 1: favorite pizza parlor. And the Joker gets in there and
Speaker 1: poisons all the dough in that pizza parlor, and then
Speaker 1: he has one of his goons drop off some coupons
Speaker 1: for the pizza parlor over at Gordon's home. Now, the
Speaker 1: Joker is banking on the fact that Gordon, he knows
Speaker 1: this pizza parlor, he likes the pizza there, and he
Speaker 1: just got some coupons for it, and he's gonna probably
Speaker 1: order pizza from that pizza place, and he will welcome
Speaker 1: the poisoned pizza into his home. Eagerly. That's kind of
Speaker 1: what happens with a supply chain attack because the malware
Speaker 1: is hidden inside a product that's from a trusted partner,
Speaker 1: so the victim is more likely to incorporate that malware
Speaker 1: into their own systems. Vers San was able to create
Speaker 1: an attack through squaw adding, which is grabbing a valid
Speaker 1: internal package name on code that happened to be distributed
Speaker 1: through geth hub. Essentially, he was leaning on an open
Speaker 1: source approach to code distribution, and a lot of companies
Speaker 1: use that for various products and it worked really well.
Speaker 1: His quote unquote malware which really didn't do much but
Speaker 1: returned some very basic information. Because he didn't want to
Speaker 1: actually cause any problems, he didn't want to compromise these systems.
Speaker 1: He was doing this a sort of a type of
Speaker 1: penetration testing to see if the companies regarded against this
Speaker 1: kind of attack. He found that it was effective in
Speaker 1: at least thirty five organizations, and these included really big ones.
Speaker 1: Apple was one of them. For example. He called it
Speaker 1: a quote dependency confusion bug end quote, and indicated that
Speaker 1: if a malicious hacker had taken that approach, they might
Speaker 1: have been able to do stuff like install backdoor access
Speaker 1: points into what would otherwise appear to be a secure system.
Speaker 1: To get into full detail of what he did would
Speaker 1: require an understanding that goes beyond what I have. But
Speaker 1: it does show that this kind of attack can be
Speaker 1: devastatingly effective if used by malicious hackers, and it could
Speaker 1: mean that in the future we'll see companies quarantine a
Speaker 1: system in order to test out patched software before incorporating
Speaker 1: that patch into the full system overall, just in case
Speaker 1: someone has compromised a trusted partner. I guess you just
Speaker 1: can't trust anyone. That's going to be a theme that
Speaker 1: comes back later. And in our last little bit for
Speaker 1: this segment, Twitter's chief financial officer Ned Siegel said in
Speaker 1: an interview that the band that Twitter has placed on
Speaker 1: former President Donald Trump's account is in fact permanent. He's
Speaker 1: really most sincerely banned. I guess you could say Trump
Speaker 1: received the band toward the end of his presidency after
Speaker 1: the riots at the US Capitol on January six, and
Speaker 1: that ban is going to be in place even if
Speaker 1: Trump is re elected to president sometime in the future. Yikes,
Speaker 1: So Siegel says to CNBC, the way our policies work
Speaker 1: when you're removed from the platform. You're removed from the platform,
Speaker 1: whether you're a commentator, you're a CFO, or you are
Speaker 1: a former or current public official. Remember, our policies are
Speaker 1: designed to make sure that people are not inciting violence,
Speaker 1: and if anybody does that, we have to remove them
Speaker 1: from the service. And our policies don't allow people to
Speaker 1: come back. End quote. Earlier this week, Twitter held and
Speaker 1: earnings called to share information with shareholders about how the
Speaker 1: company is doing. And I'm sure there was some concern
Speaker 1: that banning Trump was going to have a negative impact
Speaker 1: on the business side of the service. According to c NBC,
Speaker 1: Twitter beat analyst projections for earnings and for revenue into
Speaker 1: twenty twenty, but it did fall behind when it came
Speaker 1: to growing the user base. Twitter CEO Jack Dorsey also
Speaker 1: revealed that of Twitter's users are actually outside the United States.
Speaker 1: Twitter is also still dealing with being in the crosshairs
Speaker 1: of some world events, such as the ongoing farmer protests
Speaker 1: in India that I reported on previously. Well, we have
Speaker 1: some more news stories to cover, but before we get
Speaker 1: to any of those, let's take a quick break. On
Speaker 1: Tuesday's episode, I talked about how Apple's head of hardware
Speaker 1: had moved over to the company's Virtual and augmented reality department,
Speaker 1: which I guess we can just call mixed reality. That's
Speaker 1: kind of the the umbrella term for those technologies. Well,
Speaker 1: today we can follow up a little bit more on that.
Speaker 1: Mac Rumors published an article including designs by artist Antonio
Speaker 1: di Rosa, who has worked with Apple on several occasions
Speaker 1: to create artists renderings of different design concepts. Now, these
Speaker 1: renderings are meant more as a way to consider, you know,
Speaker 1: different design options. They may or may not resemble a
Speaker 1: final product from Apple. In fact, there's no guarantee that
Speaker 1: there will be a final product in some cases, although
Speaker 1: it seems pretty certain that this is going forward and
Speaker 1: de Rosa's pieces, these mixed reality headsets are given the
Speaker 1: name Apple View, but there is no indication that Apple
Speaker 1: has actually settled on any name as of yet. I'm
Speaker 1: still holding out for Eye Eyes or something like that.
Speaker 1: So what was it looked like? Well, it kind of
Speaker 1: looks like someone's got an iPhone strapped to their head.
Speaker 1: I mean, it just imagined that you've got a headband
Speaker 1: and there's a visor that fits over the eyes. It
Speaker 1: is kind of like a horizontal somewhat oval shaped iPhone,
Speaker 1: and it's curved so that it can fit over the
Speaker 1: eyes of the user. Oh and you better believe there's
Speaker 1: an Apple logos act dab in the middle of that thing.
Speaker 1: According to the website the information, the Apple design is
Speaker 1: said to incorporate more than twelve cameras in it, so
Speaker 1: this gadget could potentially be both for virtual and augmented reality.
Speaker 1: Those cameras could be used to provide a live video
Speaker 1: feed of the users surroundings, and the device could lay
Speaker 1: digital information on top of that, or it might also
Speaker 1: be used so that the headset can just have a
Speaker 1: sense of a user's environment and their head position and
Speaker 1: orientation if they are using it as a virtual reality device,
Speaker 1: thus giving queues to users so that you know, they
Speaker 1: don't do stuff like run into a wall or something.
Speaker 1: The general rumor right now is that it is going
Speaker 1: to be geared more as a VR device than an
Speaker 1: a R device. Maybe there will be some a R
Speaker 1: use cases, but they'll be more limited. That actually shocks
Speaker 1: me considering the number of cameras incorporated into this thing,
Speaker 1: though presumably those cameras will provide the headset with a
Speaker 1: lot of a bill these to track a user's head
Speaker 1: motions anyway. It also is supposed to have to eight
Speaker 1: K displays in there, one for each eye, and all
Speaker 1: of this helps explain why most of the websites I've
Speaker 1: seen talking about this thing are guessing that's going to
Speaker 1: cost around three thousand dollars when it does become available
Speaker 1: for purchase. It's supposed to be announced before the end
Speaker 1: of this year, and JP Morgan predicts that will go
Speaker 1: on sale within the first quarter of twenty twenty two,
Speaker 1: so just a year. That's kind of exciting. And speaking
Speaker 1: of cameras, well, we all know that we live in
Speaker 1: a world peppered with cameras. Lots of us have one
Speaker 1: within reach at any given moment thanks to our phones,
Speaker 1: and sure those cameras catch plenty of ridiculous and trivial stuff,
Speaker 1: but it also means that tons of people have powerful
Speaker 1: tools to document important events at a moment's notice, and
Speaker 1: that includes capturing video of police activity, something that some
Speaker 1: police have really tried to discourage in the past, but
Speaker 1: at least here in the United States, it is completely
Speaker 1: legal to record video of a police officer performing official
Speaker 1: duties in public, even if those police officers don't like it.
Speaker 1: Bling Bling reports that now there's a growing trend of
Speaker 1: police officers trying to leverage copyright takedown notices in an
Speaker 1: effort to discourage people from posting and sharing videos of them.
Speaker 1: The idea is pretty simple. So police officer sees that
Speaker 1: someone is trying to capture them on video, So the
Speaker 1: police officer whips out his or her own cell phone
Speaker 1: and blasts some copyrighted music. So the idea here is
Speaker 1: that the person capturing the video is getting that music
Speaker 1: on the microphone as well. If they upload the video
Speaker 1: to a social platform, the owner of the copyrighted music
Speaker 1: will issue a takedown notice for the unlicensed use of
Speaker 1: the music, particularly if it's all an automated system. Pretty
Speaker 1: shady stuff, right, And for activists this is really hard
Speaker 1: because if they get enough complaints about videos that they're posting,
Speaker 1: they might receive a ban from their platforms. And many
Speaker 1: of these activists are trying to perform a public service.
Speaker 1: In the wake of the Black Lives Matter movement, we
Speaker 1: have seen how important it is to hold police accountable,
Speaker 1: to make sure that those who are supposed to be
Speaker 1: protecting and serving and enforcing the law are themselves also
Speaker 1: subject to the law. The Drive has an interesting article
Speaker 1: about how farmers are turning to hackers in order to
Speaker 1: be able to repair their own equipment. All right, So
Speaker 1: this gets out a few different things that I've talked
Speaker 1: about on previous episodes of tech Stuff. There's this concept
Speaker 1: called the right to repair, which is, if you purchase
Speaker 1: some technology, whatever it may be. Maybe it's a stereo system,
Speaker 1: maybe it's a harvester for a farm, but you should
Speaker 1: be able to make reasonable repairs to that technology all
Speaker 1: on your own. The limits of your repair should really
Speaker 1: be up to your expertise and knowledge. But a lot
Speaker 1: of companies have made repairs really hard, from using proprietary
Speaker 1: screws and other fasteners, to making it intentionally difficult to
Speaker 1: access components, to including terms of service that discourage people
Speaker 1: from opening up a piece of technology in the first place.
Speaker 1: Then you've got the black box problem. This is when
Speaker 1: it's difficult or impossible for someone to see how a
Speaker 1: particular piece of technology works, and sometimes you have firmware
Speaker 1: there that prevents you from even doing any work unless
Speaker 1: you first run certain diagnostic tests and processes with official equipment.
Speaker 1: Now we've definitely seen this sort of thing in the
Speaker 1: automotive world, where it's much harder to work on modern
Speaker 1: vehicles compared to cars from just a few decades ago.
Speaker 1: While working on cars does require skill and knowledge, the
Speaker 1: barrier to entry was lower in the past. I mean,
Speaker 1: you still had to learn how to do it, but
Speaker 1: car companies weren't making it harder to do this. However,
Speaker 1: these days, with computerized systems and specialized service codes, it
Speaker 1: could be really hard to figure out what's even going
Speaker 1: on with a vehicle and even harder to conduct repairs.
Speaker 1: And the same is true with farm equipment. So farmers
Speaker 1: have become frustrated when trying to get hold of software
Speaker 1: and firmware from companies like John Deer in order to
Speaker 1: diagnose and repair problems with complicated equipment. Because of that,
Speaker 1: these farmers are starting to turn to pirate firmware for
Speaker 1: their equipment in order to be able to make those
Speaker 1: repairs themselves or to have independent mechanics do it for them,
Speaker 1: and companies like John Deer don't want that to happen.
Speaker 1: These companies purposefully restrict access to stuff like firmware and
Speaker 1: software because that represents another potential revenue source, which is
Speaker 1: repair and maintenance. See, if you make a tractor, you
Speaker 1: can only sell that one tractor once. But if you
Speaker 1: also offer repair and maintenance services, while you can keep
Speaker 1: making revenue off of at initial sale for as long
Speaker 1: as possible, I mean, especially if you make it really
Speaker 1: hard for anyone else to do those kinds of repairs
Speaker 1: and maintenance. And that's the heart of the problem. Farmers
Speaker 1: who understandably want to get the most out of their
Speaker 1: equipment would like to be able to do that kind
Speaker 1: of maintenance and repair themselves or on their own terms,
Speaker 1: and thus limit their costs. And this gets right into
Speaker 1: that right to repair issue, which is something we're seeing
Speaker 1: in different parts of the world as groups of consumers
Speaker 1: protest the business model that relies not just on sales
Speaker 1: of hardware, but having a whole sales department that's related
Speaker 1: to fixing and maintaining that hardware. And I should add that,
Speaker 1: according to the Drive, most of the farmers aren't actually
Speaker 1: happy about having to resort to pirate ID software and firmware.
Speaker 1: They would much prefer to go through official channels. They
Speaker 1: would prefer to purchase a license from John Deer directly.
Speaker 1: It's just that's not on the table. I see a
Speaker 1: lot of parallels with other industries actually, including the music industry. Historically,
Speaker 1: if companies make some aspect of their products difficult to access,
Speaker 1: people will find workarounds, and so it's generally just a
Speaker 1: bad idea to even go that route in the first place.
Speaker 1: On Wednesday, Facebook announced it would reduce the amount of
Speaker 1: political subject matter popping up in people's news feeds as
Speaker 1: part of an effort to reduce quote inflammatory content end quote.
Speaker 1: According to Tech Explore, it's going to start small, aiming
Speaker 1: at a sliver of users in places like Canada, Indonesia,
Speaker 1: and Brazil, before trying it out in the United States.
Speaker 1: Asta Gupta, the Product manager director at Facebook, said during
Speaker 1: these initial tests, will explore a variety of ways to
Speaker 1: rank political content in people's feeds using different signals, and
Speaker 1: then decide on the approaches will use going forward. Now.
Speaker 1: Apparently that means Facebook will no longer recommend politics themed
Speaker 1: groups to users, and it will reduce political themed posts
Speaker 1: that are here and feeds through automated systems. So, in
Speaker 1: other words, the algorithm suggesting these posts that part will stop.
Speaker 1: Users will still be able to post about politics if
Speaker 1: they want to. They'll still be able to join groups
Speaker 1: that have a political perspective and a political purpose if
Speaker 1: they want so. The idea here is really the algorithm
Speaker 1: is getting out of it. The algorithm that determines what
Speaker 1: you see where in your Facebook feed will be pulling
Speaker 1: back on the political stuff, But if all of your
Speaker 1: friends are chatting about politics, you're likely to still see
Speaker 1: a lot of politics over there. I think this shows
Speaker 1: how Facebook is continuing to react to the issues of
Speaker 1: extremist groups that were forming and radicalizing others on the platform,
Speaker 1: and how Facebook's algorithm really kind of played a part
Speaker 1: in all of that. The algorithm helped promote those groups
Speaker 1: to people that were potentially uh able to be radicalized,
Speaker 1: and so we saw that that trend get worse and worse.
Speaker 1: So I feel like this is largely a response to
Speaker 1: that and other lousy news. Nicolo Laurent, the CEO of
Speaker 1: Riot Games, is now under investigation for sexual harassment and
Speaker 1: gender discrimination charges. Now. The company Right Games is known
Speaker 1: for games like League of Legends and Valeriant, and the
Speaker 1: board of directors will be overseeing this investigation, which is
Speaker 1: being conducted by a third party law firm Lawrence. Former
Speaker 1: executive assistant Sharon O'Donnell claims that she was wrongfully terminated
Speaker 1: this past summer after she filed a complaint with the
Speaker 1: HR department against Laurent, saying he had made sexual advances
Speaker 1: toward her. There are other allegations against Laurent as well,
Speaker 1: primarily about some alleged comments he made in the company
Speaker 1: of women in the past, and I won't repeat those
Speaker 1: things here because you know they're gross. Riot Games has
Speaker 1: been under the microscope in the past for this kind
Speaker 1: of stuff too. Kotaku actually ran a really a great
Speaker 1: investigative peace in eighteen about the sexist sure at Riot Games,
Speaker 1: including stories from a former employee with the company who
Speaker 1: described her experiences of trying to navigate the culture and
Speaker 1: seeing her ideas consistently shot down, not on the merits
Speaker 1: of the ideas themselves, but because of her gender. She
Speaker 1: actually tells a story about how she pitched an idea,
Speaker 1: got shot down, told a male peer to pitch the
Speaker 1: same idea a couple of weeks later, and when he
Speaker 1: did it, it it went over like Gangbusters. That's not great.
Speaker 1: And later in a couple of people sued Riot Games
Speaker 1: for gender discrimination. So to me, it sounds like this
Speaker 1: has been an issue from the top down. Not that
Speaker 1: dissimilar to what we heard about Ubisoft last year. Over
Speaker 1: in the UK, police have arrested eight people between the
Speaker 1: ages of eighteen and twenty six who were allegedly part
Speaker 1: of a group trying to illegally access the phones of
Speaker 1: various prominent Americans like celebrities and sports stars, or rather,
Speaker 1: I should say the phone numbers. See, they were doing
Speaker 1: this through sim swapping. This is a process in which
Speaker 1: you will port a phone number from one simcard to another,
Speaker 1: and you might have to do this for totally legitimate reasons.
Speaker 1: Let's say that you're changing from one model of a
Speaker 1: phone to a totally different model of a phone, and
Speaker 1: they happen to use different style simcards. I had. This
Speaker 1: happened when you know the micro mini simcard thing was
Speaker 1: really transitioning, and you want to keep your phone numbers,
Speaker 1: so you want to be able to port your number
Speaker 1: from your old simcard to your new one, and you
Speaker 1: also want to be able to access all the apps
Speaker 1: and data you have on your old phone as easily
Speaker 1: as possible. Well, porting your account over to a new
Speaker 1: simcard is part of that process, and these hackers were
Speaker 1: trying to move phone numbers over to SIM cards that
Speaker 1: they had in their possession that would effectively hijack the
Speaker 1: phone numbers so that any calls going to that celebrity
Speaker 1: or sports star or whatever would instead go to this
Speaker 1: new phone. And it gave them the potential old to
Speaker 1: access tons of stuff along with it, like accounts with
Speaker 1: companies like Amazon for example. And you can see how
Speaker 1: this can be used for all sorts of illegal purposes,
Speaker 1: from theft to blackmail. So how did they make the swaps, Well,
Speaker 1: it seems like most of the time they were actually
Speaker 1: working with various phone providers, and they might fool the
Speaker 1: phone providers. You know, they could pose as the person
Speaker 1: who owns the number, or maybe an assistant to that
Speaker 1: celebrity or whatever, and then use a bit of social
Speaker 1: engineering to convince the technicians on the other end of
Speaker 1: the phone to go ahead and make that change to
Speaker 1: the new simcard. Or they might actually work with someone
Speaker 1: at the company's directly, someone who might have been in
Speaker 1: cahoots with the thieves, and once they do port that
Speaker 1: number over, they can wait to see if the targets
Speaker 1: started to make changes to stuff like passwords. So you
Speaker 1: know how two factor authentication systems can sometimes send like
Speaker 1: a password code to your phone. Well, if you swap
Speaker 1: the phone number over to a different simcard, then it's
Speaker 1: the hackers who are getting those, uh those text messages
Speaker 1: with the temporary passwords or the way to access certain accounts,
Speaker 1: and potentially they could switch over the accounts to themselves
Speaker 1: that way. UK law enforcement says the group faces charges
Speaker 1: of violating the Computer Misuse Act as well as fraud
Speaker 1: and money laundering charges, and that they could also face
Speaker 1: extradition to the United States for their crimes. Okay, we
Speaker 1: have a few more stories to wrap up today's news episode,
Speaker 1: but before we get to that, let's take another quick break. Hey,
Speaker 1: I'm back. Do you remember that earlier segment when I
Speaker 1: said there was a security researcher who had used a
Speaker 1: supply chain attack to test various big company systems and
Speaker 1: then found them lacking. Well, something similar has happened to
Speaker 1: a lot of Google Android users. Not at the heart
Speaker 1: of the problem is an app called barcode Scanner. I
Speaker 1: bet you can't guess what I does anyway. For a
Speaker 1: long time that app was total legit. It was a
Speaker 1: simple but effective barcode scanner. However, sometime in December of
Speaker 1: last year that changed. The security firm malware Bites, which
Speaker 1: you might remember was also the target of a supply
Speaker 1: chain attack itself, has reported that customers were seeing some
Speaker 1: weird behavior on their Android devices. When they would open
Speaker 1: up their default browser, they were getting absolutely bombarded with
Speaker 1: pop up ads. It was kind of like the bad
Speaker 1: old days of the Worldwide Web all over again, stupid
Speaker 1: pop up ads. At first, the analysts found these reports
Speaker 1: kind of perplexing because they would look at what the
Speaker 1: customers had on their phones and they'd say, Gosh, you
Speaker 1: haven't installed any new apps in a while, so nothing
Speaker 1: really has changed here. And all the apps that you
Speaker 1: have installed came from the official Google app store Google Play.
Speaker 1: These weren't like sideloaded apps from some geezy app developer
Speaker 1: or anything like that. And it turned out that barcode
Speaker 1: Scanner was in fact at fault, and more so, it
Speaker 1: appeared to be an intentional decision. In the words of
Speaker 1: security researcher Nathan Collier quote in the case of barcode Scanner,
Speaker 1: malicious code had been added that was not in previous
Speaker 1: versions of the app. Furthermore, the added code used heavy
Speaker 1: obfuscation to avoid detection to verify this is from the
Speaker 1: same app developer. We confirmed it had been signed by
Speaker 1: the same digital certificate as previous clean versions. Because of
Speaker 1: its malign intent, we jumped past our original detection category
Speaker 1: of adware straight to trojan yikes end quote. The yikes
Speaker 1: was mine, by the way, So yeah, a trojan is
Speaker 1: malware that poses as if it's benign legitimate software, and
Speaker 1: it carries with it some sort of payload that can
Speaker 1: execute malware of some kind on an infected system. Google
Speaker 1: has since removed the barcode Scanner app from the play Store,
Speaker 1: and if you happen to have that app installed on
Speaker 1: an Android device, you should uninstall that app remove it.
Speaker 1: Google is not removing that automatically, at least not as
Speaker 1: of the time I'm recording this episode, but you know,
Speaker 1: better safe than sorry. Go ahead check make sure it's
Speaker 1: not on any of your Android devices. If it is,
Speaker 1: remove it. And here's an example of some malicious code
Speaker 1: making its way to targets because it came from a
Speaker 1: trusted source. The tech world is really turning into a
Speaker 1: Mission Impossible movie where you learn you cannot trust anyone
Speaker 1: except Benji. It seems like a stand up dude that
Speaker 1: ethan character. I don't know about him. This next story
Speaker 1: is one that I'm sure you have all heard already,
Speaker 1: but I kind of had to cover it, particularly after
Speaker 1: taiwoh Adebamawo tweeted this story to me late on Tuesday.
Speaker 1: I am a course talking about the virtual courtroom proceeding
Speaker 1: in which a lawyer appeared on screen as a kitty cat.
Speaker 1: The three Judicial District Court in Texas was in session
Speaker 1: and County Attorney Rod Ponton had a cute kitty cap
Speaker 1: picture on display instead of video from his own webcam.
Speaker 1: Judge Roy Ferguson helpfully pointed out that Mr Ponton appeared
Speaker 1: to have a filter over his video chat settings, and
Speaker 1: Ponton said, quote, I'm here live, I'm not a cat
Speaker 1: end quote. The judge then replied, quote I can see
Speaker 1: that end quote. The judge subsequently posted a tweet recommending
Speaker 1: that Zoom users check their video filter settings before they
Speaker 1: actually join a meeting. Now, in the grand scheme of
Speaker 1: Zoom failures, this one's pretty innocent, and the judge commended
Speaker 1: Mr Ponton. He said, quote, the filtered lawyer showed incredible
Speaker 1: grace end quote. So honestly, after reading the story. This
Speaker 1: was a really refreshing and amusing take. No one got hurt,
Speaker 1: everyone remained professional. We got a fun story out of it,
Speaker 1: which is just nice. You know something else that is nice,
Speaker 1: or at least I think it is, is that computers
Speaker 1: are coming up with some really funky math. Y'all all right,
Speaker 1: So I'm gonna do my best to explain this, but
Speaker 1: I do so with full acknowledgement that I am in
Speaker 1: way over my head. My math skills topped out at
Speaker 1: trigonometry and algebra. But Vice has an article titled machines
Speaker 1: are inventing new math We've never seen, And at the
Speaker 1: heart of this are mathematical conjectures. Now, if you're like me,
Speaker 1: that term might be new to you. Essentially, it's a
Speaker 1: form of mathematical statement that as yet has not been
Speaker 1: rigorously proven to be true. So let's say you detect
Speaker 1: what appears to be a pattern in some data, and
Speaker 1: as far as you can tell, there is actually a
Speaker 1: pattern there, And after a bit you figure out a
Speaker 1: way to describe this pattern through a mathematical statement a formula,
Speaker 1: if you will. Now, does this mean there really is
Speaker 1: a pattern in that data? Well? Maybe, but maybe not.
Speaker 1: It might be only the appearance of a pattern, and
Speaker 1: it takes a lot of testing to make sure that
Speaker 1: that conjecture holds up, and if it does so after
Speaker 1: rigorous testing, then it might graduate and become a theorem.
Speaker 1: This is sort of like the concepts of hypotheses and
Speaker 1: theories in science. A hypothesis is a prediction which may
Speaker 1: or may not come true. A theory is something that
Speaker 1: has been tested multiple times in different ways, different approaches,
Speaker 1: different people, and has held up to be true despite
Speaker 1: all that testing, which is the same sort of thing,
Speaker 1: really well. The Vice article explains that computer systems are
Speaker 1: playing a bigger role in developing mathematical conjectures. One system,
Speaker 1: in particular, the Rama NuGen machine, developed in part by
Speaker 1: researchers from Google, is doing this. The system is creating
Speaker 1: conjectures aimed at calculating universal constants. Pie is an example
Speaker 1: of a universal constant. It's the ratio between the circumference
Speaker 1: of a circle and that circle's diameter, and this ratio
Speaker 1: is the same whether the circle is on the nanoscale
Speaker 1: or if the circle is larger than the known universe,
Speaker 1: because the ratio still remains three point one, four, etcetera. Etcetera, etcetera.
Speaker 1: And so these systems are proposing different formula to calculate
Speaker 1: universal constants. This could lead to far more efficient and
Speaker 1: accurate means of doing that. If those conjectures hold water,
Speaker 1: it will be up to mathematicians to put the conjectures
Speaker 1: to the test and just let me say better than
Speaker 1: than me. Now. I included this next story because I
Speaker 1: happened to love the music of the punk band The Pogues,
Speaker 1: famous for such tunes as fairy Tale of New York
Speaker 1: and Turkish Song of the Damned and Sunny Side of
Speaker 1: the Street. Well, Jim Finer, one of the original members
Speaker 1: of the Pogues and also the co writer on the
Speaker 1: songs I just mentioned, has created the proposal for an
Speaker 1: interesting artistic experiment. The goal, he says, was to create
Speaker 1: a means of making music of quote, indeterminate length and
Speaker 1: indeterminate score end quote. He took inspiration from an ancient
Speaker 1: practice in Japan, a type of meditation and musical instrument
Speaker 1: called the su kin kutsu, which involves an upside down
Speaker 1: jar and water drops. So imagine you've got a big jar,
Speaker 1: it's open at the top, you turn it upside down,
Speaker 1: you put it in a little like pit essentially, and
Speaker 1: you bury it. You cut a hole in the bottom
Speaker 1: of that jar, which is now effectively the top. You know,
Speaker 1: it's the part that's poking out the ground, and you
Speaker 1: allow water to drip through that hole into the interior.
Speaker 1: As the water accumulates, it has a little pool at
Speaker 1: the base of that jar that's buried underground, and the
Speaker 1: vibrations as the drops splashed down caused the jar to
Speaker 1: reverberate and it chimes out kind of like a bell.
Speaker 1: So Finer took this idea and he cranked it up
Speaker 1: a notch. In his own words, his quote score for
Speaker 1: a hole in the ground end quote was conceived as
Speaker 1: a composition of indeterminate length and score. Water dripping into
Speaker 1: a deep underground chamber strikes both tuned percussion and a
Speaker 1: pool at the bottom. The sounds are piped above ground
Speaker 1: through a giant horn that stands seven ms above the ground,
Speaker 1: and by pipe through, he's literally talking about a hollow tube,
Speaker 1: a horn that would use acoustics to amplify the sound
Speaker 1: as it travels up the length of the horn to
Speaker 1: the flared in above ground. He said, I like the
Speaker 1: idea of coming across this in a landscape unexpectedly. It's
Speaker 1: a piece that's made for people who know it's there,
Speaker 1: but equally it's made for people to just come across. Now,
Speaker 1: this reminds me of some other acoustic art pieces that
Speaker 1: I have seen, including the classic Aeolian harp, which is
Speaker 1: played by the wind. Nothing more punk rock than handing
Speaker 1: the instruments over to Mother Nature for a wicked solo.
Speaker 1: And finally, ten years ago, the world received an amazing gift.
Speaker 1: I am, of course talking about Rebecca Black's immortal classic Friday.
Speaker 1: Whether you're kicking in the front seat or sitting in
Speaker 1: the back seat. Well, now Rebecca Black has released a
Speaker 1: remix of that song ten years later, and it features
Speaker 1: not justin all grown up Rebecca sporting some neon punk looks,
Speaker 1: but also three oh three Big Freedia, who has one
Speaker 1: of the best Christmas albums I've ever heard, not Safe
Speaker 1: for Work, and Dorian Elektra on the track as well.
Speaker 1: And I listened to the remix and I have to
Speaker 1: tell you that it's remarkable in that it is so
Speaker 1: not my jam, but it is also not my jam
Speaker 1: in a different way than the original was also so
Speaker 1: not my jam. I think it is cool. However, that
Speaker 1: ms Black has been able to embrace her impact on
Speaker 1: the web and also pursue a legit career as a
Speaker 1: singer and songwriter. She never disappeared. She's had a YouTube
Speaker 1: channel and has been uploading to it for the last
Speaker 1: nine years, so she's been engaging with the public since
Speaker 1: her rise to viral fame. I have absolutely no doubt
Speaker 1: that she was also on the receiving end of an
Speaker 1: unbelievable amount of mockery for her original video, and I
Speaker 1: think that's really a shame. I mean, wasn't an indulgent project, sure,
Speaker 1: but good grief, y'all. If YouTube have been around when
Speaker 1: I was a kid, I am certain there would be
Speaker 1: no shortage of indulgent videos from yours truly. In fact,
Speaker 1: you could probably argue convincingly that there is no shortage
Speaker 1: of indulgent material from me as it stands right now.
Speaker 1: It's just that mine doesn't happen to go viral. Anyway,
Speaker 1: if you have fond or funny memories of the song,
Speaker 1: you might want to check out the bonkers music video
Speaker 1: for the remix. Now. I'm not saying you're gonna like it,
Speaker 1: but maybe you will, and you will certainly see something
Speaker 1: that is unique. Well, that wraps up this news episode.
Speaker 1: Hope you guys enjoyed it. If you have any suggestions
Speaker 1: for topics I can tackle on the normal Tech Stuff episodes,
Speaker 1: you can let me know on Twitter. The handle is
Speaker 1: tech stuff hs W and I will talk to you
Speaker 1: again really soon. Text Stuff is an I Heart Radio production.
Speaker 1: For more podcasts from I Heart Radio, visit the I
Speaker 1: Heart Radio app, Apple Podcasts, or wherever you listen to
Speaker 1: your favorite shows