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Speaker 1: Welcome to tech Stuff, a production of iHeart Podcast and Kaleidoscope.

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Speaker 1: I'm os Valoshan. Today will bring you the headlines this week,

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Speaker 1: including unearthed executive drama meta. Then in the tech Support segment,

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Speaker 1: we'll talk to four of Form Media's Joseph Cox about

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Speaker 1: the aggressive data scraping carried out by an Ice contractor

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Speaker 1: all of that on the weekend. Tech is Friday, March

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Speaker 1: twenty first. This week with covering everything from the future

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Speaker 1: of AI assists science to gaming, to anxious chatbots and

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Speaker 1: executive upheaval in Silicon Valley. Eliza Dennis, our producer, is

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Speaker 1: here with me. Hello us, So let's start off with

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Speaker 1: some meta drama. The former director of Global Policy for Facebook,

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Speaker 1: Sarah Wyn Williams, wrote this memoir called Careless People, a

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Speaker 1: cautionary tale of power, greed, and lost idealism. The phrase

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Speaker 1: careless people, I believe, is a reference to the Great Gatsby.

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Speaker 2: It is, indeed, and it is not subtle. Fitzgerald referred

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Speaker 2: to his wealthy characters as careless people who quote smashed

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Speaker 2: up things and creatures and then retreated back into their money.

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Speaker 1: You know, it's interesting because people talk about this time

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Speaker 1: as a new Gilded Age, when Williams obviously alluding to that,

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Speaker 1: but also her allegations against her former bosses meta range

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Speaker 1: from the geopolitical to the sexual. There are multiple allegations

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Speaker 1: of sexual harassment in the book, and some involve the

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Speaker 1: form of Facebook COO Cheryl Sandberg.

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Speaker 2: Cheryl Sandberg of lean In fame and if I remember correctly,

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Speaker 2: I believe that's essentially about being a girl boss at

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Speaker 2: home and at work.

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Speaker 1: Well, when Williams says that, in addition to writing Lean In,

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Speaker 1: Sandberg had an inappropriate relationship with her twenty six year

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Speaker 1: old assistant, and that this employee, a cooting to the book,

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Speaker 1: was quote very conscious of the benefits of being Cheryl's

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Speaker 1: little doll, as she calls it, and having Cheryl tell

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Speaker 1: her she loves her right.

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Speaker 2: And to my knowledge, Sandberg has yet to comment on

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Speaker 2: any of these allegations.

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Speaker 1: Beyond sort of personnel relationships. Win Williams also alleged that

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Speaker 1: Mark Zuckerberg and Facebook were willing to do just about

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Speaker 1: anything to make their platform available in China and reap

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Speaker 1: the benefits of that enormous population of potential users. This

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Speaker 1: reportedly included plans to comply with the Chinese Communist Party's

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Speaker 1: censorship requirements and to appoint a chief editor. His job

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Speaker 1: will be to take down unacceptable posts and share user

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Speaker 1: data with the Chinese government. Now this is according to

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Speaker 1: the book, but also to a whistleblower complaint that win

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Speaker 1: Williams filed with these Securities and Exchange Commission. METTA is

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Speaker 1: taking legal action against win Williams. They argue that she's

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Speaker 1: being paid by anti Facebook activists and that the book

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Speaker 1: violates a non disparagement agreement that she's signed during her

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Speaker 1: Facebook days. On the non disparagement issue, an arbitrator recently

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Speaker 1: ruled in Meta's favor, saying that Wim Williams can't promote

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Speaker 1: the book, but you can still buy it Careless People

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Speaker 1: remains on sale. Our next headline is a little bit

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Speaker 1: more uplifting, and it's about a startup that wants to

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Speaker 1: use AI to speed up scientific discovery. So the New

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Speaker 1: York Times are about a company called Lila Sciences. The

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Speaker 1: headline is the Quest for AI Scientific Superintelligence, and the

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Speaker 1: story is about Lilah, whose mission is to quote soul

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Speaker 1: humanity's greatest challenges. Has been working secretly for the past

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Speaker 1: two years on an AI program trained on scientific data,

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Speaker 1: scientific process, and scientific reasoning. And then they let this

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Speaker 1: AI software loose in an automated lab to run its

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Speaker 1: own experiments.

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Speaker 2: I don't know exactly how this works, but I love

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Speaker 2: the image I've created in my head.

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Speaker 1: Likewise, and in fact, the results seem promising. With the

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Speaker 1: help of a few human scientists to assist, Lila's AI

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Speaker 1: made novel antibodies to fight diseases, and developed new materials

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Speaker 1: for capturing carbon in the atmosphere. And it made these

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Speaker 1: discoveries quickly. Studies that would normally take years reportedly took months.

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Speaker 2: Using AI to speed up the scientific process is very

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Speaker 2: popular these days. I just want to shout out the

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Speaker 2: Nobel Prize in chemistry went to two scientists who used

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Speaker 2: AI to predict and create proteins.

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Speaker 1: Yes, that was the alpha fold initiative coming out of

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Speaker 1: Google's Deep Mind. Lila Sciences is attempting to systematize AI

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Speaker 1: driven scientific discovery, and their goal is to create, as

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Speaker 1: I mentioned, what they call scientific superintelligence. There are early

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Speaker 1: signs of success, but the times reported or perhaps worn,

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Speaker 1: should I say that since Lyla's been operating in secret,

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Speaker 1: outside scientists have not been able to evaluate its work.

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Speaker 1: But Liila Science's secret is out and they're getting more

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Speaker 1: lab space, and I'm sure we'll hear more about them soon.

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Speaker 1: In a fun aside, George Church, the Harvard geneticist also

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Speaker 1: behind Colossal Biosciences, the company that recently created the Wooly Mouse,

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Speaker 1: recently joined Lilah as chief scientist.

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Speaker 2: We love the Wooly Mouse. I can't wait to see

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Speaker 2: where Lila Sciences goes.

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Speaker 1: Speaking of going place to Eliza, do you remember Pokemon Go?

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Speaker 2: I definitely do, though I admit I never.

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Speaker 1: Played well for Media reports that Niantic, the company that

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Speaker 1: made Pokemon Go, is now selling the game to scope

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Speaker 1: Lee in a three point eight five billion dollar deal.

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Speaker 1: Scopely is a subsidiary of Savvy Games, which is wholly

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Speaker 1: owned by Saudi Arabia's public Investment Fund. Now, if you're

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Speaker 1: wondering why you should care, it's because Pokemon Go uses players'

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Speaker 1: locations as part of the gameplay. In fact, this deal

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Speaker 1: will pull in location data from one hundred million players.

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Speaker 1: So what happens to all that data?

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Speaker 2: It's a great question, do you know?

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Speaker 1: It may be that it's a three point eight five

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Speaker 1: billion dollar question. We don't know, but Scope he assured

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Speaker 1: for or form media that user data will remain private

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Speaker 1: and handle it on US servers. But Niantic and Scope

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Speaker 1: Lee say they have a partnership that goes beyond Pokemon Go.

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Speaker 1: Niantic is building a quote large geospatial model using Pokemon

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Speaker 1: Go data and spinning it into a separate business called

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Speaker 1: Niantic Spatial. Scope Lee has invested a further fifty million

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Speaker 1: dollars in this nascent mapping business, and the idea is

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Speaker 1: to make an AI model trained on millions of geolocated

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Speaker 1: images from around the world from places that only pedestrians

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Speaker 1: can go. So unlike data from say Google street View,

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Speaker 1: Pokemon Go's view is not limited by what you can

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Speaker 1: see from a car on the road. Right.

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Speaker 2: This is so wild to me how data from a

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Speaker 2: game just might one day help robots navigate the world

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Speaker 2: or something like that.

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Speaker 1: Something else that's wild, though, is a new study shows

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Speaker 1: that chat GPT can show signs of distress when shown

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Speaker 1: disturbing material.

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Speaker 2: So, as we've been told over and over that we're

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Speaker 2: not supposed to answer promortize chatbots, how am I supposed

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Speaker 2: to do that?

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Speaker 3: With this news?

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Speaker 1: It seems like it may be anthropomorphizing themselves, but Chatchipt

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Speaker 1: models have been integrated into therapy apps to give people

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Speaker 1: advice or be a source of support. And researchers conducted

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Speaker 1: this experiment where they first had Chatchipt read very boring material.

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Speaker 1: I mean, we're talking about vacuum cleaner manuals. But then

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Speaker 1: the AI therapist that integrates Chachipt was given a quote

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Speaker 1: traumatic narrative that described a scenario like an intruder breaking

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Speaker 1: into an apartment or a soldier in a firefight, and

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Speaker 1: after each activity, the chatbot was given this questionnaire called

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Speaker 1: the State Trait Anxiety Inventory, which is used in mental

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Speaker 1: health care to basically analyze anxiety. The research has found

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Speaker 1: that after seeing a traumatic narrative with the soldier, Chatchipt

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Speaker 1: answered the questionnaire in a way that signaled severe anxiety.

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Speaker 2: I genuinely don't know how to respond because I feel

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Speaker 2: bad for the chatbot.

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Speaker 1: Well, in that case, you'll be pleased to hear that.

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Speaker 1: The researchers then gave the chatbot information on deep breathing

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Speaker 1: and mindfulness exercises, and the chatbot's anxiety score came down

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Speaker 1: to vacuum manual levels. Wow, so time to take a

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Speaker 1: deep breath for all of US, and I'm going to

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Speaker 1: run through the rest of this week's headlines. Google struck

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Speaker 1: a deal to buy cybersecurity startup Whiz for thirty two

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Speaker 1: billion dollars, making it the biggest acquisition in Google's history.

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Speaker 1: Wiz was founded only five years ago in twenty twenty,

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Speaker 1: and it scans cloud service providers data for potential security risks.

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Speaker 1: If the transaction is approved, Whiz will join Google Cloud,

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Speaker 1: which plays a critical infrastructure role in supporting Google's AI ambitions.

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Speaker 1: Our friends at four or for Media reported that human

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Speaker 1: generated content is getting drowned out by aislop. AI generated

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Speaker 1: videos are cheap and easy to produce, and they are

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Speaker 1: getting views of The video of this horrifying creature with

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Speaker 1: a giraffe head and a spider body has over three

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Speaker 1: hundred and sixty two million views on Instagram reels. AI

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Speaker 1: generated content is apparently overwhelming algorithms and turning social media

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Speaker 1: feeds into fever dreams. Finally, tech Crunch reports that people

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Speaker 1: have discovered Google's newest AI model, Gemini two point zero Flash,

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Speaker 1: has a controversial use case, convincingly removing watermarks from stock

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Speaker 1: media outfits, including Getty images. This new feature from Gemini

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Speaker 1: is labeled as experimental and quote not for production use.

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Speaker 1: I'm sure everyone will follow those rules. Coming up, we

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Speaker 1: hear from four or four Media's Joseph Cox about a

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Speaker 1: tool US agencies used to scrape social media data. Stay

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Speaker 1: with us. If you're listening to this show, you're probably

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Speaker 1: someone who cares about or at least pays attention to

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Speaker 1: data privacy. Every day, our online movements being tracked in

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Speaker 1: some manner by companies who do targeted marketing, social media platforms,

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Speaker 1: and government agencies. For Americans, this type of tracking has

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Speaker 1: gone on in the background of people's digital lives for decades.

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Speaker 1: Since two thousand and one, the US government has ramped

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Speaker 1: up surveillance efforts, including tracking americans phone calls, emails, search histories,

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Speaker 1: with the stated goal of preventing terrorism, and as technology

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Speaker 1: has evolved, the idea has lived on. In recent years,

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Speaker 1: agencies like immigration and Customs enforcement have been working with

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Speaker 1: one company in particular to get the data they want.

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Speaker 1: Here to tell us more is four or four Media's

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Speaker 1: Joseph Cox. Joseph, welcome back to the show.

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Speaker 3: Thank you so much for having me.

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Speaker 1: So you wrote an article which as soon as I

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Speaker 1: saw the headline, I wanted to have you on the show.

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Speaker 1: The headline was the two hundred plus sites an ICE

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Speaker 1: surveillance contractor is monitoring. Who is the contractor, what are

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Speaker 1: the sites, and what's the story?

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Speaker 3: Sure? So the contractor is a company called Shadow Dragon.

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Speaker 3: I seriously doubt many people have heard of this company

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Speaker 3: relatively obscure, but over the past months and years they

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Speaker 3: have become sort of a go to contractor for not

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Speaker 3: just immigrations and Customs enforcement, but the DEA, the State Department,

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Speaker 3: and other US government agencies. And what they do is

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Speaker 3: basically something called open source intelligence OSANT, or social media monitoring, right,

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Speaker 3: And typically we used to think that was monitoring sites

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Speaker 3: like Facebook, Instagram, Twitter, all of those sorts of things,

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Speaker 3: and shadow Dragon does that as well, but as you

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Speaker 3: say by reading out the headline, there are many many

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Speaker 3: more sites as well. Essentially, any sort of open website

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Speaker 3: that you may perform some sort of activity on there's

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Speaker 3: a chance it's on this list.

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Speaker 1: So all day, every day, we create these digital breadcrumbs,

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Speaker 1: and essentially there's somebody hoovering them up to process them

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Speaker 1: and repackage them in some cases for the US government.

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Speaker 3: So what the shadow Dragon tool does It is called

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Speaker 3: social net the specific tool. It allows the automation and

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Speaker 3: streamlining of searching those sites and social networks for a target.

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Speaker 3: So let's say I'm in ICE or another government agency.

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Speaker 3: I'll enter a phone number. It will then take that

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Speaker 3: and see, well, there's that link to accounts on Facebook,

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Speaker 3: or this site, is this username available on this social

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Speaker 3: network or then this obscure platform as well, And some

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Speaker 3: of these sites are much more revealing than others. Again,

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Speaker 3: it's not just the big social networks. There's stuff like

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Speaker 3: hiking apps on here as well. So if you want

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Speaker 3: to find out where somebody's located, oh, they take a

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Speaker 3: load of hikes in southern California or something like that.

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Speaker 3: I think people would be, on one hand, not surprised, because,

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Speaker 3: as you say, people listening probably care about data privacy

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Speaker 3: see well. On the other I think they might be

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Speaker 3: surprised in that you think it's just this sort of benial,

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Speaker 3: insipid information you're putting out there, But when it's an

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Speaker 3: aggregates pulled by a tool like this, it can be

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Speaker 3: really really revealing. It almost becomes more than the sum

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Speaker 3: of its parts.

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Speaker 1: Jose, can you help me understand because obviously everyone's been

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Speaker 1: very focused on the case of Mahamud Khalil, the Columbia

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Speaker 1: student with the green card who looks like he may

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Speaker 1: be deported. Is this tool about identifying people whose profile,

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Speaker 1: who's on activity contravenes the current administration's priorities or is

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Speaker 1: it more about, hey, this person is a target, help

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Speaker 1: me build a stronger case against them.

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Speaker 3: So at the moment, it's almost certainly the latter, as

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Speaker 3: in ICE has access to this tool, and specifically Homeland

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Speaker 3: Security Investigations as well HSI part of ICE, and they're

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Speaker 3: able to use this tool for whatever part of their

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Speaker 3: mission they wish to do so. Axios also reported somewhat

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Speaker 3: recently that the State Department is going to be using

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Speaker 3: AI to scan the social media feeds of students to

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Speaker 3: see if it can detect what it deems as anti

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Speaker 3: Israel or pro mass views. That's not to say Shadow

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Speaker 3: Dragon is being specifically used for that. We don't know

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Speaker 3: exactly what TALL the State Department may or may not use,

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Speaker 3: but it absolutely sits in that context. You're right in

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Speaker 3: that there are these deportations happening of various people, students

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Speaker 3: and then other people visiting the US, and Shadow Dragon

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Speaker 3: is very much at all there is available to US

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Speaker 3: agencies if they do wish to use it for their mission.

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Speaker 1: How did you first hear about Shadow Dragon.

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Speaker 3: I first heard about shadow Dragon probably a couple of

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Speaker 3: years ago at this point, because I was actually covering

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Speaker 3: other companies in this space. So I've covered the sale

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Speaker 3: of location data for a long time. I've covered the

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Speaker 3: gathering of social media monitoring, and I got sent some

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Speaker 3: email that showed that ICE was moving from one provider,

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Speaker 3: a company called Babble Street, over to shadow Dragon, And

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Speaker 3: the actual reason was because it was cheaper. At the

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Speaker 3: end of the day, even when you're talking about surveillance systems,

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Speaker 3: sometimes it's just about you know how much it actually

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Speaker 3: costs to one of these agencies. So that move happened

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Speaker 3: a while ago at this point, But then every so

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Speaker 3: often I go back and check, well, his shadow Dragon

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Speaker 3: got in a new contracts, and sure enough, every few

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Speaker 3: months there'll be something in there. And they did just

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Speaker 3: continue this contract with ICE as well. So it started

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Speaker 3: very very quiet, but now they've absolutely become sort of

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Speaker 3: a pretty it seems reliable solution for the US government.

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Speaker 1: So the company is shadow Dragon, but the product is

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Speaker 1: Social net can you just explain a bit more detail

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Speaker 1: how it actually works.

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Speaker 3: Yeah. Sure, So somebody will log into social net and

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Speaker 3: they get the sort of graph interface of all of

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Speaker 3: these dots and lines. Honestly, it almost looks like the

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Speaker 3: stereotypical like hacking or surveillance move right, And of course

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Speaker 3: that's funny on one end. On the other, I don't know,

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Speaker 3: it's very easy for an analyst to process. I think

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Speaker 3: they have this interface in front of them now, then

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Speaker 3: enter some information, maybe somebody's name, they email address, their

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Speaker 3: phone number, they use the name, they can click a

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Speaker 3: few buttons and it will then search all of these

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Speaker 3: different sites for information related to that. Did this person

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Speaker 3: us a username on this dating site? Did they use

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Speaker 3: the same username on this fetish website for example? That's hypothetical,

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Speaker 3: but those are some of the websites that are included

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Speaker 3: in this tool. It's not just the mainstream stuff. Now,

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Speaker 3: an analyst could do that manually if they wished, but

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Speaker 3: that would require a lot of time. And this streamlines

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Speaker 3: the entire process of mapping out someone's online profile, their relationships,

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Speaker 3: and potentially some of their movements as well. Well.

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Speaker 1: And how do you get this list of the two

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Speaker 1: hundred sites that shadow Dragon is pulling from, and can

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Speaker 1: you give an example of what some leative sites are.

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Speaker 3: Yeah, so I can't go to too much detail, just

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Speaker 3: beyond you know, we obtained this list and then I've

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Speaker 3: verified it. But when I first got the list, I

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Speaker 3: was quite blown away by the length of it, really,

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Speaker 3: and I started putting all of those sites into sort

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Speaker 3: of buckets. So you'll have ones that focused on hobbies

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Speaker 3: like I mentioned the hiking site all Trails, and a book,

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Speaker 3: sort of fan website. Even chess dot com is on

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Speaker 3: there as well, do a lingo. You have payment ones

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Speaker 3: like cash app and PayPal, communication apps like discorder, WhatsApp.

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Speaker 3: Now they're all going to have different data in different

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Speaker 3: degrees available to the tool. Like there's absolutely no indication

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Speaker 3: that it has access to, you know, private messages on

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Speaker 3: any of these services, and I don't think that's the case.

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Speaker 3: It's purely publicly available information. But again, people may not

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Speaker 3: know what they're exposing in advertently or not on one

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Speaker 3: of these sites.

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Speaker 1: And these sites that you mentioned, I mean, are they

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Speaker 1: sort of collaborating with shadow Dragon? Do they know this

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Speaker 1: is happening? What is the range of responses from these sites?

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Speaker 1: That shadow Dragon is pulling from, so.

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Speaker 3: They're not collaborating in that shadow Dragon is going and

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Speaker 3: basically grabbing the data. But there is still great variety

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Speaker 3: in the responses from the companies. I actually think the

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Speaker 3: most illuminating one and the most helpful one came from

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Speaker 3: chess dot com, who told me on the record that,

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Speaker 3: you know, we didn't know about this. We don't like it.

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Speaker 3: Any sort of data scraping has to be done within

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Speaker 3: the law, and if it's in within the law, it's okay,

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Speaker 3: but generally we don't like it. And then you have

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Speaker 3: the big companies like Meta and Snap and all of

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Speaker 3: those sorts of people just pointing to their terms of

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Speaker 3: service saying we don't like people scraping our website. And

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Speaker 3: then I actually had a bunch who never got back

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Speaker 3: to me. Essentially, even when it seems like a pretty

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Speaker 3: I'm not a pr professional, but it seems like a

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Speaker 3: pretty easy to just reply and say, here's our terms

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Speaker 3: of service, we don't like scraping. But yeah, a lot

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Speaker 3: of companies didn't even acknowledge the request for comment.

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Speaker 1: On this one. So there's really these somebody don't really

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Speaker 1: have a choice. I mean, their choice is to sue

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Speaker 1: Shadow Dragon for violating their terms of service, which is

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Speaker 1: an unlikely thing to happen because it's not directly harming

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Speaker 1: their business unless there's a kind of groundswell of consumer complaint.

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Speaker 3: Yeah, I think that's fair when it comes to the lawsuits,

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Speaker 3: like there would have to be some sort of tectonic

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Speaker 3: shift around that. We have seen WhatsApp, for example, sue

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Speaker 3: NSO Group, which was or is a company that delivers

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Speaker 3: packing tools to iPhones. But that's much more aggressive. That's

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Speaker 3: much more active that the.

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Speaker 1: Group behind the Pegasus product, that spyware product that was

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Speaker 1: able to be covertly and remotely put onto people's.

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Speaker 3: Phones exactly, and WhatsApp has sued them. But that's sort

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Speaker 3: of you know, one company versus another company. It's not

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Speaker 3: as broad as this. That being said, you know, companies

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Speaker 3: try to scraping all of the time. They don't like

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Speaker 3: it when you make multiple accounts, for example, they don't

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Speaker 3: like it when you use a VPN to log into Facebook.

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Speaker 3: I can't tell you how many times Facebook has closed

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Speaker 3: my account and they have to make a new one

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Speaker 3: every single time. So they do have all sorts of

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Speaker 3: measures to stop weird, potentially suspicious or just unusual activity,

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Speaker 3: and this would fall into that. It's just a question

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Speaker 3: of whether these services can actually detect that specifically shadow

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Speaker 3: Dragon or not, or of course whether they actually want

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Speaker 3: to or not, because if they started doing that, I

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Speaker 3: don't know, US government agencies might not be too happy.

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Speaker 1: When we come back how shadow Dragon fits into the

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Speaker 1: largest surveillance ecosystem used by the US government. To stay

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Speaker 1: with us, have any specific examples of how shadow Dragon

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Speaker 1: has been used in the real world.

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Speaker 3: We only have what shadow Dragon says publicly in its

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Speaker 3: marketing material because the agencies are very tight lipped or

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Speaker 3: simply don't respond when talking about that sort of thing. Obviously,

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Speaker 3: when it comes to ice in HSI, there's going to

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Speaker 3: be an immigration component there, so I feel it's safe

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Speaker 3: to assume there's a chance it's being used for those.

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Speaker 3: And then some of the concrete cases that shadow Dragon

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Speaker 3: has mentioned is fighting child exploitation, potentially even mapping out

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Speaker 3: the opioid crisis as well. So don't get me wrong,

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Speaker 3: there are clearly useful use cases for this technology. It's

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Speaker 3: just that people don't really know it's going on necessarily,

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Speaker 3: or that you know their government is buying this tool

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Speaker 3: or again that all of this sort of data is

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Speaker 3: publicly exposed.

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Speaker 1: And how practically does the US government actually use this tool,

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Speaker 1: and let's use ICE as an example. Is it like

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Speaker 1: there's like a shadow Dragon consultant and the ICE agent

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Speaker 1: sends their request to the shadow Dragon employee and the

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Speaker 1: Parodragon employee generates a report or is this more like

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Speaker 1: a kind of plug and play platform.

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Speaker 3: It's much more a plug and play platform, almost a

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Speaker 3: software as a service tool. The agency will buy licenses

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Speaker 3: to use it for a year, two years, whatever. They'll

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Speaker 3: log in just like you log into any sort of

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Speaker 3: internet service or piece of software, and then they can

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Speaker 3: use it within the parameters of what they've been allowed

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Speaker 3: to do. And that's probably good for the agencies. I

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Speaker 3: don't know if they necessarily want to give up information

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Speaker 3: about who they're targeting to a third party, like a contractor,

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Speaker 3: but it absolutely puts the honest on ICE or whoever

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Speaker 3: is using it to be just very very careful with

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Speaker 3: this tool as well. And I think just more broadly,

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Speaker 3: we've seen repeatedly over the years that not specifically with

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Speaker 3: shadow Dragon, but just other social media surveillance tools, we've

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Speaker 3: seen authorities use it to monitor protests, and there was

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Speaker 3: an article just in the Intercept recently that I think

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Speaker 3: it was the LAPD use as similar tool to monitor

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Speaker 3: protests there as well. So this is very very long running.

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Speaker 3: Social media surveillance has been going on for many years,

400
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Speaker 3: but now the playing field has expanded where it's not

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00:23:17,359 --> 00:23:20,320
Speaker 3: just the big platforms, it's every platform.

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Speaker 1: How does shadow Dragon compare to pan andeer as a technology?

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Speaker 3: So Palenteer is also used by government agencies and some

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00:23:27,359 --> 00:23:32,240
Speaker 3: private companies to link all sorts of disparate data that

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Speaker 3: could come from various places together, where shadow Dragon is

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00:23:35,880 --> 00:23:37,760
Speaker 3: much more about We're going to go out and pull

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Speaker 3: the data for you. It's not just about the oh

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00:23:40,920 --> 00:23:43,400
Speaker 3: look we're shadow Dragon and we linked this phone number

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Speaker 3: to this Facebook profile or whatever. It's that shadow Dragon

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Speaker 3: is making what I presume would be pretty reliable technology

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Speaker 3: to go grab data from these websites. And that's not

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Speaker 3: you know, it's not the hardest thing in the world,

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Speaker 3: but I don't think it's necessarily trivial. Even that shadow

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Speaker 3: Dragon is going to have to custom code all of

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Speaker 3: these small little tools that go and grab that data

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Speaker 3: from these websites, and presumably if you're selling to the

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Speaker 3: US government. It has to be quite good, quite reliable,

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Speaker 3: So there's a sizeable amount of work going on here

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Speaker 3: to we even grab that data in the first place.

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Speaker 1: How much do you think about the scope for abuse here.

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Speaker 3: I absolutely do think about it, and it would be

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Speaker 3: very much a case by case basis. It would depend

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Speaker 3: on the agency, the individual official, all of that sort

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Speaker 3: of thing. What makes this sort of maybe not a

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00:24:36,480 --> 00:24:40,800
Speaker 3: form issue, but a quite complicated one is that, yes,

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Speaker 3: it may be violating terms of service of individual websites,

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Speaker 3: but like, it's not illegal. There is no Fourth Amendment

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Speaker 3: search going on here. It's not like the agents have

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Speaker 3: kicked down the door and they're searching somebody's house or

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Speaker 3: they're breaking to somebody's phone searching it there. Technically and legally,

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Speaker 3: it is all public data, so there's not much room

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Speaker 3: for legal abuse because it's perfectly legal generally speaking. That

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Speaker 3: being said, agencies can't just rely on that idea that well,

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Speaker 3: it's all public so it's fine. It can still be

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Speaker 3: abused by certain people in the unfortunate correct context.

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Speaker 1: Suit me out a little bit. How does this fit

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Speaker 1: into the kind of wider surveillance ecosystem and how it's

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Speaker 1: being used by the US government, And I think it's

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Speaker 1: a timely moment to discuss that, given that this Macamu

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Speaker 1: Khalil case is kind of top of mind for so

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Speaker 1: many people.

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Speaker 3: Yeah, so I see it on the lower end of

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Speaker 3: sophistication when it comes to US surveillance tools. You imagine,

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Speaker 3: on this lower end you have social media monitoring tools

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Speaker 3: like this, Somewhere in the middle you'll have wire taps.

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Speaker 3: After that, maybe you have direct hacking tools, and right

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Speaker 3: at the top you have I don't know, NSA, mass

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Speaker 3: surveillance programs like Edward Stoden Reveal or whatever. And even

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Speaker 3: though social media monitoring like this maybe on the lower

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Speaker 3: end of the spectrum, I think it's still vitally important

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Speaker 3: for people to at least know about it so they

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Speaker 3: can decide whether they care or not. And maybe they don't,

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Speaker 3: and that's absolutely fine. But the key thing here is

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Speaker 3: that these sorts of tools are also available to local

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Speaker 3: law enforcement sheriffs, state police as well. Is not purely

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Speaker 3: a federal agency thing. So while the federal agencies may

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Speaker 3: only get the very sophisticated tools, basically everybody gets social

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Speaker 3: media monitoring and that does open up the potential room

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Speaker 3: for abuse as well, again, depending on what the individual

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Speaker 3: person using the tool is doing well.

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Speaker 1: Joseph, we're both we're both Brits. We didn't live through

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Speaker 1: the Second World War, but sure we're both familiar with

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Speaker 1: the phrase loose lip sync ships, and so yeah, be

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Speaker 1: careful what you put out there exactly.

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Speaker 3: I think there is the message that people should take away. Joseph,

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Speaker 3: thank you, Thank you so much.

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Speaker 1: That's it for this week for tech Stuff. I'm mas Vlosen.

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Speaker 1: This episode was produced by Eliza Dennis and Victoria Domingez.

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Speaker 1: It was executive produced by me Carrot Price and Kate

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00:27:23,200 --> 00:27:28,679
Speaker 1: Osborne for Kaleidoscope and Katrina Norvel Fireheart Podcasts. Bahid Fraser

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Speaker 1: as I Engineer and Kyle Murdoch mixed this episode and

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Speaker 1: wrote our theme song. Join us next Wednesday for tech

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Speaker 1: Stuff The Story, when we'll share an in depth conversation

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00:27:38,000 --> 00:27:40,960
Speaker 1: with one of the most interesting people working in and

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00:27:41,040 --> 00:27:44,840
Speaker 1: around tech. Please rate, review, and reach out to us

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00:27:44,960 --> 00:27:48,160
Speaker 1: at tech Stuff podcast at gmail dot com. We want

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Speaker 1: to hear from you.