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Speaker 1: Get in touch with technology with tech Stuff from how

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Speaker 1: stuff Works dot com. Hey there, and welcome to tex Stuff.

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Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer with

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Speaker 1: how Stuff Works and I love all things tech and

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Speaker 1: in our last episode, I talked about how web analytics

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Speaker 1: work in general and why they are important both for

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Speaker 1: people visiting a website and owners of websites and the

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Speaker 1: advertisers who support websites and the companies that advertise through

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Speaker 1: these advertisers. They really help website designers also get a

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Speaker 1: better understanding of how their users navigate and consume stuff

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Speaker 1: on their sites and allows the web administrators to tweak

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Speaker 1: things to make the experience better. So it's not just

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Speaker 1: about advertising. It's also about how can I make this

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Speaker 1: website easier to navigate, more intuitive, more interesting, more exciting

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Speaker 1: to use, or more useful or whatever the purpose of

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Speaker 1: the website is that benefits the visitor, makes the experience

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Speaker 1: more satisfying one, and it helps the website administrator also

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Speaker 1: monetize through web advertising. But now let's get to the

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Speaker 1: other side of the coin. Tracking information obviously brings with

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Speaker 1: it some very nasty potential problems like threats to privacy

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Speaker 1: and security. Information is incredibly valuable. It is the currency

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Speaker 1: of the Internet. You might thought it was bitcoin, it's not.

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Speaker 1: Data is your currency. And generally speaking, the more data

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Speaker 1: a company can get about people who are using the web,

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Speaker 1: the better it is for that company, not necessarily better

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Speaker 1: for the people, the better for that company. Knowing information

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Speaker 1: about a person means being able to sell to that

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Speaker 1: person more effectively, or it might mean being able to

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Speaker 1: exploit that person in less legal or ethical ways, and

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Speaker 1: so they out of gathered about users can become a

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Speaker 1: tool or a weapon, depending upon the type of information

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Speaker 1: gathered and the will of the person who has access

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Speaker 1: to that information. So ideally you don't have any bad

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Speaker 1: actors out there, and even if people are gathering a

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Speaker 1: lot of information about users, they're not trying to put

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Speaker 1: it to any malicious purpose. Before I dive into a

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Speaker 1: detailed account of web analytics and privacy, I should say

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Speaker 1: that not everyone is out to scrape every bit of

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Speaker 1: data off of users or to figure out the identity

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Speaker 1: of a specific user. Many analyzes are more focused on

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Speaker 1: identifying emerging trends rather than singling out one specific user,

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Speaker 1: So the goal is not to look at that data

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Speaker 1: like a browser's history, like looking at the cookie information

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Speaker 1: and saying, oh, this person went from X website to

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Speaker 1: HY website to Z website and then come to the

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Speaker 1: conclusion of that must be Jonathan Strickland instead. More often

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Speaker 1: than not, these analytics companies are looking at aggregated data

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Speaker 1: that is, at least on the service level, anonymous, and

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Speaker 1: the purpose is to see more valuable information, such as

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Speaker 1: rose Gold is so totally in right now, so put

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Speaker 1: all your rose Gold products on your main page because

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Speaker 1: people are gonna go nuts. Right This really dates this

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Speaker 1: podcast because I'm about about two years out of touch,

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Speaker 1: so it tells you this one should have come out

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Speaker 1: two years ago. Anyway, this concept makes sense when you're

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Speaker 1: thinking of big sweeping strategies, like which products you want

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Speaker 1: to feature on an online stores homepage, or which news

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Speaker 1: stories are likely to be thought of as the most

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Speaker 1: important and relevant on any given day. So you might

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Speaker 1: look at something like Google Trends and say, oh, well,

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Speaker 1: a lot of people are searching this particular term. Let's

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Speaker 1: create an article about this thing. We can inform people,

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Speaker 1: we can make sure it's a really good article, but

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Speaker 1: we can also take advantage of the fact that people

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Speaker 1: are interested in this idea right now, so it's kind

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Speaker 1: of a mutually beneficial experience in the ideal. But it

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Speaker 1: would be silly to say that no one's interested in

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Speaker 1: your individual preferences, because that's not true. There are people

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Speaker 1: who are very interested in your individual preferences. For one thing,

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Speaker 1: it can help identify what different groups of people like,

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Speaker 1: so a company could present those different groups with distinct

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Speaker 1: experiences that were meant to appeal to that group. Right.

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Speaker 1: That's targeted marketing or targeted advertising. So let me give

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Speaker 1: an example. Let's say I run an online store, and

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Speaker 1: I've coded my home page in such a way that

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Speaker 1: it can dynamically display different products based off the information

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Speaker 1: I glean from analyzing a user's behaviors. And my site

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Speaker 1: uses cookies and JavaScript, and those analyze the are and

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Speaker 1: it presents the most appropriate products for return visitors. So

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Speaker 1: when you pop into my store, I happen to know

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Speaker 1: that you recently started for Star Wars toys because the

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Speaker 1: cookie information that I've installed on your browser from your

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Speaker 1: previous visit has told me this, And so I have

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Speaker 1: some Star Wars related products that I want to prominently

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Speaker 1: show to you in my homepage. Now when I say

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Speaker 1: I want to, all of this is done automatically. You've

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Speaker 1: got all this meta information, these tags that computers can

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Speaker 1: use to sort through and select to present what appears

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Speaker 1: to be the most appropriate products that will appeal to

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Speaker 1: the visitor. Now, let's say your buddy shows up and

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Speaker 1: your buddy is not as into Star Wars as you are.

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Speaker 1: Your buddies like a big clover Field fan, and your

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Speaker 1: buddy visits my online store and see is a totally

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Speaker 1: different selection of products than you do when they pop on.

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Speaker 1: Maybe your buddy is visiting my store for the first time,

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Speaker 1: in which case I don't have any for any information

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Speaker 1: about him or her. I don't know anything about this

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Speaker 1: person because they've just come to my website for the

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Speaker 1: first time. Now, they come there and I decided to

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Speaker 1: pop a cookie on their web browser, so i'll know

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Speaker 1: the next time they come through. But this first time,

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Speaker 1: it's a blank slate. That means that my store is

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Speaker 1: probably gonna show them a pretty neutral selection of products.

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Speaker 1: Maybe there will be some of the most popular products

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Speaker 1: that happened to appeal to a broad spectrum of people,

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Speaker 1: but they aren't targeted toward that specific person yet. Because

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Speaker 1: I don't know what that person's preferences are. But as

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Speaker 1: your friend navigates through my site, I'm collecting more and

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Speaker 1: more information about what they like based upon their behaviors,

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Speaker 1: and then I can make sure the next time they

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Speaker 1: come to my website that it serves up a more

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Speaker 1: appropriate landing page for them based upon their preferences. Again,

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Speaker 1: and I say, I decide this is all automatic. Let's

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Speaker 1: go a step further. Let's say that you are running

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Speaker 1: a blog that has online advertising on it. So you've

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Speaker 1: got spaces on your blog that are reserved for advertising,

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Speaker 1: and the ads themselves are tracking users with cookies and JavaScript.

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Speaker 1: Most ads come from brokers who have numerous clients, right,

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Speaker 1: So let's say that you go to a blog and

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Speaker 1: you see an ad for a popular soft drink company.

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Speaker 1: That ad did not come directly from the soft drink company.

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Speaker 1: More likely than that it came through an advertising company

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Speaker 1: that has that soft drink company is one of its clients.

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Speaker 1: So the brokers, these companies that have thousands of clients

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Speaker 1: representing all these different industries, can use this tracking information

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Speaker 1: in cookies and JavaScript to determine what stuff you're most

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Speaker 1: likely to respond to based upon your browsing history, so

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Speaker 1: that means the broker could potentially serve up ads based

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Speaker 1: on the information to help improve the chances that you'll

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Speaker 1: find any given ad more useful and click on it.

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Speaker 1: In these cases, the experiences are personalized, but that personalization

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Speaker 1: still is not dependent upon your identity per se. I mean,

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Speaker 1: it's based upon what you like and what your behaviors

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Speaker 1: have indicated you find valuable or interesting. But it's not

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Speaker 1: like that specific data is identifiable stuff like your name

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Speaker 1: or your address or anything like that. Although they can

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Speaker 1: at least get an approximation of your address based upon

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Speaker 1: uh your IB address, so that that could at least

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Speaker 1: know generally where you were, um maybe more specifically if

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Speaker 1: you're happy to use a mobile device and you have

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Speaker 1: location tracking on, or as it turns out, you don't

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Speaker 1: necessarily have to have location tracking turned on. There was

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Speaker 1: a recent story from uh AP that looked into this

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Speaker 1: and said that Google Android devices would check in with

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Speaker 1: Google an average of fourteen times an hour, giving information

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Speaker 1: about location even with location services turned off. So that's

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Speaker 1: a kind of tracking information that definitely rubs people the

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Speaker 1: wrong way, very valuable information. If Google wants to serve

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Speaker 1: up ads to you. That's that are based on your

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Speaker 1: your locale, but not very comforting if you're thinking about

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Speaker 1: I'm just carrying my phone around. I don't need my

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Speaker 1: phone telling Google everywhere I'm going throughout the day. Now,

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Speaker 1: there are instances where a company, an agency, or a

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Speaker 1: government might want to identify someone based upon their browsing behavior.

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Speaker 1: For example, let's say that there's a crime that's been

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Speaker 1: committed and law enforcement has come into possession of a

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Speaker 1: computer that they believe belonged to the perpetrator of that crime,

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Speaker 1: but they still don't know who that perpetrator is. They've

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Speaker 1: got they've up the computer, his or her computer, but

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Speaker 1: they don't know who that person is yet, and there's

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Speaker 1: no overtly identifiable information on the computer's hard drive, no fingerprints,

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Speaker 1: that kind of thing. Would it be possible for an

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Speaker 1: investigator or an analyst to be able to figure out

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Speaker 1: the identity of the computer's owner just through that person's

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Speaker 1: browsing history. If you looked at the information of what

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Speaker 1: websites they went to, would you be able to figure

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Speaker 1: out who it was that owned that computer? Well, setting

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Speaker 1: aside the possibility that the perpetrator had remained signed into

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Speaker 1: any services that would link back to his or her identity.

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Speaker 1: The task would require the analysts to look at the

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Speaker 1: patterns of behaviors and the browser history to figure out

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Speaker 1: what had the person had that computer's keyboard been doing.

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Speaker 1: It's kind of scary to think about this, but this

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Speaker 1: is totally possible to do. It's built upon the same

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Speaker 1: principles that were used to support e commerce. Back in

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Speaker 1: two six there were some Russian analysts who proposed a

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Speaker 1: method of user profiling that would create profiles of users

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Speaker 1: based on their browser history. So you would get shoveled

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Speaker 1: into progressively smaller groups based on your behavior. So you know,

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Speaker 1: initial analysis might put you in one of several broad categories,

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Speaker 1: but the more specific behaviors you exhibit, the more specific

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Speaker 1: the groups could be that you would be sorted into,

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Speaker 1: and that would represent profiles. As word vectors, that's a

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Speaker 1: method to assign context to words that ties into natural

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Speaker 1: language processing. I did a couple episodes on those a

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Speaker 1: little while back. The researchers use those word vectors to

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Speaker 1: create clusters of topics in a hierarchy to determine or

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Speaker 1: determined by rather user behavior and the stuff that users valued.

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Speaker 1: More as demonstrated in their behavior by following links or

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Speaker 1: staying on certain pages for a longer time, or making

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Speaker 1: searches would occupy a higher place in that hierarchy, and

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Speaker 1: that was one way of identifying users, at least by interest.

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Speaker 1: Now again that didn't assign a name yet, but that

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Speaker 1: was a building block towards this. There's a two thousand

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Speaker 1: seven paper I read that described a different approach that

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Speaker 1: could predict a user's gender and age based on his

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Speaker 1: or her web browsing behavior. The researchers created a model

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Speaker 1: that relied on users reporting their age and their gender,

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Speaker 1: so it's a self reporting kind of thing, and they

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Speaker 1: would also give up access to their browsing history to

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Speaker 1: this model, and the model would learn the associate to

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Speaker 1: associate certain behaviors with respect to age and gender and

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Speaker 1: draw general conclusions based on that. And once it learned

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Speaker 1: through this training process, it could then analyze an unknown

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Speaker 1: users browser history and then predict that person's gender and age.

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Speaker 1: I don't know how accurate it was. I came across

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Speaker 1: this information all reading a totally different but related paper,

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Speaker 1: didn't have time to track down the two seven document.

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Speaker 1: By this does lead to the way law enforcement might

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Speaker 1: use user profiling to identify someone based on their browser behavior.

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Speaker 1: I'll explain more in just a second, but first let's

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Speaker 1: take a quick break to thank our sponsor. Before the break,

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Speaker 1: I mentioned a paper that related paper was specifically about

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Speaker 1: identifying a suspect based on their web behavior and it

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Speaker 1: has the title Web user profiling based on Browsing Behavior Analysis.

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Speaker 1: And in that paper, the researchers describe a method in

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Speaker 1: which a computer believed to belong to a suspect is

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Speaker 1: compared to other computers that have known users. So law

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Speaker 1: enforcement gets hold of a computer, they know that this

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Speaker 1: computer was used by the perpetrator of a crime. They

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Speaker 1: don't have an identity yet, they do have some suspects.

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Speaker 1: They don't know if any of the suspects actually were

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Speaker 1: the perpetrator. So the goal is to take this target computer,

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Speaker 1: the one that was involved with the actual perpetrator, with

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Speaker 1: candidate computers the ones that suspects are using, and factors

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Speaker 1: such as the specific sites that were visited, the time

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Speaker 1: spent on every site, the order that the user would

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Speaker 1: browse the sites. All of these things are taken into consideration,

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Speaker 1: and at the heart of the matter is the idea

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Speaker 1: that we humans tend to be creatures of habit. So

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Speaker 1: here's how it would work. Investigators take that target computer

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Speaker 1: and they perform a data extraction on the computer. They

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Speaker 1: pull all the information they can off of it to

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Speaker 1: get a lead on the identity, and includes the browser

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Speaker 1: history and browser behaviors, and they analyze this. They have

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Speaker 1: identified some suspects and those suspects may be using other

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Speaker 1: computer s access online services, and those are the candidate computers.

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Speaker 1: So law enforcement gets possession of those candidate computers, presumably

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Speaker 1: through a warrant, and they preserve they do the same

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Speaker 1: sort of thing. They do a data extraction on each

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Speaker 1: of those computers. Then they process all that information and

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Speaker 1: they analyze it, and investigators determine which factors are domains

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Speaker 1: of interest, like what what are the things in the

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Speaker 1: target computer that could potentially be identify irs for somebody,

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Speaker 1: and they break this down into a vector representation. They

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Speaker 1: wait each of the factors to assign each one in

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Speaker 1: relative importance. So, for example, awaiting might represent that the

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Speaker 1: activity on the target computer showed the perpetrator repeatedly visited

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Speaker 1: the same five websites, so those websites would be weighted

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Speaker 1: heavier than others because the perpetrator had gone to them

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Speaker 1: multiple times, and it might within those five websites, each

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Speaker 1: of those websites might have their own weighting that is

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Speaker 1: based upon the amount of time spent on those sites

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Speaker 1: and the number of times that the perpetrator had logged

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Speaker 1: into them that are recorded in that browser history. These

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Speaker 1: indicate trends and behaviors. Then you would compare that with

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Speaker 1: the information you found from the candidate computers, and if

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Speaker 1: you found one that demonstrated a similar browsing behavior as

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Speaker 1: the one that was on the target computer, you can

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Speaker 1: make an argument that the respective suspect may well be

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Speaker 1: your criminal, then you can consider them a lead. It's

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Speaker 1: not exactly a smoking gun, but it's certainly says this

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Speaker 1: person browses on the Internet exactly the same way as

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Speaker 1: the person who owned this computer, and we know the

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Speaker 1: person who owned this computer committed the crime, and it

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Speaker 1: can lead you into a more specific investigation. In two

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Speaker 1: thousand and seventeen, Gizmoto ran a piece titled Here's all

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Speaker 1: the data collected from you as you browse the Web,

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Speaker 1: and it was written by David Neild and I really

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Speaker 1: recommend checking out this article. Again, it's called here's all

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Speaker 1: the data collected from you as you browse the web.

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Speaker 1: It's great piece. I'm gonna kind of go over it

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Speaker 1: here a little bit. Neil points out the type of

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Speaker 1: data your computer can share with sites on the Internet,

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Speaker 1: and as he mentions, it can include all of the following.

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Speaker 1: Your IP address. Now that makes sense. The IP address

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Speaker 1: corresponds to your computer or your router UH or a router.

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Speaker 1: It's necessary so that a site knows where to send

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Speaker 1: the data that you've requested. So if you visit a

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Speaker 1: website your typically you're technically sending a request to a

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Speaker 1: web server. The server has to know where to send

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Speaker 1: that site otherwise you'll never get anything back. But an

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Speaker 1: IP address can provide information that gives the site owners

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Speaker 1: a general idea of your location, not specifically where you are,

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Speaker 1: but generally where you are. Then there's the type of

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Speaker 1: system you're using, such as whether or not you're on

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Speaker 1: a phone or a tablet, or a computer or a

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Speaker 1: gaming console. UH. This is what will also typically include

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Speaker 1: information like the operating system that you're using, the display

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Speaker 1: resolution on the device you have, what processors your machine

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Speaker 1: might have like CPU and GPU, and the specific types

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Speaker 1: like how many cores that how much processing power that

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Speaker 1: kind of stuff, Which browser you might be using, what

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Speaker 1: plugins you have installed in that browser, your devices battery

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Speaker 1: charge could be part of the information. All of that

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Speaker 1: is part of the information that that your machine is

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Speaker 1: handing over. In this exchange, Neild also mentions the web

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Speaker 1: page that will let you know all the data your

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Speaker 1: browser since two pages. By default, that site is called

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Speaker 1: web k dot robin linus dot com or linus if

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Speaker 1: you prefer, it's w E B k A Y dot

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Speaker 1: R O b I n l I n us dot com.

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Speaker 1: So I went ahead and checked it out just to

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Speaker 1: see what would say about my connection here at work.

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Speaker 1: So it knew my work computer is running when seven, yeah,

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Speaker 1: I know. It also knew that I was using Chrome

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Speaker 1: as my browser. It identified the GPU and the CPU

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Speaker 1: for my computer. It knew what resolution I had set

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Speaker 1: my screen. It knew my laptops battery was at a

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Speaker 1: charge because it was plugged into a docking station at

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Speaker 1: the time. It identified the I s B my office uses.

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Speaker 1: It identified the download speed I had available to me.

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Speaker 1: It estimated my location. It was off by a couple

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Speaker 1: of blocks, but it was in the general area. It

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Speaker 1: identified which social media accounts I was logged into at

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Speaker 1: that time. If it had been a mobile device, um,

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Speaker 1: it would have also told me about my devices orientation,

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Speaker 1: like whether it was in portrait or landscape mode, and

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Speaker 1: more information like that. And then yield linked to another

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Speaker 1: site called click that one can monitor mouse movements and

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Speaker 1: mouse clicks and how active you are with a site.

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Speaker 1: I visited this one too, and it was kind of creepy.

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Speaker 1: It's just find in a way to actually reveal to

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Speaker 1: you how much information is being sent to a website.

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Speaker 1: So there's actually a voice that talks to you, prerecorded

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Speaker 1: stuff that's meant to be a little unsettling, and it

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Speaker 1: sends you information telling you, oh, you just move the

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Speaker 1: mouse to the right, you just moved it to the left,

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Speaker 1: You've sat still for thirty seconds, You've been viewing this

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Speaker 1: page for a minute. So this is all information that

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Speaker 1: could be sent to a site like they could actually

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Speaker 1: monitor where is your mouse moving across a web page,

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Speaker 1: which again gets a little creepy. Right now, there are

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Speaker 1: legitimate uses for that kind of information from a website

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Speaker 1: design perspective, it could tell you a lot about the

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Speaker 1: sort of things users find attractive or interesting. About your website,

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Speaker 1: but there are also potential misuses and legit analytics firms

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Speaker 1: won't use information to compromise users privacy, but not everyone's legit.

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Speaker 1: Here's another example. Let's say that you are in a

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Speaker 1: faery person. Actually, I'm not gonna say that you're a

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Speaker 1: nice person, you're not nefarious. Let's say there is a

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Speaker 1: nefarious person out there, and this nefarious person has installed

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Speaker 1: some rogue JavaScript on a website, then has tricked people

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Speaker 1: into going to it, and is able to give certain

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Speaker 1: bits of information that appear to include compromising information about

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Speaker 1: the user, and they're able to contact the user to

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Speaker 1: send a message out to that users perhaps their email

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Speaker 1: address or something on those lines, and through this method

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Speaker 1: of contact, they are trying to blackmail the users, saying

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Speaker 1: I have dirt on you because I know that you've

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Speaker 1: visited such and such website. Maybe it's an adult content website,

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Speaker 1: maybe it's a website that's about a sensitive subject. And

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Speaker 1: they're able to tell this from the cookies or the JavaScript,

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Speaker 1: and so they're sending a message that's essentially saying, if

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Speaker 1: you don't cooperate with me, I'm going to reveal the

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Speaker 1: information I have about you, Now that may not be

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Speaker 1: that they have any real information about you, anything that's

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Speaker 1: of any real damaging worth. But they're trading on people's

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Speaker 1: natural fears and and they know that even if not

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Speaker 1: of their attacks are going to be successful, at least

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Speaker 1: enough of them will be for it to be worthwhile.

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Speaker 1: So that's one way someone might make nefarious use of

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Speaker 1: this kind of data. I'll talk a little bit about

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Speaker 1: some ways that governments and companies and individuals have tried

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Speaker 1: to protect themselves and others from this kind of abuse

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Speaker 1: in just a second, but first let's take another quick

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Speaker 1: break to thank our sponsor. Now, there are some laws

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Speaker 1: in place that help protect people from predatory use of

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Speaker 1: their data. In the United States gets a little loosey goosey.

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Speaker 1: There's some state level laws in some places, but obviously

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Speaker 1: those apply within a state, not across the entire country.

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Speaker 1: There are a few federal protections that are in place.

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Speaker 1: In Europe, the protections are way more extensive. The g

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Speaker 1: d PR resolution is an example of that, but it's

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Speaker 1: just one example of that. So in Europe people generally

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Speaker 1: enjoy a better level of protection as far as uh

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Speaker 1: their data security is concerned, and there are a lot

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Speaker 1: of analytics companies out there that have tried to address

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Speaker 1: these issues because they want to know. They want people

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Speaker 1: to know, Hey, what we do is valuable. What we

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Speaker 1: do actually is part of what makes the Internet work.

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Speaker 1: As long as we do it with accountability and we

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Speaker 1: do it with respect to your privacy, everything should be

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Speaker 1: fine and everyone should benefit. So one of the big

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Speaker 1: pushes in the industry is to be more transparent about

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Speaker 1: what which data points these rights are collecting and to

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Speaker 1: what purpose, Like why are they collecting all this information?

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Speaker 1: And it can't just be transparent. It needs to be

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Speaker 1: worded in a way that makes sense. It's not buried

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Speaker 1: in jargon and legal ease, because then just nine people

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Speaker 1: just skip over it and they don't get angry until

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Speaker 1: something goes wrong. So being able to explain in blame language, hey,

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Speaker 1: we are collecting these data points about people. This is

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Speaker 1: how we're using that data. Here's how you will benefit

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Speaker 1: from that use, and here's how we benefit from that use.

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Speaker 1: If it's completely transparent, everyone is much less likely to

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Speaker 1: get upset because they're less likely to misinterpret what is

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Speaker 1: happening or to make assumptions about the worst right. So

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Speaker 1: tracking in itself might not be malicious. It's meant to

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Speaker 1: make things better for everybody, but it's also very easy

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Speaker 1: to misuse the information and data is valuable right, so

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00:24:59,040 --> 00:25:02,080
Speaker 1: it has actual real value to it. That means bad

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Speaker 1: actors will go after it too. So what can you

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00:25:04,800 --> 00:25:09,160
Speaker 1: do on a personal level to protect yourself. One thing

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Speaker 1: is that browsers have a do not track setting that

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Speaker 1: you can enact. You can enable do not tracked track. Rather,

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Speaker 1: in theory, that protocol would mean that sites would agree

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Speaker 1: not to track you. Now, I say in theory because

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Speaker 1: there's nothing legally requiring sites to obey that protocol, so

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Speaker 1: they might track you anyway. The more reputable ones probably won't,

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Speaker 1: but other sites might not really give it any mind,

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Speaker 1: so it's not really the safest approach. You can try

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Speaker 1: to browse in private or incognito mode and a browser

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Speaker 1: lots of browsers allowed for this, and usually what that

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Speaker 1: means is it will only load cookies for that current session,

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Speaker 1: so you're not gonna have cookies save to the browser

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Speaker 1: in this way, so that reduces a site's ability to

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Speaker 1: track your information. Although the longer you stay on a

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Speaker 1: site and the more you click around, the more information

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Speaker 1: you are giving that site. Uh, Incognito mode really only

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Speaker 1: kind of a racist trace of your activities on that

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Speaker 1: local device. So the computer you're using, the mobile device

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Speaker 1: you're using, whatever that may be. Incognito mode really just

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Speaker 1: keeps it from being you know, your activities being left

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Speaker 1: on that device. Your Internet service provider will still see

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Speaker 1: where you're going, because it has to in order to

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Speaker 1: be able to send you the information that you're requesting

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00:26:35,160 --> 00:26:37,760
Speaker 1: through the web browser. Um, you still have an IP

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Speaker 1: address that can still narrow down where you live or

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Speaker 1: where you're accessing the information from. If you log into

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Speaker 1: a service like Facebook or Twitter or something like that,

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Speaker 1: that's a dead giveaway. So this is a limited help.

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Speaker 1: Another thing you might do is install browser extensions that

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Speaker 1: limit active scripts from running on websites without your authorization.

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Speaker 1: So there are extensions like no Script Security Suite that's

436
00:27:02,000 --> 00:27:06,080
Speaker 1: for Firefox, UH, their Script Safe that's for Chrome. These

437
00:27:06,080 --> 00:27:09,640
Speaker 1: are extensions that put the control in your hands. So

438
00:27:09,920 --> 00:27:11,680
Speaker 1: when you access a site that has one of these

439
00:27:11,680 --> 00:27:14,879
Speaker 1: sort of invisible trackers on it or whatever, it'll pop

440
00:27:15,000 --> 00:27:17,879
Speaker 1: up and alert you and you can choose to either

441
00:27:18,000 --> 00:27:20,639
Speaker 1: allow it or to prevent it from being able to

442
00:27:20,680 --> 00:27:24,280
Speaker 1: track you. UH. At least in the JavaScript approach. If

443
00:27:24,320 --> 00:27:28,520
Speaker 1: people are looking at their access logs, that's still gonna

444
00:27:28,520 --> 00:27:31,080
Speaker 1: show that you've visited the site, but it won't give

445
00:27:31,119 --> 00:27:34,520
Speaker 1: the kind of tiny amounts of data that JavaScript would.

446
00:27:34,800 --> 00:27:37,800
Speaker 1: Tiny tiny is in focused, there's actually quite a lot

447
00:27:37,840 --> 00:27:41,640
Speaker 1: of data. The Electronic Frontier Foundation offers up an extension

448
00:27:41,680 --> 00:27:46,280
Speaker 1: for Firefox, Opera, and Android called Privacy Badger. This add

449
00:27:46,320 --> 00:27:50,720
Speaker 1: on blocks trackers and spy wear. Specifically, it quote stops

450
00:27:50,800 --> 00:27:54,359
Speaker 1: advertisers and other third party trackers from secretly tracking where

451
00:27:54,400 --> 00:27:56,960
Speaker 1: you go and what pages you look at on the web.

452
00:27:57,560 --> 00:28:00,000
Speaker 1: If an advertiser seems to be tracking you across multiple

453
00:28:00,080 --> 00:28:04,560
Speaker 1: websites without your permission, Privacy Badger automatically blocks that advertiser

454
00:28:04,600 --> 00:28:07,719
Speaker 1: from loading any more content in your browser. To the advertiser,

455
00:28:07,720 --> 00:28:10,840
Speaker 1: it looks like you suddenly disappeared. End quote. So it

456
00:28:10,880 --> 00:28:15,280
Speaker 1: does this by identifying which content sources are registering your

457
00:28:15,280 --> 00:28:18,199
Speaker 1: presence on a web page, including the ads that are

458
00:28:18,280 --> 00:28:21,000
Speaker 1: loaded on that web page, and as you go from

459
00:28:21,000 --> 00:28:23,639
Speaker 1: one page to another, if it keeps picking up the

460
00:28:23,720 --> 00:28:26,720
Speaker 1: same sources, that's an indication that you're being tracked, and

461
00:28:26,760 --> 00:28:30,159
Speaker 1: those are the ones that will um it will stop

462
00:28:30,200 --> 00:28:33,800
Speaker 1: loading into your web browser, and since it stops loading it,

463
00:28:34,200 --> 00:28:37,480
Speaker 1: the source can no longer get information about your activities,

464
00:28:37,480 --> 00:28:39,640
Speaker 1: and it's like you just disappeared into thin air. But

465
00:28:39,760 --> 00:28:43,080
Speaker 1: what about them virtual private networks. I'm gonna have to

466
00:28:43,080 --> 00:28:45,920
Speaker 1: do a full episode about VPNs and why they exist

467
00:28:45,960 --> 00:28:49,240
Speaker 1: and why they're important and when you should use one.

468
00:28:49,960 --> 00:28:53,080
Speaker 1: I'll do one of those in the future, but generally,

469
00:28:53,560 --> 00:28:58,800
Speaker 1: in this context, they're mostly good for hiding your physical location. UH.

470
00:28:58,840 --> 00:29:02,440
Speaker 1: The lokal ation will appear to correspond to that of

471
00:29:02,520 --> 00:29:05,720
Speaker 1: the virtual private network, not to you, not to your

472
00:29:05,800 --> 00:29:11,760
Speaker 1: real world location, because the web browser will be acting

473
00:29:11,840 --> 00:29:17,479
Speaker 1: like the VPN is the source of the traffic, not

474
00:29:17,480 --> 00:29:21,200
Speaker 1: not your computer, and the VPN handles it from that

475
00:29:21,240 --> 00:29:24,240
Speaker 1: point to get it to you. So you would still

476
00:29:24,280 --> 00:29:26,280
Speaker 1: get cookies from sites. They'd still be able to track

477
00:29:26,320 --> 00:29:30,040
Speaker 1: your activities, but I would do it through the the

478
00:29:30,080 --> 00:29:34,080
Speaker 1: context of the VPN and UH. And since your behaviors

479
00:29:34,080 --> 00:29:36,360
Speaker 1: are filtering through the VPN instead of your normal I

480
00:29:36,560 --> 00:29:39,160
Speaker 1: s P, what you're really doing is trading one entity

481
00:29:39,240 --> 00:29:42,160
Speaker 1: for another. Instead of having the I s P be

482
00:29:42,280 --> 00:29:45,600
Speaker 1: the one monitoring all the stuff you're doing, the VPN

483
00:29:46,360 --> 00:29:49,360
Speaker 1: could technically monitor all the stuff you're doing, so I

484
00:29:49,400 --> 00:29:51,200
Speaker 1: guess then it just comes down to who do you

485
00:29:51,240 --> 00:29:54,760
Speaker 1: trust more, the VPN or the I s p UM.

486
00:29:54,840 --> 00:29:57,440
Speaker 1: The answer is going to be very dependent upon which

487
00:29:57,480 --> 00:30:00,520
Speaker 1: of those entities are you're making use of at any

488
00:30:00,560 --> 00:30:04,760
Speaker 1: given time. So one last little bit about the pros

489
00:30:04,800 --> 00:30:09,280
Speaker 1: and cons of tracking. Tracking is what makes online advertising work.

490
00:30:10,040 --> 00:30:13,560
Speaker 1: So it's somewhat infuriating because online tracking gives us a

491
00:30:13,600 --> 00:30:16,480
Speaker 1: really granular view of which ads work on which sites,

492
00:30:16,520 --> 00:30:20,120
Speaker 1: and which ones don't. We learned about how different form

493
00:30:20,200 --> 00:30:23,240
Speaker 1: factors can be more or less effective. You might find

494
00:30:23,240 --> 00:30:25,960
Speaker 1: out that at A tests really well on site one,

495
00:30:26,600 --> 00:30:29,280
Speaker 1: but it fails miserably on site too. But AD B,

496
00:30:30,240 --> 00:30:32,080
Speaker 1: which is for the exact same product, is at A,

497
00:30:32,240 --> 00:30:34,760
Speaker 1: but it's a different design that one works great on

498
00:30:34,800 --> 00:30:37,360
Speaker 1: site too. Or maybe you find out just by changing

499
00:30:37,360 --> 00:30:40,360
Speaker 1: where an AD displays on a page it drives more engagement.

500
00:30:41,040 --> 00:30:43,800
Speaker 1: The reason this is important is because running a website

501
00:30:44,000 --> 00:30:47,240
Speaker 1: is not free. If it were, the world would be

502
00:30:47,240 --> 00:30:51,280
Speaker 1: a very different place. So companies like how stuff works

503
00:30:51,320 --> 00:30:54,960
Speaker 1: dot Com have costs associated with them, right, and those

504
00:30:54,960 --> 00:30:58,240
Speaker 1: are significant costs, not just like web hosting, but other

505
00:30:58,280 --> 00:31:02,320
Speaker 1: stuff like off the space, lay salaries, healthcare lots and

506
00:31:02,400 --> 00:31:06,360
Speaker 1: lots of costs. So if there's no money coming in

507
00:31:06,560 --> 00:31:09,120
Speaker 1: to cover those costs, you won't stay in business. You

508
00:31:09,240 --> 00:31:14,160
Speaker 1: go into debt. Eventually you go into bankruptcy. Uh. So

509
00:31:14,320 --> 00:31:16,520
Speaker 1: you want to make money to pay off the costs,

510
00:31:16,560 --> 00:31:18,360
Speaker 1: and you really want to make enough to make a profit.

511
00:31:18,400 --> 00:31:20,040
Speaker 1: I mean, that's what a business is all about, is

512
00:31:20,040 --> 00:31:24,560
Speaker 1: making profits. So without profit, businesses don't really exist. And

513
00:31:24,600 --> 00:31:27,720
Speaker 1: then the content goes away. So unless we move to

514
00:31:28,000 --> 00:31:32,720
Speaker 1: a totally different model of the web, which probably be

515
00:31:32,800 --> 00:31:34,720
Speaker 1: one where we have to pay for everything we want

516
00:31:34,760 --> 00:31:38,680
Speaker 1: to access, everything would be behind a paywall, it would

517
00:31:38,680 --> 00:31:42,800
Speaker 1: be really hard to continue to have web content. We

518
00:31:42,880 --> 00:31:46,840
Speaker 1: have to have some financial means to support the content

519
00:31:47,720 --> 00:31:50,000
Speaker 1: or else the content goes away. Same thing is true

520
00:31:50,040 --> 00:31:53,920
Speaker 1: for podcasts. I mean, the reason we have sponsors is

521
00:31:54,000 --> 00:31:59,480
Speaker 1: to h to pay off the costs of producing these

522
00:31:59,480 --> 00:32:04,520
Speaker 1: shows and posting the shows and continue to develop shows

523
00:32:04,520 --> 00:32:09,560
Speaker 1: and make new shows. The ads support that, and hopefully

524
00:32:10,040 --> 00:32:14,800
Speaker 1: the ads that we are choosing to place with shows

525
00:32:15,440 --> 00:32:18,600
Speaker 1: are meaningful to our listeners, because if they're not, then

526
00:32:18,600 --> 00:32:22,360
Speaker 1: it's not really doing anyone any good. And ultimately, you

527
00:32:22,440 --> 00:32:29,440
Speaker 1: want the best possible relationship between content, advertising, and users.

528
00:32:29,520 --> 00:32:33,680
Speaker 1: You want something where everybody is happy with it, because otherwise,

529
00:32:33,680 --> 00:32:36,280
Speaker 1: what's the point. The same thing is true with the website,

530
00:32:37,280 --> 00:32:39,680
Speaker 1: so the tracking is very important to get that kind

531
00:32:39,680 --> 00:32:42,960
Speaker 1: of information. It's kind of funny to me because classic media,

532
00:32:43,040 --> 00:32:47,760
Speaker 1: your traditional media, things like television, magazines, newspapers, that kind

533
00:32:47,800 --> 00:32:51,960
Speaker 1: of stuff, everything that has advertising in it, Uh, it's

534
00:32:51,960 --> 00:32:55,160
Speaker 1: a lot harder to tell how well that advertising works,

535
00:32:56,320 --> 00:32:59,000
Speaker 1: how much impact that advertising has. With the exception of

536
00:32:59,040 --> 00:33:02,200
Speaker 1: stuff like the Super Bowl in the United States, where

537
00:33:02,200 --> 00:33:06,000
Speaker 1: people famously will tune in just to watch commercials, you

538
00:33:06,000 --> 00:33:09,560
Speaker 1: really don't know how much attention is being directed toward commercials.

539
00:33:09,640 --> 00:33:12,719
Speaker 1: You might be able to get some general ratings about

540
00:33:12,920 --> 00:33:16,160
Speaker 1: how well a certain television show has done, but that

541
00:33:16,200 --> 00:33:20,880
Speaker 1: doesn't really tell you anything about the ads themselves. So

542
00:33:22,720 --> 00:33:27,440
Speaker 1: it's funny to me that the traditional media, the advertising world,

543
00:33:27,480 --> 00:33:30,960
Speaker 1: is very comfortable in that space and in the online

544
00:33:30,960 --> 00:33:33,600
Speaker 1: space where we can actually see how well an ad

545
00:33:33,640 --> 00:33:36,760
Speaker 1: does because we can see how many people click on it,

546
00:33:36,840 --> 00:33:41,000
Speaker 1: how many people actually went through and said this is interesting,

547
00:33:41,120 --> 00:33:43,000
Speaker 1: I want to know more, I want to be able

548
00:33:43,000 --> 00:33:46,040
Speaker 1: to buy this. We can actually see how effective that is,

549
00:33:46,120 --> 00:33:52,160
Speaker 1: and somehow that makes it less valuable, uh in some cases,

550
00:33:52,200 --> 00:33:55,920
Speaker 1: like the CPMs that are demanded and in direct mail,

551
00:33:56,400 --> 00:33:59,960
Speaker 1: like sending stuff out in magazines and things that's way

552
00:34:00,200 --> 00:34:05,680
Speaker 1: higher than what you typically see for most online advertising. Um,

553
00:34:05,720 --> 00:34:08,800
Speaker 1: one of those things where a little knowledge can be dangerous.

554
00:34:08,840 --> 00:34:13,799
Speaker 1: I guess, very fascinating topic. And while you can go

555
00:34:13,880 --> 00:34:18,280
Speaker 1: through and do those extensions and use VPNs and things

556
00:34:18,320 --> 00:34:21,920
Speaker 1: and turn off a lot of the the elements that

557
00:34:22,040 --> 00:34:25,879
Speaker 1: will allow sites to track you, if you do that,

558
00:34:26,360 --> 00:34:31,000
Speaker 1: you also lose that of the benefits that tracking gives

559
00:34:31,200 --> 00:34:34,680
Speaker 1: to users. That might be a worthy trade off for

560
00:34:34,760 --> 00:34:37,800
Speaker 1: you if you really value your privacy and you don't

561
00:34:37,840 --> 00:34:41,560
Speaker 1: want sites to get access to that kind of information.

562
00:34:42,520 --> 00:34:46,040
Speaker 1: But UM, you know it's it's it's just this kind

563
00:34:46,040 --> 00:34:49,120
Speaker 1: of the way our online world works, and without some

564
00:34:49,200 --> 00:34:53,479
Speaker 1: sort of transformative change, I don't see that being any

565
00:34:53,520 --> 00:34:57,520
Speaker 1: different anytime soon. But it is an interesting subject. If

566
00:34:57,520 --> 00:35:00,880
Speaker 1: you guys have any ideas for future episodes, I any

567
00:35:00,920 --> 00:35:02,719
Speaker 1: sort of topic you want me to cover, whether it's

568
00:35:02,760 --> 00:35:06,160
Speaker 1: a technology, a company, a person in tech. Maybe there's

569
00:35:06,160 --> 00:35:08,600
Speaker 1: someone I should interview or have on as a guest host.

570
00:35:09,160 --> 00:35:11,839
Speaker 1: Send me a message. The email addresses tech stuff at

571
00:35:11,880 --> 00:35:14,479
Speaker 1: how Stuff works dot com or drop me a line

572
00:35:14,480 --> 00:35:16,359
Speaker 1: on Facebook or Twitter to handle it. Both of those

573
00:35:16,480 --> 00:35:19,640
Speaker 1: is tech stuff hs W. Don't forget. Head on over

574
00:35:19,680 --> 00:35:23,279
Speaker 1: to T public dot com slash tech stuff. That's T

575
00:35:23,560 --> 00:35:26,800
Speaker 1: e e Public dot com slash tech stuff to get

576
00:35:26,840 --> 00:35:30,719
Speaker 1: all your tech stuff merchandise needs. You know, maybe maybe

577
00:35:30,760 --> 00:35:34,160
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578
00:35:34,200 --> 00:35:37,359
Speaker 1: coffee sitting here, but I have no mug to put

579
00:35:37,400 --> 00:35:40,680
Speaker 1: it in. Get yourself a tech stuff mug. They're pretty awesome.

580
00:35:40,719 --> 00:35:44,360
Speaker 1: I've got two of them myself, And don't forget to

581
00:35:44,400 --> 00:35:49,120
Speaker 1: follow us on Instagram. Don't talk to you again really

582
00:35:49,200 --> 00:35:57,760
Speaker 1: soon for more on this and thousands of other topics

583
00:35:57,800 --> 00:36:04,759
Speaker 1: because it how stuff works dot com. Who who Who