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 a love of all things tech, and I figured
Speaker 1: i'd do UH an episode or two about tech and privacy.
Speaker 1: I've titled this episode how Tech Spies on Us, But
Speaker 1: right from the get go, I have to admit that
Speaker 1: that is a little disingenuous because in many cases, not all,
Speaker 1: but in many cases, we're essentially giving tech permission to
Speaker 1: just harvest information about us, which is a little different
Speaker 1: than spying. It's kind of like saying, no, I'm cool
Speaker 1: with there being a live camera on me all the time,
Speaker 1: just broadcasting to some other location. You can't really call
Speaker 1: that spying if you were in on it at the top.
Speaker 1: But the way tech tends to go about this UH
Speaker 1: usually follows a pathway that isn't transparent, and it's not
Speaker 1: always obvious, and sometimes it relies on people not really
Speaker 1: being aware of what they've agreed to. So I really
Speaker 1: wanted to go into that so that we can all
Speaker 1: have a deeper understanding of how tech gathers information and
Speaker 1: then how companies leverage that and exploit our information, and
Speaker 1: furthermore to kind of, you know, think about whether or
Speaker 1: not we're okay with this. Some of you might be,
Speaker 1: and there's I'm not casting any shade, I'm not making
Speaker 1: any judgments, but others might not be. And that's why
Speaker 1: I wanted to kind of go through this and really
Speaker 1: get down to why it seems like our tech has
Speaker 1: almost a preternatural ability to know things about us. So
Speaker 1: let me paint for you a hypothetical situation. You are
Speaker 1: hanging out with a friend and you're both chatting a out,
Speaker 1: you know, all sorts of stuff, and the two of
Speaker 1: you decided to go to a nice restaurant with an
Speaker 1: outdoor seating area because you know, we're still kind of
Speaker 1: post pandemic type stuff, and you know you're being super
Speaker 1: responsible with regard to health concerns and all of that. Anyway,
Speaker 1: you have a conversation with your friend who is telling
Speaker 1: you all about this movie they just watched. And after
Speaker 1: your meal, you say goodbye to your friend and you
Speaker 1: head on home. Later that same day or evening or
Speaker 1: night whatever, you're on the internet and you see something
Speaker 1: kind of weird. You actually start seeing ads for that
Speaker 1: film your friend was talking about popping up on different
Speaker 1: sites and services, and you don't remember seeing ads for
Speaker 1: this particular movie before, So maybe it's cherry picking. Maybe
Speaker 1: it's the whole van as always by the corner thing
Speaker 1: where you only notice something after it's been brought to
Speaker 1: your attention. But maybe it's not. So what the heck
Speaker 1: is going on? Was your phone spying on you? Was
Speaker 1: it listening in on your conversationation that you had with
Speaker 1: your friend at dinner and then sent that information off
Speaker 1: somewhere to be processed and analyzed, then sold to advertisers,
Speaker 1: And then when you get back and now you have
Speaker 1: targeted ads aimed at you because your phone was eavesdropping
Speaker 1: on you. Now, I mentioned this sort of thing in
Speaker 1: a recent tech News episode, and I'm not gonna make
Speaker 1: you wait through this whole episode to answer that hypothetical question.
Speaker 1: Your tech is most likely not listening in on your conversations,
Speaker 1: not because that would be hard to do it. It
Speaker 1: actually wouldn't be hard to do that, but because there's
Speaker 1: really no need to do it. There's no need to
Speaker 1: go that far. Also, if tech were actually actively listening
Speaker 1: in on you all the time, governments around the world
Speaker 1: would be extremely interested in that, either to use it
Speaker 1: for their themselves as a kind of surveillance of their
Speaker 1: own citizens and people who are within the country, or
Speaker 1: they would want to go after tech companies for violating
Speaker 1: various privacy and security laws. Now, the point is that
Speaker 1: the way our modern tech works, and the way companies collect, share,
Speaker 1: and barter our data, means there's no need to listen
Speaker 1: in to what we're saying. Our tech knows who we are,
Speaker 1: it knows where we go, it knows what we're doing,
Speaker 1: and because the people around us also carry similar tech,
Speaker 1: it knows who we're with, and by cross referencing data,
Speaker 1: it knows what sort of connections exist between us. So
Speaker 1: today I thought I talk a bit more about how
Speaker 1: our tech collects data and the history of that, from
Speaker 1: the stuff that we willingly surrender to the stuff that
Speaker 1: we might not even realize was being shared. We'll talk
Speaker 1: about how this has evolved and how geolocation has played
Speaker 1: a really big part in this, and this will lead
Speaker 1: us to some recent events in which we've seen big
Speaker 1: companies like Facebook and Google try to skirt around attempts
Speaker 1: to give users the option to opt out of some
Speaker 1: forms of data collection now, as always in tech stuff,
Speaker 1: anyone who's listened to a textuff episode knows I love
Speaker 1: going through history because it's not like there was just
Speaker 1: a switch that was flipped one day and then suddenly
Speaker 1: all of our personal information got hoovered up by the Internet. Also,
Speaker 1: we should keep in mind that there are a lot
Speaker 1: of different privacy laws around the world that can restrict
Speaker 1: this kind of you know, data collection and how data
Speaker 1: companies can use that information. So, for example, the European
Speaker 1: Union has laws that provide a decent amount of protection
Speaker 1: for citizens. But as I am located in the United States,
Speaker 1: where the Internet first got its start, and thus where
Speaker 1: the attitudes and practices regarding private information on the Internet
Speaker 1: got their start, at least with regard to you know,
Speaker 1: the web and the Internet in general, I'm mostly going
Speaker 1: to be focusing on the good old us of a
Speaker 1: which isn't really that old, and frequently isn't that good either.
Speaker 1: So here in the United States, a right to privacy
Speaker 1: was not one of the guarantees laid out in the Constitution,
Speaker 1: at least not explicitly. However, the various forms of government,
Speaker 1: including the Supreme Court, over the course of decades and
Speaker 1: several court cases has essentially found that four of the
Speaker 1: first five amendments to the Constitution extend over towards a
Speaker 1: right to privacy. So those would be the first Amendment.
Speaker 1: That's the one that guarantees the right to assembly, uh,
Speaker 1: the freedom of religion, the freedom of speech, and the
Speaker 1: freedom of expression. Then we skip over the second Amendment
Speaker 1: and we head over to Amendment number three, which prevents
Speaker 1: the government from being able to station soldiers in private
Speaker 1: homes of citizens. Then there's the Fourth Amendment, which protects
Speaker 1: citizens from unreasonable search and seizure. That's a big part
Speaker 1: of privacy obviously. And then we've got Amendment number five,
Speaker 1: which has a little bit of Monica in my life. Wait, no,
Speaker 1: I'm sorry, that's mambo number five. Amendment number five says
Speaker 1: that US citizens enjoy certain legal protections. For example, you
Speaker 1: can't be tried for the same crime twice, right, that's
Speaker 1: double jeopardy. That obviously doesn't include stuff like the appeals process,
Speaker 1: but that's separate. Also, citizens can take the Fifth Amendment
Speaker 1: to avoid self incrimination during a trial, so they cannot
Speaker 1: be compelled to confess to a crime. Uh. That again
Speaker 1: relates to privacy. Now, none of those four amendments provide
Speaker 1: explicit rights to privacy, but they all extend towards that
Speaker 1: direction in different ways. So that was back in seventeen
Speaker 1: eighty nine, which means it was like two centuries before
Speaker 1: we had to worry about the Internet, but a century
Speaker 1: after the Constitution was ratified. That being an eight ninety
Speaker 1: an article written by Justice Louis Brandy and Samuel Warren
Speaker 1: argued for a more explicit right to privacy. It was
Speaker 1: the early days of photography in the eighteen nineties, and
Speaker 1: already the two saw the potential for people to have
Speaker 1: their privacy violated due to the fact that now it
Speaker 1: was easier to capture a moment forever and then potentially
Speaker 1: distribute it widely through the press. In nineteen fourteen, we
Speaker 1: got the founding of the Federal Trade Commission, or FTC. Now,
Speaker 1: the primary responsibility of the FTC is to ensure that
Speaker 1: companies within the United States are playing fair. The FTC
Speaker 1: can go after companies that use deceptive commercial practices, but
Speaker 1: later on, really like starting around the nineteen seventies, the
Speaker 1: FTC would also focus on companies that violated citizen privacy,
Speaker 1: going global. For a moment in nineteen forty eight, the
Speaker 1: United Nations drafted the Declaration of Human Rights, which included
Speaker 1: within it article number twelve, of which states, quote no
Speaker 1: one shall be subjected to arbitrary interference with his privacy, family, home,
Speaker 1: or correspondence, nor two attacks upon his honor and reputation.
Speaker 1: Everyone has the right to the protection of the law
Speaker 1: against such interference or attacks. End quote. Now, apart from
Speaker 1: the non inclusive pronoun usage there, this was a really
Speaker 1: big step toward positioning privacy as a basic human right.
Speaker 1: In nineteen sixty a legal scholar named William Prosser published
Speaker 1: an article titled Fittingly Enough Privacy, and in that article
Speaker 1: processor outlined four cases in which infringing on privacy should
Speaker 1: allow for the victim to pursue a civil lawsuit against
Speaker 1: the perpetrator. Those four cases were intrusion upon seclusion or solitude,
Speaker 1: so in other words, someone's barging in on you when
Speaker 1: you're just trying to be alone, or intrusion into private affairs. Similarly,
Speaker 1: public disco cosure of embarrassing private facts, which when you
Speaker 1: think about that, the Internet and the way it works
Speaker 1: would just catch on fire if people were really holding
Speaker 1: that seriously. Today publicity which places a person in a
Speaker 1: false light in the public eye was another case. And
Speaker 1: appropriation of one's name or likeness. So if someone were
Speaker 1: to go about posing as Jonathan Strickland and it's not me,
Speaker 1: it's not someone else who's actually named Jonathan Strickland like
Speaker 1: they were trying to pose as me, I should be
Speaker 1: allowed to sue that person based on that that criteria. Now,
Speaker 1: obviously in these cases, uh, there's a lot of leeway
Speaker 1: because there also are issues where it kind of starts
Speaker 1: to track a little bit toward issues with the First Amendment. Right,
Speaker 1: So in case of public disclosure of embarrassing private facts,
Speaker 1: if you're talking about a public figure, there's a lot
Speaker 1: more leeway there because it may be that that public
Speaker 1: fig years private facts have a public bearing, like if
Speaker 1: it's a politician or something. So it does get a
Speaker 1: little dicey, but these matters always do. We'll skip ahead
Speaker 1: to nineteen seventy four, though I should say that there
Speaker 1: were some court cases and some scholarly articles that further
Speaker 1: the framing of privacy. By nineteen seventy four, the US
Speaker 1: passed the Privacy Act, which placed limits on how federal
Speaker 1: agencies can collect and use personally identifiable information not granted.
Speaker 1: These restrictions were all about government use, federal government use,
Speaker 1: not state government, and not corporate use, so it's not
Speaker 1: like this applied across the board. In nineteen six, the
Speaker 1: US government passed the Telephone Consumer Protection Act and established
Speaker 1: they Do Not Call Registry, and these were meant to
Speaker 1: reduce the number of solicitation calls that citizens would get,
Speaker 1: you know, the spam calls we would call them today,
Speaker 1: and it would give people the opportunity to opt out
Speaker 1: of being on that regis streets, so that in theory,
Speaker 1: you wouldn't get those cold calls. Now, this is one
Speaker 1: of those things that in recent years has become an
Speaker 1: area of focus because stuff like robo calls and spoofing
Speaker 1: have really sidestepped the protections that were in place all
Speaker 1: the way back in six rendering them almost meaningless. And
Speaker 1: you've heard a lot of calls even in you know,
Speaker 1: high areas of Congress to have a new version of
Speaker 1: this too address things like companies that use spoofing and
Speaker 1: robo calls to do a widespread targeting of spam. Over
Speaker 1: in Europe, the EU adopted the Data Protection Directive in
Speaker 1: nine and then in the EU replaced that with the
Speaker 1: General Data Protection Regulation or g d p R. This
Speaker 1: is the set of rules and restrictions that really prevents
Speaker 1: largely like big tech companies from following the same source
Speaker 1: of strategies in the EU that they follow here over
Speaker 1: in the United States. So you'll hear a lot about
Speaker 1: companies having to readjust how they work in the EU,
Speaker 1: because if they were to continue to operate as they
Speaker 1: do in the United States, they could be held legally
Speaker 1: liable for lots of violations. There are other rules that
Speaker 1: are important. There's KAPPA. That's the Children's Online Privacy Protection
Speaker 1: Act here in the United States. That act places much
Speaker 1: tighter restrictions on companies when it comes to the collection
Speaker 1: and use of data about people who are younger than thirteen.
Speaker 1: That law and the enforcement of it have created some
Speaker 1: fairly tricky situations for companies and for others, like notably
Speaker 1: content creators on platforms like YouTube. But I'm pretty sure
Speaker 1: I'm gonna have to do just a full episode on
Speaker 1: KAPPA and its consequences in the future, because those consequences
Speaker 1: include stuff that I think are valuable and stuff that
Speaker 1: because of the interpretation of the law and the implementation
Speaker 1: of policies on platforms like YouTube can also be harmful.
Speaker 1: It's complicated, so that's why it would require its own episode.
Speaker 1: In the US past, the Graham Leach Blightly Act, which
Speaker 1: requires financial institutions to explain how they use and share
Speaker 1: private consumer data. So this was for things like credit
Speaker 1: organizations banks. That kind of thing also requires that those
Speaker 1: companies provide a means for customers to opt out of
Speaker 1: having their information shared, which is a pretty good point
Speaker 1: to focus on for a second. In the United States,
Speaker 1: the general approach the default is to require companies to
Speaker 1: provide an opt out option, but a lot of companies
Speaker 1: bury these sorts of settings or features so that they're
Speaker 1: not easy to find or activate, and often any disclosure
Speaker 1: of there being an opt out feature can be buried
Speaker 1: inside a long terms of service end user agreement page
Speaker 1: which most people don't take the time to read. And
Speaker 1: I'm just as guilty of this as other people. I
Speaker 1: don't I'm not you know, I'm not throwing shade here, folks,
Speaker 1: I am. I've done this, and some people argue that
Speaker 1: it would be better to have an opt in approach,
Speaker 1: so this would be where you would sign up for
Speaker 1: a service. You would be told, hey, do you mind
Speaker 1: if we use your information to do X, Y and
Speaker 1: Z in a very clear and transparent way, not buried
Speaker 1: in like pages and pages of terms of service, and
Speaker 1: you would then click a box to allow it to happen.
Speaker 1: But since so much revenue depends intrinsically on the ability
Speaker 1: of companies to collect and share data, there's an extreme
Speaker 1: financial incentive to go the opt out route. More on
Speaker 1: that later. On the state level, presently, two states in
Speaker 1: the US have passed privacy laws meant to protect the
Speaker 1: private information of citizens of those states, and they are California,
Speaker 1: which passed the California Consumer Privacy Act in which went
Speaker 1: into effect in twenty twenty, and then Virginia, which very
Speaker 1: recently passed the Consumer Data Protection Act just this past
Speaker 1: March in but that law won't go into effect until January.
Speaker 1: The other forty eight states of the US pretty much
Speaker 1: just followed the general federal rules to some extent. So
Speaker 1: that's the legal background on privacy in the United States
Speaker 1: and to a lesser extent, the EU without going into
Speaker 1: like super detailed analysis. The idea being privacy is clearly
Speaker 1: a thing, but it's not as heavily protected from a
Speaker 1: legal standpoint in the United States as it could be. Meanwhile,
Speaker 1: obviously technology advances at an incredible pace and frequently leaves
Speaker 1: the legal system in the dust. But what about the
Speaker 1: actual collection of personal information in the tech age. Well,
Speaker 1: again we need to think back historically. Now, in the
Speaker 1: old old days, you know, pre digital age, businesses essentially
Speaker 1: kept an eye on customers, particularly repeat customers, and kept
Speaker 1: an eye on what they were buying. This was necessary
Speaker 1: in order to just keep stores stocked with the stuff
Speaker 1: people actually needed. And I think this kind of tracking,
Speaker 1: which is being really generous, uh, it was much more
Speaker 1: general approach. It's pretty easy to understand and to forgive.
Speaker 1: So imagine that you are a store owner and you
Speaker 1: notice that every two months farmer Betty comes in and
Speaker 1: she buys two bags of grain. You would learn pretty
Speaker 1: quickly that you need to make sure you have grain
Speaker 1: stocked every two months because typically that's when she would
Speaker 1: come in and buy them. So you want to make
Speaker 1: sure you had that on hand. And you would do
Speaker 1: this with all your customers, whatever it was that they
Speaker 1: were buying. You would make sure that you were stocked
Speaker 1: up on and you might also try and experiment and
Speaker 1: stock some stuff was related to the products that your
Speaker 1: regulars were buying, and assuming that you speculate correctly, everyone
Speaker 1: benefits from that. You make more sales and your customers
Speaker 1: end up getting stuff that they need, even if they
Speaker 1: didn't know they needed it at the time. Fast forward
Speaker 1: a whole lot to the point where we had electronic
Speaker 1: means of keeping inventory. The invention of stuff like computer
Speaker 1: systems and the bar code in the nineteen seventies that
Speaker 1: made it possible for us to keep an up to
Speaker 1: date electronic record of inventory and sales, and these weren't
Speaker 1: directly tied to customers just yet. That would still largely
Speaker 1: depend heavily on observation, but now it was much easier
Speaker 1: to spot buying trends and respond to them in close
Speaker 1: to real time. That particular branch would lead to data
Speaker 1: driven marketing, in which experts and marketing would look at
Speaker 1: various goods and services and use data to determine which
Speaker 1: regions they should focus on and which one's might prove
Speaker 1: to be less profitable. So let's say you are uh,
Speaker 1: the owner of a chain of grocery stores in the Southeast.
Speaker 1: You might notice that grocery stores in Atlanta are selling
Speaker 1: a lot of a particular type of product, and then meanwhile,
Speaker 1: a store in you know, Charlotte isn't selling that so much,
Speaker 1: but it is selling a different product at very high volume.
Speaker 1: These are the sort of dad trends you would want
Speaker 1: to know so that you could make sure you had
Speaker 1: the right stock on hand, you could do advertising campaigns,
Speaker 1: and you can maximize your sales and minimize your waste.
Speaker 1: It was incredibly valuable data that was undeniable. Information was
Speaker 1: the key to maximizing profit and reducing costs as much
Speaker 1: as possible. In the nineteen eighties we saw the rise
Speaker 1: of direct marketing, in which marketers would customize and personalized
Speaker 1: efforts and aim them at specific shoppers. Now we're no
Speaker 1: longer looking at regions, we're looking at individuals. And typically
Speaker 1: they did this through direct mail sales. And this was
Speaker 1: a pretty primitive approach and based solely on the customer's
Speaker 1: past purchases. So I can give you an example of this.
Speaker 1: I grew up in the eighties. I was one of
Speaker 1: those kids who occasionally would buy comic books, and of
Speaker 1: course stuff on the backs of comic books would sometimes
Speaker 1: be really tempting, Like man I really would like that
Speaker 1: hand buzzer. That seems like that will be a real hit,
Speaker 1: And you go and you send your like dollar seventy
Speaker 1: five or the mail and you buy one. And then
Speaker 1: next thing you know, you start getting catalogs for all
Speaker 1: these sort of novelty gifts. And that's how I ended
Speaker 1: up on a billion mailing lists that were all aiming
Speaker 1: at me in different ways for different types of weird
Speaker 1: or novelty type stuff. That was kind of the approach.
Speaker 1: It was pretty primitive. It was not, you know, super sophisticated,
Speaker 1: but it did set a foundation that particular branch would
Speaker 1: later extend further into st like loyalty programs in which
Speaker 1: stores would issue cards or tokens, often using a bar
Speaker 1: code right that they would scan, and that would link
Speaker 1: purchases to specific customers. Now you actually know who it
Speaker 1: is that's buying stuff and how frequently they're buying it,
Speaker 1: and when linked to other information such as a person's
Speaker 1: email address or their snail mail address, that can allow
Speaker 1: stores to proactively reach out to a customer and alert
Speaker 1: them of sales, maybe offer up coupons, all in an
Speaker 1: effort to sell more stuff. And it gave the stores
Speaker 1: way more information about the preferences of their customers on
Speaker 1: that individual basis. That's sort of a microcosm of what
Speaker 1: we're looking at with personal data on the Internet. I'll
Speaker 1: explain more after this short break. Okay, we have gotten
Speaker 1: up to the ninety nineties and the birth of the
Speaker 1: World Wide Web. Now, the original purpose of the web
Speaker 1: was to create a collection of documents that could be
Speaker 1: linked to one another using hypertext links. So it was
Speaker 1: just a means of sharing information and linking information together
Speaker 1: which could allow you to create a type of contextualization.
Speaker 1: So think of the average experience you might have on
Speaker 1: a site like Wikipedia. Sure you might start off reading
Speaker 1: about sloths, but then through a series of clicking on
Speaker 1: various links in different articles, you ultimately end up reading
Speaker 1: about the communist revolution in Cuba. It didn't take too
Speaker 1: long after the initial launch of the earliest web pages
Speaker 1: for commerce to follow onto the web. In the digital
Speaker 1: magazine hot Wired introduced something new, the banner ad. Hot
Speaker 1: Wired was an online branch of the print magazine Wired.
Speaker 1: Now hot Wired doesn't exist anymore, but Wired now occupies
Speaker 1: both print and digital formats. However, the banner ad became
Speaker 1: a really important stepping stone in our story. The first
Speaker 1: banner ad was for a T and T, which reportedly
Speaker 1: paid hot Wire a fee of thirty dollars so that
Speaker 1: the banner ad would be placed at the top of
Speaker 1: hot Wired pages for the duration of three months during
Speaker 1: that time, according to one source, at least I could
Speaker 1: not verify this. It's widely reported, but I feel like
Speaker 1: they're all pulling it from the same source, So take
Speaker 1: this with a grain of salt. But apparently that banner
Speaker 1: ad enjoyed a click through rate of forty so quick aside,
Speaker 1: just in case you're not familiar with online ad terms,
Speaker 1: click through is what it sounds like. It's how many
Speaker 1: people actively clicked on an ad, which would then link
Speaker 1: the person to some other page. It would send them
Speaker 1: to a page that might have a little more information
Speaker 1: about a specific service or product, and frequently it would
Speaker 1: also include some means of signing up or purchasing that
Speaker 1: service or product. So if you're an advertiser, you want
Speaker 1: a pretty decent click through rate because one, it shows
Speaker 1: your ad was effective, and too, it makes your client
Speaker 1: happy because presumably they're going to get more sales, and
Speaker 1: click through is indescribably effective. It is it's insane when
Speaker 1: nearly half of all the people visiting a web page
Speaker 1: are clicking on an AD that's on that page. That's incredible.
Speaker 1: These days, the average click through on display ads is
Speaker 1: somewhere in the neighborhood of point three five per cent,
Speaker 1: so less than half a percentage point. Banner ads, by
Speaker 1: the way, get even less, sometimes as low as point
Speaker 1: zero five percent click through. So yeah, was unthinkably successful.
Speaker 1: It probably said a lot of very unrealistic expectations, if
Speaker 1: I'm being honest. But it was also a brand new thing.
Speaker 1: People had yet to develop ad blindness to banner ads, right.
Speaker 1: They They hadn't sort of trained themselves to just ignore
Speaker 1: everything that's at the top or the right of the
Speaker 1: page or sometimes the bottom. They were looking at everything.
Speaker 1: And also ad blockers were not yet a thing, so
Speaker 1: it wasn't like people were using means to prevent ads
Speaker 1: from showing up in the first place. Now, in those
Speaker 1: early days, the general thought was that a conversion, that is,
Speaker 1: converting someone from viewing an AD to acting on it,
Speaker 1: was pretty much limited to sales. So, in other words,
Speaker 1: people thought of ads as only being successful if someone
Speaker 1: was actively buying stuff through interacting with that ad. But
Speaker 1: pretty early on that attitude began to change because there
Speaker 1: were other aspects of conversion to consider. Clicking on the
Speaker 1: ad showed interest, and interest alone could be a conversion.
Speaker 1: It might mean that the company that was in charge
Speaker 1: of of uh, whatever projects our service the ad was
Speaker 1: linked to, might have to do some extra work, but
Speaker 1: you have at least identified a a prospect. Downloading a
Speaker 1: coupon was another type of conversion, and companies began to
Speaker 1: have a way to track data trends through online interactions,
Speaker 1: at least to how well their ads were kind of doing.
Speaker 1: At the same time, a developer named Lou Montoli created
Speaker 1: a new type of computer file that would transform the
Speaker 1: experience of using the World Wide Web. These files, called cookies,
Speaker 1: are integral to how we experience the web. The cookies
Speaker 1: keep track of which websites we visit, how frequently we
Speaker 1: visit them, and what we do on those sites, including
Speaker 1: stuff like if we make a purchase or if we
Speaker 1: click through an ad. They allow us to do stuff
Speaker 1: like log into a service online, like you know, put
Speaker 1: in your user name and password, and then you can
Speaker 1: stay logged in even if you navigate away from the
Speaker 1: site and you come back to it later, you're still
Speaker 1: lugged in. Well, that's thanks to cookies. That way, when
Speaker 1: we come back, we're already lugged in. We don't have
Speaker 1: to go through that process again unless you're using something
Speaker 1: that has really high security, in which case you would
Speaker 1: have to do it because the security is the most
Speaker 1: important part. Similarly, if you're using a site that allows
Speaker 1: you to set certain preferences, the cookie file on your
Speaker 1: computer tells that site what those preferences are, so that
Speaker 1: when you return, those preferences are already in place for
Speaker 1: you automatically. It creates a level of convenience that makes
Speaker 1: the web more usable. Now, when you visit a site,
Speaker 1: the site can request the information stored in that cookie file.
Speaker 1: It has to because if the site needs to adjust
Speaker 1: things for you, it has to know what to do right.
Speaker 1: And this is where we start to get to a
Speaker 1: point where personal information becomes a hot commodity online. The cookie,
Speaker 1: which had clear benefits for users, would have even more
Speaker 1: significant benefits for businesses online. So let's switch back to
Speaker 1: the ads side of the story. At first, companies would
Speaker 1: follow a T and T S lead and purchase banner
Speaker 1: space or right rail space on a website for a
Speaker 1: set amount of money for a set amount of time.
Speaker 1: But it didn't take long for that to change. In
Speaker 1: Netscape and info seek migrated to a new pricing model.
Speaker 1: Instead of creating a one size fits a few approach
Speaker 1: to selling web page landscape, which meant companies would have
Speaker 1: to pay the same amount whether their ads were working
Speaker 1: on that page or not, and for you know, whatever
Speaker 1: duration they had picked. The new approach was the good
Speaker 1: old CPM. CPM stands for cost per milay, with milla
Speaker 1: being the Roman word for thousand. So it sounds at
Speaker 1: first like you're saying cost per million, but you're really
Speaker 1: saying cost per thousand. So the thousand in this case
Speaker 1: tends to mean impressions. That is the number of times
Speaker 1: the ad is presumably seen by visitors to that particular website.
Speaker 1: So what this really breaks down to is that web
Speaker 1: pages that are really popular and they get lots of
Speaker 1: visitors can demand a higher CPM because more folks go there,
Speaker 1: So ads that are placed there are going to have
Speaker 1: higher visibility than an ad placed on you know, old
Speaker 1: Joe Bob's Duct Tape Museum website. A site that gets
Speaker 1: a lot of traffic can demand more money per thousand impressions,
Speaker 1: kind of like how in the United States, if you
Speaker 1: want to have a commercial played during the Super Bowl,
Speaker 1: it's gonna cost you millions of dollars compared to, you know,
Speaker 1: putting an ad on some niche television channel for late
Speaker 1: night TV. On the flip side, for advertisers, they can
Speaker 1: negotiate a rate with websites for a certain number of impressions,
Speaker 1: which effectively replaced the duration limit for an ad. So
Speaker 1: instead of saying I want an ad running on this
Speaker 1: page for three months, you would say, all right, the
Speaker 1: web page has a CPM rate of ten dollars, meaning
Speaker 1: that you have to pay ten dollars for every one
Speaker 1: thousand views, and you might negotiate for a million impressions,
Speaker 1: which would mean that the advertiser would have to pay
Speaker 1: the website ten thousand dollars to carry that ad in
Speaker 1: order to generate a million impressions. And if the page
Speaker 1: got a million impressions in a couple of days, boom,
Speaker 1: that ad campaign was done. If it takes weeks, well,
Speaker 1: then the campaign would last longer. And obviously that CPM
Speaker 1: was different depending on the popularity of the website. Website
Speaker 1: that's not that popular would have a low CPM, and
Speaker 1: it would also take a longer time to reach whatever
Speaker 1: the agreed upon number of impressions was. By the way,
Speaker 1: this is also why there are a lot of websites
Speaker 1: that have things like quizzes and galleries where you have
Speaker 1: to scroll through each item. Like any website where it's
Speaker 1: top ten movies that feature ghosts that have hair in
Speaker 1: front of their face, and every single tree is its
Speaker 1: own web page. That's because every one of those web
Speaker 1: pages you go to, that's another impression. So it's a
Speaker 1: way of expanding the number of impressions and AD would
Speaker 1: get by making you have to reload the page over
Speaker 1: and over and over again. If all ten of those
Speaker 1: things were on one page, you would get one impression
Speaker 1: for that article. These things, by the way, also have
Speaker 1: massive drop off rates, like if they're not really compelling,
Speaker 1: people will bail on them within like two or three entries,
Speaker 1: so there's a diminishing returns thing going on with them.
Speaker 1: That's just some insight into how web pages generate revenue.
Speaker 1: I've been on that side, and it is not always
Speaker 1: fun anyway. A big part of all this is that
Speaker 1: the ad campaign wasn't tied to other performance metrics, right,
Speaker 1: So it wasn't whether or not people click through the
Speaker 1: ad or whether they actually made a purchase through the ad.
Speaker 1: This was just about how many people actually were exposed
Speaker 1: to the ad itself. The ad had to do the
Speaker 1: rest of the work. Then you had the emergence of
Speaker 1: double Click, that company which is now owned by Google.
Speaker 1: It was actually the focus of a big antitrust lawsuit
Speaker 1: that I'm not going to get into, but it was
Speaker 1: a big deal anyway, and let companies know which of
Speaker 1: their ads were most effective. So double click would give
Speaker 1: feedback to companies about which ads got the most impressions
Speaker 1: and click throughs, and those companies could then get a
Speaker 1: better idea of where they needed to spend their digital
Speaker 1: marketing dollars. Double clicks relationship with advertisers meant that there
Speaker 1: was a lot of rapid innovation in the web marketing
Speaker 1: space as companies began to hone in on what strategies
Speaker 1: worked and which ones didn't work. From there, you add
Speaker 1: all sorts of changes in the space. Some ads moved
Speaker 1: to pay per click models, so that was kind of
Speaker 1: going back to that conversion approach, where in this model
Speaker 1: and advertiser would only pay a website for the number
Speaker 1: of clicks that an ad received. That created an incentive
Speaker 1: for the website operators to try and make sure they
Speaker 1: were pairing ads with pages that would potentially drive the
Speaker 1: most traffic. So if you had a web page about
Speaker 1: I don't know, chainsaws, you probably wouldn't try and pair
Speaker 1: that page with an ad for perfume. Now I'm not
Speaker 1: saying there's no crossover between people who are interested in
Speaker 1: chainsaws and those who are interested in perfume, but from
Speaker 1: a marketing standpoint, you're probably not going to get the
Speaker 1: view that is the best use of your resources. And
Speaker 1: another big change around this time was to how people
Speaker 1: were accessing information on the web in general. While it
Speaker 1: might be theoretically possible to navigate the webs simply by
Speaker 1: following various hypertext links to get from point A to
Speaker 1: point B, to actually do it would be monumentally inefficient.
Speaker 1: I mean, you might have to pass through hundreds or
Speaker 1: thousands of sites to get from A to B. If
Speaker 1: you're limiting yourself to just following links that are on
Speaker 1: the page of A and trying to get to be
Speaker 1: that way, this can be a fun game by the way,
Speaker 1: a kind of seven degrees of separation kind of game,
Speaker 1: but it's not an efficient way to navigate the web.
Speaker 1: So Internet search engines were way more useful. You would
Speaker 1: put in your query in the search bar and boom,
Speaker 1: you got results that and, in theory at least best
Speaker 1: match whatever it was you're looking for. But this meant
Speaker 1: that search engines were incredible aggregators for user behavior. Not
Speaker 1: only could search engines keep itally on which search terms
Speaker 1: were the most popular at any given time, they could
Speaker 1: also consult those cookie files on users computers and see
Speaker 1: what other sites users have been visiting, and search engines
Speaker 1: could sell ads to. In fact, search engines made a
Speaker 1: subtle shift from being all about indexing the web and
Speaker 1: became more about monetizing search and getting into the data
Speaker 1: collection and advertising businesses. That's what happened to Google. I
Speaker 1: mean years ago you might call a you know, Google,
Speaker 1: a search company. Uh this was before the days of
Speaker 1: tons of other Google products emerged, like Google Cloud and
Speaker 1: Android and all that stuff. But at its heart, what
Speaker 1: Google really was wasn't a search engine. It was an
Speaker 1: advertising company. Companies could pay Google to have their sites
Speaker 1: pop up in searches as you know, results in a
Speaker 1: search result, they would be ads, they would be clearly
Speaker 1: marked his ads, but they would be advertised spots. And
Speaker 1: it gave those companies way more visibility than they might
Speaker 1: otherwise have. And Google can target specific users with ads
Speaker 1: that might appeal to them through a collection and analysis
Speaker 1: of all that personal data, both from the users cookies
Speaker 1: and their own searches history, and and if that person
Speaker 1: happens to be using Chrome or an Android device, well
Speaker 1: that's another kettle of fish entirely. So things took a
Speaker 1: massive downturn shortly after search engines began to dominate the
Speaker 1: data collection space, and that's because of the dot com
Speaker 1: bubble bursting in two thousand, two thousand one, and the
Speaker 1: world slid into an economic recession in general that particularly
Speaker 1: hit the online world hard. That was further exacerbated by
Speaker 1: the terrorist attacks on the United States on September eleven,
Speaker 1: two thousand one. But the industry did continue. There were
Speaker 1: just fewer players. Some of the bigger companies were able
Speaker 1: to survive all that turmoil, and the fact that the
Speaker 1: smaller competitors were largely wiped out meant that these companies.
Speaker 1: So companies like Google and Amazon now had an even
Speaker 1: more dominant position in the online world, so it would
Speaker 1: be very hard to overtake those companies, and both Google
Speaker 1: and Amazon are famous for jealously guarding their dominant positions.
Speaker 1: Move forward a few more years and you get the
Speaker 1: rise of social network platforms. My Space was one of
Speaker 1: the first really big social networks. It launched in two
Speaker 1: thousand three, but Facebook soon followed in two thousand four.
Speaker 1: My Space would be the most popular social network until
Speaker 1: about two thousand eight. That's when Facebook overtook it. But
Speaker 1: Facebook also introduced Facebook Ads in two thousand seven. Facebook
Speaker 1: offered even more data points about people than search engines could.
Speaker 1: I mean, people use social networks to connect with friends
Speaker 1: and to share stuff about themselves and the people they like.
Speaker 1: So people were willingly giving up tons of information that
Speaker 1: an advertiser might find extremely relevant. And so Facebook's business
Speaker 1: model largely fell into the realm of collecting and analyzing
Speaker 1: information about users, both from their activities on the platform
Speaker 1: itself and through the consultation of cookies, and Facebook could
Speaker 1: use that information to place highly relevant ads on specific
Speaker 1: user pages. This became the absolute foundation of Facebook strategy
Speaker 1: for the desktop experience, and how they generate revenue, and
Speaker 1: the value proposition Facebook has for advertisers is incredible. They
Speaker 1: can say, Hey, practically everyone in the world is on
Speaker 1: our platform, and we know what they all like and
Speaker 1: what they dislike because of cookies and their activities on Facebook. Plus,
Speaker 1: we've developed algorithms that keep people on Facebook longer. So
Speaker 1: if you advertise on us, we can make sure that
Speaker 1: the people who are most likely to respond to your
Speaker 1: ad are the people who see that ad, and we
Speaker 1: can make sure that they see your ad a lot.
Speaker 1: This also began to introduce the era of read targeting.
Speaker 1: So if you've ever had the experience of going to
Speaker 1: different websites but seeing the same ads play on those websites,
Speaker 1: you've been experiencing red targeting. Maybe you were doing some
Speaker 1: comparison shopping for I don't know how, with a brand
Speaker 1: new toaster, but for whatever reason, you didn't pull the trigger.
Speaker 1: Maybe you went as far as looking at a specific
Speaker 1: toasters page on a shopping site like Amazon, but you
Speaker 1: didn't move forward with the purchase. But now suddenly everywhere
Speaker 1: you go you seem to be seeing ads for that toaster,
Speaker 1: or maybe it's a different but similar toaster. This is retargeting.
Speaker 1: The cookies on your computer have a record of you
Speaker 1: visiting that toaster page, and they also include the fact
Speaker 1: that you didn't actually purchase the toaster when you went
Speaker 1: to that page. Those cookies allow various websites that have
Speaker 1: deals with ad companies that are working with this toaster
Speaker 1: manufacturer to dynamically insert ads for that toaster on all
Speaker 1: the various sites that you go to with the goal
Speaker 1: of convincing you to finally follow through on your purchase
Speaker 1: and buy that dang toaster. All right, we are still
Speaker 1: only just approaching the surface level of water from the
Speaker 1: tip of the iceberg. The really valuable stuff is below
Speaker 1: the surface, and we have Apple to thank for it.
Speaker 1: I'll explain more when we get back. On June seven,
Speaker 1: Apple launched the iPhone. While other smartphones predated the iPhone,
Speaker 1: it's safe to say that the iPhone was the first
Speaker 1: truly successful consumer smartphone that appealed to the mainstream market. Previously,
Speaker 1: smartphones pretty much just targeted geeks and executives. Now everybody
Speaker 1: wanted one. The smartphone would open up brand new opportunities
Speaker 1: for data collection. In two thousand eight, Apple launched the
Speaker 1: first iPhone to include a GPS chip. This allowed for
Speaker 1: really useful features for the users, such as real time
Speaker 1: maps that can give you an accurate view of your
Speaker 1: current location. That was huge, right, enormous benefit, But it
Speaker 1: also meant that along with all the data that companies
Speaker 1: could access thanks to cookies and social media posts and
Speaker 1: search engine activity, they can now also add location data
Speaker 1: to the mix as well. Now companies can know what
Speaker 1: you were doing online and where you were in the
Speaker 1: actual world. Now, to be clear, companies could do that
Speaker 1: for folks who were accessing the Internet on desktops or
Speaker 1: laptops as well. It's just that we don't tend to
Speaker 1: carry desktops around with us at all, and for those
Speaker 1: of us who do use laptops, we don't have them
Speaker 1: on an active all the time. But a smartphone that's different.
Speaker 1: That's a device that can ping back to home base
Speaker 1: several times a day, sometimes more than a hundred times
Speaker 1: a day, and that pain can include stuff like how
Speaker 1: much screen time you've spent on the device that day,
Speaker 1: what apps you've been using, what sites and services you've accessed,
Speaker 1: and where in the world you happen to be. And again,
Speaker 1: this allows companies to target more specific ads your way,
Speaker 1: and now those ads could be location based as well
Speaker 1: as activity based. So maybe you're wandering around a new
Speaker 1: city and you start seeing ads for specific locations like
Speaker 1: restaurants or shops or amusement parks or whatever. On the
Speaker 1: one hand, that could be really useful as you try
Speaker 1: to find things that you might want to experience in
Speaker 1: a new place. But on the other it indicated that
Speaker 1: the smartphone was really gathering a ton of information about you.
Speaker 1: And then there's that scenario I mentioned at the top
Speaker 1: of this episode. If you hang out with other folks
Speaker 1: and everyone happens to have a smartphone, everyone is generating data,
Speaker 1: whether they're actively using their phones or not. And part
Speaker 1: of that data isn't just what they're doing or where
Speaker 1: they are, but also who there with. And now our
Speaker 1: relationships with one another, the time we spend with each other,
Speaker 1: and the places where we spend it, that all becomes
Speaker 1: part of the data grab as well. It represents another
Speaker 1: way that companies can leverage and exploit the information we generate.
Speaker 1: One of the industries that grew out of all of
Speaker 1: this was the data brokerage industry. These are companies that
Speaker 1: collect and maintain massive data repositories about well about us.
Speaker 1: These companies buy and sell personal information as if it
Speaker 1: were any other commodity, because for a lot of entities
Speaker 1: out there, that's exactly what our personal information is. So
Speaker 1: even for companies that might not have the means to
Speaker 1: collect your personal data directly through their own services, can
Speaker 1: pay to get hold of those sweet ones and zeros
Speaker 1: through using data brokers. The U. S State of Vermont
Speaker 1: passed a law a couple of years ago that mandated
Speaker 1: that any company that bought or sold third party personal
Speaker 1: data had to register with the Secretary of State. As
Speaker 1: a result, one hundred twenty one companies registered with the
Speaker 1: Vermont state government. The companies didn't have to provide information
Speaker 1: about who was in their databases. They didn't have to
Speaker 1: say how many people were in them. The rules didn't
Speaker 1: require that these companies make available any information about consumers
Speaker 1: to those consumers, which means if you wanted to check
Speaker 1: to see how much dirt any of those companies might
Speaker 1: have on you, and you, you know, lived in Vermont,
Speaker 1: well you would kind of still be out of luck
Speaker 1: because the law didn't go that far. The law did
Speaker 1: require that the companies had to inform the government about
Speaker 1: any kind of opt out features that the companies provided,
Speaker 1: but that only assumed that they actually were providing an
Speaker 1: opt out feature for the average consumer. What this means
Speaker 1: is that there are more than one companies trafficking and
Speaker 1: personal data, and yours could be among them, and to
Speaker 1: opt out of that system, you would have to contact
Speaker 1: each and every one of these data brokers and go
Speaker 1: through whatever process they might have in order to opt out,
Speaker 1: because by default we are all opted into that system.
Speaker 1: In some cases, we did have a choice, in the
Speaker 1: sense that the choice was whether or not we wanted
Speaker 1: to use a specific service or platform or visit a
Speaker 1: specific website. Again, this is frequently where those long user
Speaker 1: agreements come in, the ones most of us skip right over,
Speaker 1: so that we just click on that I agree button
Speaker 1: and get on with it. We might not be aware
Speaker 1: that we just gave consent to have all of our
Speaker 1: data collected, but that's arguably on us if we didn't
Speaker 1: bother to read the terms and conditions. But in other cases,
Speaker 1: we might not ever have really had a chance to
Speaker 1: opt out of a specific data brokers collections at all
Speaker 1: because we never had direct contact with some of those
Speaker 1: data brokers. Because again information is bought, sold, and traded
Speaker 1: like crazy. So some of these companies are just buying
Speaker 1: up data that was collected by someone else and we
Speaker 1: only ever had contact with that initial point. So as
Speaker 1: an example, let's say that you sign up for a
Speaker 1: social networking platform. We'll call it space Look. So you
Speaker 1: sign up on space Look, and there's this long, boring
Speaker 1: passage of information that you've got to scroll through so
Speaker 1: that you can click the I Agree button, so you
Speaker 1: zoom past all the dull stuff so that you can
Speaker 1: finally get to uploading photos of your adorable kitty cat online.
Speaker 1: But in that dull passage, there are terms that explain
Speaker 1: that space Look will be collecting information about you and
Speaker 1: then using the information to serve you ads. And in addition,
Speaker 1: space Look might also sell or share your personal information
Speaker 1: with other third party entities. So you've effectively signed over
Speaker 1: your personal data to space Look for it to do
Speaker 1: whatever it wants with it within the confines of the
Speaker 1: agreement that you've clicked on, and your info might get
Speaker 1: sent to various data brokers that otherwise you have never
Speaker 1: heard of and never contacted. But wait, it gets worse. Recently,
Speaker 1: Facebook and Google have been in the News for putting
Speaker 1: up a bit of a fuss when it comes to
Speaker 1: the types of data collection that are available to them.
Speaker 1: Facebook got upset at Apple for a new change in
Speaker 1: privacy settings on iOS devices, and it requires Facebook to
Speaker 1: inform users about how it wants to collect data regarding
Speaker 1: user activity on those iOS devices. So like iPhones and
Speaker 1: you know, iPads, things like that, that activity includes the
Speaker 1: use of other apps on the device. So, in other words,
Speaker 1: Facebook collects information on users app activity even if that
Speaker 1: activity isn't directly involving Facebook itself. So if you do
Speaker 1: any banking on your phone, or shopping, or maybe you
Speaker 1: play certain mobile games, well, Facebook wants to know about
Speaker 1: all that because that data is valuable. Apples change requires
Speaker 1: Facebook to alert users that it wants to collect that data,
Speaker 1: kind of like this, this app wants to know your location.
Speaker 1: Is that okay? It's similar to that, And it gives
Speaker 1: the chance for users to opt out of that process
Speaker 1: right then and there in that alert. And Facebook hates
Speaker 1: that because if you give people the choice is to
Speaker 1: not be tracked, often they take that choice. They just
Speaker 1: you know, have to know about it first. So if
Speaker 1: you aren't allowed to bury that notice in page two
Speaker 1: of settings or in a deep user agreement, Well, then
Speaker 1: a lot of folks might just take the option to
Speaker 1: opt out, which means that's a hit on Facebook's revenue,
Speaker 1: and Facebook and a fan of that, it has launched
Speaker 1: a little bit of a campaign that essentially argues that
Speaker 1: Apple's new rules are harmful to small businesses and that
Speaker 1: people should feel badly about opting out, which is um,
Speaker 1: super disingenuous. If you ask me, Facebook, I don't think
Speaker 1: is at all concerned about small businesses except to the
Speaker 1: extent at which those small businesses spend money on Facebook. Similarly,
Speaker 1: Google was in the news when internal documents leaked showing
Speaker 1: that the company had leaned hard on Android device manufacturers
Speaker 1: to hide geo tracking opt out features deep in settings.
Speaker 1: And so Google was essentially saying, hey, that's cool that
Speaker 1: you want to make this Android smartphone, do us a
Speaker 1: solid for the geo tracking stuff. Hide that like on
Speaker 1: page two or three of your settings, so that nobody
Speaker 1: ever bothers to go that far. And the goal was
Speaker 1: just to make it harder for people to find where
Speaker 1: they could turn off geo tracking, so that the company
Speaker 1: could continue to collect that sweet data without too many
Speaker 1: people opting out dirty pool Google. Just a few years ago,
Speaker 1: all this data would have been alarming, but it also
Speaker 1: would have been kind of burdened by the fact that
Speaker 1: there's just so much information that's hard to do anything
Speaker 1: with it. So it's one thing to collect enormous amounts
Speaker 1: of personal information, but it's another to actually find a
Speaker 1: meaningful use for all that data. You get a lot
Speaker 1: of noise along with a little bit of signal. But
Speaker 1: over the past few years, data analysis has advanced dramatically
Speaker 1: and it's become much more sophisticated. Big data, which was
Speaker 1: a buzz term that came largely from the marketing world,
Speaker 1: is a real thing now, and when paired with systems
Speaker 1: that use strategies like machine learning, advertising companies are able
Speaker 1: to get incredibly detailed looks at who each of us
Speaker 1: happens to be. Our data can be parsed and contextualized
Speaker 1: in millions of ways that are incredibly valuable to countless
Speaker 1: people and organizations. Some of those might be largely benign,
Speaker 1: or at least no more malicious than your typical capitalistic endeavor,
Speaker 1: but some might be way more malevolent. And of course
Speaker 1: I haven't even touched on the burden of good stewardship
Speaker 1: when it comes to protecting data. Many of those one
Speaker 1: data broker companies have been targets of hackers, and more
Speaker 1: than a few have had some pretty nasty data breaches
Speaker 1: over the years. So I guess the whole point of
Speaker 1: this episode is to really explain how technology in the
Speaker 1: digital age largely centers around the collection and exploitation of information,
Speaker 1: and that a lot of that information comes from people
Speaker 1: like us, and that if we feel strongly about that,
Speaker 1: we have to take steps to address this issue. Unfortunately,
Speaker 1: right now, those steps are often laborious and convoluted. It's
Speaker 1: easy to get discouraged. It's easy to prioritize convenience over privacy.
Speaker 1: It's easy to give into the statement that Mark Zuckerberg
Speaker 1: famously made in two when he said privacy is dead.
Speaker 1: But as we see implementations of systems that exploit our data,
Speaker 1: and as these become undeniably more invasive, it might benefit
Speaker 1: us to look at them more closely and act in
Speaker 1: our own self interest, because I assure you most of
Speaker 1: these companies are not going to do that for us.
Speaker 1: I'm talking to you, Stephanie, yes, you. I've personalized this
Speaker 1: episode for every listener, and you, step phany need to
Speaker 1: take action. I'm kidding. I didn't personalize this podcast, and
Speaker 1: anyone not named Stephanie is probably just confused, and anyone
Speaker 1: who is named Stephanie is probably flipping out. But no,
Speaker 1: I just wrote that as a joke. But it is
Speaker 1: the sort of thing that websites and apps and other
Speaker 1: Internet related services can do for reals. In fact, technically,
Speaker 1: with enough work, a podcast like this could probably do
Speaker 1: it too. It would just require me to go through
Speaker 1: a very long list of names and record them and
Speaker 1: then have dynamic insertion of that statement in the podcast
Speaker 1: and targeted to specific listeners. It would be a lot
Speaker 1: of work, is what I'm saying, something that I am
Speaker 1: not willing to do, but it could be done, and
Speaker 1: maybe that's not always a good thing. All right. That
Speaker 1: wraps up this very long soapbox edition of tech Stuff.
Speaker 1: Hope you guys learned something in that and found some
Speaker 1: value in that discussion. I will be doing some more
Speaker 1: episodes about privacy related materials like Kappa. I do want
Speaker 1: to talk about that and the intent of that legislation
Speaker 1: as well as the actual impact of it, So look
Speaker 1: forward to that in the future. But If you have
Speaker 1: suggestions for things I should cover in future episodes of
Speaker 1: tech Stuff, reach out to me. The best place to
Speaker 1: do that is on Twitter. The handle for the show
Speaker 1: is tech Stuff H s W and I'll talk to
Speaker 1: you again really soon. Tech Stuff is an I Heart
Speaker 1: Radio production. For more podcasts from My Heart Radio, visit
Speaker 1: the I Heart Radio app, Apple Podcasts, or wherever you
Speaker 1: listen to your favorite shows.