Speaker 1: Welcome to tex Stuff, a production from I Heart Radio.
Speaker 1: Hey there, and welcome to tech Stuff. I'm your host,
Speaker 1: Jonathan Strickland. I'm an executive producer with I Heart Radio,
Speaker 1: and I love all things tech and I don't get
Speaker 1: to do this very often, so indulge me. But in
Speaker 1: Shakespeare's classic tragedy Hamlet, our protagonist and perpetually moody Dane
Speaker 1: says at one point there is nothing either good or bad,
Speaker 1: but thinking makes it so. What he means there is that,
Speaker 1: at least in his eyes, all things in the universe
Speaker 1: are just as they are. They are neither good nor bad.
Speaker 1: It's only how we think about them that makes them
Speaker 1: good or bad. This is similar to a philosophy and
Speaker 1: I've talked about on this show when it comes to technology.
Speaker 1: Technology and of itself has the capacity to help or
Speaker 1: to harm. But the underlying tech isn't necessarily good or evil.
Speaker 1: It's how it's put to use that makes all the difference. Now, granted,
Speaker 1: there are some technologies that are harder to use in
Speaker 1: a way that is a net positive, you know, like
Speaker 1: nuclear warheads for example. Not that people haven't tried, they have,
Speaker 1: but you get my meaning. Well, one technology that has
Speaker 1: far reaching effects and consequences that can end up being
Speaker 1: positive or negative. Would be the algorithms that are underlying
Speaker 1: stuff like search and social networks. Specifically today, I'm going
Speaker 1: to be talking about Facebook in this episode, but algorithms
Speaker 1: underlie the various computer systems and online systems that we
Speaker 1: rely upon, and they have the potential to be harmful
Speaker 1: depending on their implementation. But before I start talking about
Speaker 1: the effects of algorithms, let's back up a little bit
Speaker 1: and define that what exactly is an algorithm. Basically, an
Speaker 1: algorithm is a set of directions or rules, and that's
Speaker 1: really it. There's nothing special about this definition. These rules
Speaker 1: guide how computers calculate operations and solve problems. It's a
Speaker 1: finite sequence of instructions for computers to follow when they're
Speaker 1: executing a specific task. These instructions are unambiguous, which means
Speaker 1: the computer system doesn't have to make judgment calls or
Speaker 1: anything like that while executing the instructions. There is a
Speaker 1: clear path to follow based on whatever the situation is
Speaker 1: at hand. A different situation might lead to a different outcome,
Speaker 1: but the instruction path would still remain clear. If you
Speaker 1: were to dig down deeply enough to see what was
Speaker 1: going on behind the computer's actions. The number of potential
Speaker 1: paths to various outcomes could be an warmous and so
Speaker 1: to us it would look like a really complicated system
Speaker 1: and very difficult to grock. But if you really got granular,
Speaker 1: you would see the logic, as it were, that connects
Speaker 1: the beginning state to the end state of any given operation.
Speaker 1: At Google, search algorithms include elements that determine what position
Speaker 1: of particular query result will take on a results page.
Speaker 1: So when we search for something using an engine like Google,
Speaker 1: there are several things going on in that split second
Speaker 1: before our results pop up. For one thing, Google has
Speaker 1: an index of all the web pages it has crawled,
Speaker 1: and so Google will reference that index to find all
Speaker 1: the entries and that index that relate to the terms
Speaker 1: that you put in your search query. And then those
Speaker 1: results are ranked by a few different criteria. So way
Speaker 1: up there is relevancy, like how relevant is each search
Speaker 1: result to the original search query. If I were to
Speaker 1: search for Captain America, Google is going to put the
Speaker 1: pages about the fictional superhero way up towards the top
Speaker 1: search results about someone who happens to hold the rank
Speaker 1: of Captain and there's somewhere a mention of the region
Speaker 1: of America would likely fall much lower on the search
Speaker 1: results list, because even though those pages will have relevant
Speaker 1: terms in them, the chances are it's not what I'm
Speaker 1: actually looking for. A context is important, but context is
Speaker 1: just part of it. There are thousands of pages that
Speaker 1: mentioned Captain America. Some are from really good resources, meaning
Speaker 1: they are resources that are dependable, they're informative, they might
Speaker 1: be entertaining, you know whatever. Some are from garbage sites
Speaker 1: that don't provide any real valuable experience. So then you've
Speaker 1: got the ranking system within Google that determines how the
Speaker 1: most relevant search engine results will appear on the results age. Now,
Speaker 1: if there are thousands or even millions of hits, how
Speaker 1: does Google determine which ones show up on the first
Speaker 1: page of results. Well, there's a complicated system that determines
Speaker 1: that ranking, and it's not really in the realm of
Speaker 1: this episode to go into it, but suffice it to
Speaker 1: say that Google takes a lot of things into consideration
Speaker 1: when ordering search results. Ostensibly, this is all in an
Speaker 1: effort to give you the most relevant and helpful results
Speaker 1: based on your search query. For the people companies and
Speaker 1: organizations that are making pages. It's always a goal to
Speaker 1: rank really high on that list, preferably on that first page,
Speaker 1: and if you can, the top half of that first page,
Speaker 1: because most people will only look at the first few
Speaker 1: search results and then they'll ignore everything that comes afterward.
Speaker 1: Over the years, Google has made it really tricky to
Speaker 1: game this engine, which means it's hard to come up
Speaker 1: with effective strategies to show up higher in search results.
Speaker 1: Your best bet is really to create just really good
Speaker 1: resources around the particular topic of interest in question. And also,
Speaker 1: you know, happened to be a really respected resource, which
Speaker 1: is not easy to do, especially if you're just starting out. Obviously, Also,
Speaker 1: whenever Google makes changes to this algorithm, it can drastically
Speaker 1: affect how your page appears in search results, even with
Speaker 1: a perfect query. And when tech stuff was still part
Speaker 1: of how stuff works, that was something we were always
Speaker 1: concerned about. A change in the Google algorithm would mean
Speaker 1: that our web traffic could either skyrocket or it could plummet.
Speaker 1: There was no change in the quality of our work.
Speaker 1: Our work was just as good as it had been before.
Speaker 1: It would just be a change in how our work
Speaker 1: would show up in search results. However, that's the Google algorithm.
Speaker 1: With other algorithms like the ones on Facebook, those can
Speaker 1: be easier to game if you know what you're doing.
Speaker 1: And what's more, there are algorithms on Facebook that allow
Speaker 1: for advertisers to engage in some discriminatory and potentially criminal behavior.
Speaker 1: So we'll look at how the various algorithms on Facebook
Speaker 1: can have a negative impact because of the way they
Speaker 1: are implemented and because of the way that people are
Speaker 1: taking advantage of them. Now, in the beginning, Facebook didn't
Speaker 1: have an algorithm at all. Heck, it didn't even have
Speaker 1: a news feed when it first started. Instead, you could
Speaker 1: post stuff to your profile, but then you could visit
Speaker 1: the profiles of friends to see what they had posted.
Speaker 1: You could leave comments on stuff, but it still required
Speaker 1: you to actually go over to your friends profile. There
Speaker 1: was no aggregator for content just yet that changed in
Speaker 1: two thousand seven when Facebook introduced the news feed. Now,
Speaker 1: your homepage on Facebook had a record of your friends activities,
Speaker 1: just listed in reverse chronological order. You know, the most
Speaker 1: recent things appearing at the top of the list. You
Speaker 1: could log in and see what your friends had been
Speaker 1: up to since the last time you were on and
Speaker 1: you could catch up. There's still no algorithm to speak
Speaker 1: of yet, and as would become a hallmark of any
Speaker 1: change made on Facebook. Ever, a lot of users objected
Speaker 1: to the news feed, and the main objection was that
Speaker 1: people felt it was a violation of privacy. They didn't
Speaker 1: like the idea that the activities they were doing on
Speaker 1: Facebook were being broadcast to all of their friends, which okay,
Speaker 1: now this one stumps me a little bit, because the
Speaker 1: profiles on Facebook were public unless you set privacy features
Speaker 1: to make it otherwise. So if you change your relationship
Speaker 1: status on your profile, for example, why would you object
Speaker 1: to it being broadcast to your friends. If anyone visited
Speaker 1: your profile, they would see the difference. So either you
Speaker 1: don't change it, or you change the privacy settings on
Speaker 1: your profile, But otherwise why would you be upset? I
Speaker 1: think the main takeaway is just that people hate change,
Speaker 1: and if you don't want something broadcast to everybody, maybe
Speaker 1: you shouldn't post it. A couple of years later, Facebook
Speaker 1: introduced the first iteration of their algorithm, which would determine
Speaker 1: what users would see in their news feed and in
Speaker 1: what order they would appear, so rather than getting a
Speaker 1: full account, of all of your friends activities in reverse
Speaker 1: chronological order. Users would see a selection of stuff that
Speaker 1: the algorithm had determined was the best for that user.
Speaker 1: So how did that work? Well, generally speaking, the algorithm
Speaker 1: took three main criteria into account to select the stuff
Speaker 1: that would show up on news feeds. One was user affinity,
Speaker 1: which was an indicator of how close the relationship is
Speaker 1: between one Facebook user and another, or a Facebook user
Speaker 1: and a brand. And this was measured in one way perspectives,
Speaker 1: and that can be a little confusing. So let's make
Speaker 1: a an example. We'll take three fictional people to explain
Speaker 1: how this affinity worked. So in this example, we've got Sam, Dean,
Speaker 1: and Castiel. Okay, So Sam and Dean are super close, right,
Speaker 1: and they often comment on each other's posts, and they'll
Speaker 1: hit like on each other's statuses and all that kind
Speaker 1: of stuff. So they tend to see one another's posts
Speaker 1: a lot in their own news feeds when they log
Speaker 1: onto Facebook. They each have a high affinity for each other.
Speaker 1: Then we've got Castil. So Castiel is friends with both
Speaker 1: Sam and Dean, but really he's much closer to Dean
Speaker 1: than he is to Sam. And Castiole responds to a
Speaker 1: lot of Dean's posts, and as a result, Castiel C's
Speaker 1: Dean's stuff pop up in his that is, Castil's news
Speaker 1: feed pretty regularly. Castil is not as close with Sam
Speaker 1: and he doesn't interact with Sam as much. So sam
Speaker 1: stuff can pop up in Castile's news feed, but it's
Speaker 1: not as frequent or as sure a thing as when
Speaker 1: Dean posts something. Now, on top of that, Dean likes Castiel,
Speaker 1: but you get the feeling that this relationship is not
Speaker 1: a perfect two way street. So Dean only interacts with
Speaker 1: some of Castile's stuff that he posts online. So Dean
Speaker 1: sees Castiel's posts on occasion in his news feed, but
Speaker 1: not nearly at the same frequency at which he sees
Speaker 1: Sam's post in his that is Dean's news feed. And yes,
Speaker 1: I just summarized the show Supernatural in an example about
Speaker 1: Facebook algorithms and affinity. Now, as we see a high
Speaker 1: affinity one person has for another helps determine how much
Speaker 1: of that other person's stuff the first person is going
Speaker 1: to see. But it only works in that one way.
Speaker 1: If I like your posts a lot, then I'm going
Speaker 1: to see more of your posts in my feed. But
Speaker 1: if you never interact with me, You're not going to
Speaker 1: see a lot of my stuff in your feed. That's
Speaker 1: what I mean by that one way perspective. Of course,
Speaker 1: there are other ways to wait this, more like you
Speaker 1: can tag someone in a post, which will definitely give
Speaker 1: their attention much more effectively. But let's move on. So
Speaker 1: the second component to the edge rank factor we had
Speaker 1: user affinity as a component one. Component two is the
Speaker 1: weight of the post W E, I, G, H T.
Speaker 1: So different kinds of posts have different weights, and the
Speaker 1: greater the weight, the more likely it will pop up
Speaker 1: on a given friends feed. So, generally speaking, with edge rank,
Speaker 1: stuff that had photos or videos had the most weight,
Speaker 1: followed by posts that contained links, followed by plain text posts. Now,
Speaker 1: the reason for this is that Facebook analysts had figured
Speaker 1: out that posts that had stuff like photos and videos
Speaker 1: with tend to get more engagement. I'll get back to
Speaker 1: engagement a bit later in this episode. Just know that
Speaker 1: it is a critical concept for Facebook. The third component
Speaker 1: factored into edge rink is called time decay, which essentially
Speaker 1: translates to how old is this post? And the idea
Speaker 1: here is that the more recent posts are likely more
Speaker 1: relevant than older posts are it doesn't do you any
Speaker 1: good to see the announcement of an upcoming get together
Speaker 1: if in fact that get together actually happened last week,
Speaker 1: so you're not likely to see the initial post pop
Speaker 1: up at the top of your news feed if you've
Speaker 1: already missed everything. As the post ages, the value of
Speaker 1: the post decreases. So when you log into Facebook or
Speaker 1: open the Facebook app or whatever, this algorithm would run
Speaker 1: with your particular situation in mind. It would scan through
Speaker 1: all the stuff that had been posted by the friends
Speaker 1: you have and the brands you follow since your last session,
Speaker 1: and then it would select and rank or order those
Speaker 1: status updates that you would see in your news feed
Speaker 1: based off of those criteria. But this would also mean
Speaker 1: you would miss out on stuff. No longer would you
Speaker 1: be able to see everything that all of your friends
Speaker 1: were doing, listed in reverse chronological order. In fact, at times,
Speaker 1: chronology didn't have anything to do with the order in
Speaker 1: which status updates would appear on your news feed. A
Speaker 1: post several hours old might appear above one that was
Speaker 1: posted just five minutes before you logged in, all because
Speaker 1: of those other factors. For some Facebook users, including me
Speaker 1: at the time, this was really frustrating. It made us
Speaker 1: feel as though we were missing out on stuff our
Speaker 1: friends were saying because we were. I found it particularly
Speaker 1: irre tating because I wasn't one to frequently engage with updates.
Speaker 1: I didn't like a lot of them, and I wouldn't comment.
Speaker 1: A ton of times. I would read everything, but I
Speaker 1: wasn't interacting with it, So the algorithm wasn't getting a
Speaker 1: really good idea of who my good friends were versus
Speaker 1: like people who are my acquaintances. So it meant that
Speaker 1: some people who were my closest friends in reality were
Speaker 1: not the ones that I was seeing, you know, being
Speaker 1: active on Facebook. Even if they were, I just wasn't
Speaker 1: seeing those posts. And my case was not unusual. A
Speaker 1: lot of people went through this and and then I
Speaker 1: missed stuff, sometimes big stuff like an engagement announcement or something.
Speaker 1: Edge rank was just the beginning, and actually that particular
Speaker 1: algorithm didn't stick around that long in the grand scheme
Speaker 1: of things. By late within Facebook, no one was really
Speaker 1: using the term edge rank anymore because they had moved
Speaker 1: towards a more sophisticated machine learning based algorithm. This one
Speaker 1: was far more sophisticated than edge rank. It was not
Speaker 1: limited to just those three main factors, although they were
Speaker 1: still components within the algorithm. Instead, according to Lar's Backstrom,
Speaker 1: who was the engineering manager for the news feed ranking
Speaker 1: at the time, this new one used somewhere in the
Speaker 1: neighborhood of one hundred thousand weights to determine what users
Speaker 1: would see and in which order. Now you would think
Speaker 1: that with that many weights it would be hard to
Speaker 1: gain the system, but you'd be wrong. Now, a couple
Speaker 1: other things I want to mention before we go to break.
Speaker 1: One of those is that, yes, there was an option
Speaker 1: still is to try and list things in most recent
Speaker 1: as opposed to what is most relevant or whatever Facebook
Speaker 1: thinks is most relevant, except that you're not really seeing
Speaker 1: everything that way. Either. You're not getting the most recent
Speaker 1: reverse chronological list of all of your friends activities. It's
Speaker 1: still a selection of what your friends are posting, and
Speaker 1: it's a selection that the algorithm has determined is the
Speaker 1: most relevant for you. It's just that they'll be listed
Speaker 1: in reverse order instead of kind of that haphazard all
Speaker 1: over the place method. But the fact is you're still
Speaker 1: not seeing everything, which still frustrates a lot of people.
Speaker 1: And when we come back we'll talk about the algorithm,
Speaker 1: how people have used the creative approach to game the system,
Speaker 1: and some unintended consequences that algorithm has led to. But
Speaker 1: first let's take a quick break. So we're at the
Speaker 1: point where an algorithm starts to serve up content catered
Speaker 1: to each individual Facebook user, and the goal was always
Speaker 1: the same from the very beginning keep people engaged, which
Speaker 1: really just means keep people on Facebook for longer. And
Speaker 1: this gets to Facebook's method of generating revenue. Facebook's primary
Speaker 1: source of revenue is through advertising. And when I say primary,
Speaker 1: according to Investopedia, advertising accounts for ent of Facebook's revenue,
Speaker 1: which for Q three was twenty one point five billion dollars.
Speaker 1: Wholly cal princely some doesn't even begin to cover it.
Speaker 1: Facebook sales ad space to various companies to serve up
Speaker 1: advertising to Facebook's users, so they're essentially think of it
Speaker 1: like a billboard. Facebook is like a giant billboard, but
Speaker 1: it's a very special billboard. It's incredibly valuable. There's another
Speaker 1: component to this I'll touch on later, which revolves around
Speaker 1: targeted advertising, but let's just stick with the basic value
Speaker 1: proposition here. So Facebook has space on its apps and
Speaker 1: its pages, and in that space ace it has the
Speaker 1: ability to show ads that they could be on the side,
Speaker 1: they can be fed into the news feed as well,
Speaker 1: so they're kind of interspersed along with the status updates
Speaker 1: from friends and stuff. Uh. The longer that people use
Speaker 1: Facebook per any given session, the more ads they will
Speaker 1: encounter as they interact with Facebook, which also means that
Speaker 1: they could potentially interact with the ads. So part of
Speaker 1: what Facebook really needs to do is to find ways
Speaker 1: to convince people to spend as much time as possible
Speaker 1: on Facebook. In this use case, time really is money.
Speaker 1: Greater engagement doesn't just mean more opportunities to see ads,
Speaker 1: it also means that Facebook can demonstrate its own value
Speaker 1: to advertisers and thus command higher prices. To put it
Speaker 1: another way, let's say you own a few billboards around town.
Speaker 1: Since I've already mentioned them, so let's say you have
Speaker 1: a billboard that is on a back road and that
Speaker 1: gets just a little bit of traffic every day, and
Speaker 1: you happen to own another billboard space which is on
Speaker 1: a much more heavily used road that goes right into
Speaker 1: the heart of town. The rates that you would be
Speaker 1: able to charge for the back road billboard are probably
Speaker 1: gonna be a lot lower than what you can command
Speaker 1: with the heavily traveled thoroughfare. More folks are going to
Speaker 1: see that second billboard, which makes it more valuable. On
Speaker 1: a similar front, if Facebook can show numbers that indicate
Speaker 1: that more than two billion people are spending more and
Speaker 1: more time on Facebook, it can command higher prices for advertising.
Speaker 1: Add companies and their clients want to be where the
Speaker 1: eyeballs are, and Facebook fits the bill nicely. So with
Speaker 1: that in mind, the real purpose of the algorithm ultimately
Speaker 1: is to serve up stuff to users that will keep
Speaker 1: them on Facebook longer and convince them to come back
Speaker 1: to Facebook frequently. Now, some of the things that will
Speaker 1: bring people back fall online with a few of the
Speaker 1: ideas that Drank demonstrated. If you logged onto Facebook but
Speaker 1: you only ever saw posts from people you only kind
Speaker 1: of sort of know, and you always missed out on
Speaker 1: the posts from your close friends, you probably not find
Speaker 1: it a very satisfying experience. So at least some of
Speaker 1: the stuff you'd be seeing would fall in line with
Speaker 1: the stuff you'd really want to see in the first place,
Speaker 1: But maybe there would be some posts you would really
Speaker 1: like to see, but the algorithm, for whatever reason, doesn't
Speaker 1: judge those as being particularly engaging. Well, the chances are
Speaker 1: more slim that you would see those posts. If you've
Speaker 1: ever posted something to Facebook that you thought was particularly
Speaker 1: important or impactful, but you didn't see very much reaction
Speaker 1: to it, there's a chance that not many people actually
Speaker 1: saw what you posted, So that's a real possibility. Of course,
Speaker 1: there's also a chance that they did see it, they
Speaker 1: just didn't care. It's kind of hard to say for
Speaker 1: any given post, but it's entirely possible for you to
Speaker 1: post something that people would have reacted to. They just
Speaker 1: never saw it, so they never got the chance to.
Speaker 1: But let's say someone in your circle posts something and
Speaker 1: it starts to catch on. Maybe it's someone in your
Speaker 1: circle that you don't interact with much, so usually you
Speaker 1: don't see very much from them on Facebook. But for
Speaker 1: whatever reason, this particular post that they made is getting
Speaker 1: a lot of interaction from other friends, which means the
Speaker 1: algorithm might say, hey, this post is really taking off
Speaker 1: a lot of people are interacting with it, so I'm
Speaker 1: going to serve it up to even more people, including you,
Speaker 1: who usually wouldn't see such things. From this particular distant friend. So,
Speaker 1: in other words, posts that get a lot of engagement,
Speaker 1: that being reactions and comments and shares and that kind
Speaker 1: of stuff, they tend to rise above other posts. Engagement
Speaker 1: doesn't have to be positive either. It's not really important
Speaker 1: to Facebook if the stuff you see makes you happy
Speaker 1: or unhappy, or if the stuff you see is true
Speaker 1: or if it's false. What matters to Facebook is that
Speaker 1: you spend as much time on the platform as they
Speaker 1: can coax from you, and that you feel the need
Speaker 1: to return to Facebook frequently. Maybe it turns out you
Speaker 1: rage posts on Facebook a lot. Maybe you see stuff
Speaker 1: that you vehemently disagree with, so you post lengthy comments,
Speaker 1: or you share a post you don't agree with, but
Speaker 1: you do so in an effort to put your own
Speaker 1: spin on the thesis of the original post, or to
Speaker 1: criticize it in some way. Your motivations or goals are
Speaker 1: not important to Facebook. The company could not care less.
Speaker 1: The platform just once your time. Well, that's being a
Speaker 1: bit too reductive. Facebook also wants your posts to inspire
Speaker 1: other people to engage using their own comments, likes, and shares,
Speaker 1: so that they get their time too. That's really it.
Speaker 1: They want everyone's time, not just yours. I'm sure most
Speaker 1: of you already see where this becomes an issue. As
Speaker 1: we've heard for a few years now, Facebook has become
Speaker 1: a hotbed for misinformation and disinformation, something that Facebook founder
Speaker 1: Mark Zuckerberg has tried to avoid addressing for years. There's
Speaker 1: a saying that's frequently misattributed to Mark Twain that says
Speaker 1: a lie can travel halfway around the world while the
Speaker 1: truth is still putting on its shoes. I think it's
Speaker 1: kind of fitting that Twain is often cited as the
Speaker 1: originator of the saying, but the truth of the matter
Speaker 1: is that it predates him. It might have been the
Speaker 1: product of Jonathan Swift, but we don't really know. But
Speaker 1: the saying is apt. Misinformation is not saddled with the
Speaker 1: heavy burden of being, you know. True misinformation can tap
Speaker 1: into biases and preconceptions. It can reinforce the beliefs we hold,
Speaker 1: whether they're positive or negative, even if those beliefs have
Speaker 1: no real basis in reality. And if we feel that
Speaker 1: our beliefs are validated, we're more likely to engage and
Speaker 1: share those posts and to feel reinforced in it to
Speaker 1: do more, to continue sharing that kind of stuff. Now.
Speaker 1: I've seen examples of this across different ideologies. The narrative
Speaker 1: we frequently see here in the United States is how
Speaker 1: right wing misinformation will spread across Facebook, and that that
Speaker 1: certainly does happen, but I've also seen it happen for
Speaker 1: people who have a left leaning ideology. For example, if
Speaker 1: a post indicates that someone with a right wing philosophy
Speaker 1: has done or said something terrible, that can spread rapidly
Speaker 1: across Facebook. But often you can do a little fact
Speaker 1: checking and find out that there's no actual evidence that
Speaker 1: such a thing was ever said or done by that person.
Speaker 1: I've seen this happen multiple times, So what I'm getting
Speaker 1: at is that no one is immune. That being said,
Speaker 1: certain groups, particularly those catering to more right wing audiences,
Speaker 1: have really pounced on the opportunity more than others have.
Speaker 1: And again I'm not saying left leaning organizations and people
Speaker 1: haven't done the same thing. They just haven't been as
Speaker 1: fast to jump on it, and it's less common they
Speaker 1: don't do it as much. Right now, I think it's
Speaker 1: pretty fair to say that no ethical organization or person
Speaker 1: would want to perpetuate misinformation or create disinformation. This is
Speaker 1: a form of manipulation to get people to support something
Speaker 1: without having to go to the trouble of actually really
Speaker 1: giving evidence that that point of view is the best one.
Speaker 1: If you're using lies to get people to support you, that's,
Speaker 1: you know, not great. But on Facebook that sort of
Speaker 1: thing can really take off, and as a post gets
Speaker 1: traction with people sharing it or commenting on it, or
Speaker 1: reacting to it, whether positively or negatively, Facebook will start
Speaker 1: serving that content to progressively larger audiences. And you can
Speaker 1: think of this as like ripples in a pond. That
Speaker 1: initial circle of a ripple that's really small, right, But
Speaker 1: let's say that that circle represents a certain group of
Speaker 1: users and they react very strongly to that content. Well,
Speaker 1: Facebook will then expand that to the next circle outward
Speaker 1: to affect a larger group of users, and if the
Speaker 1: trend continues, it just keeps getting bigger and bigger. Now,
Speaker 1: while this has been an issue with Facebook for ages,
Speaker 1: we really saw it come under scrutiny in when it
Speaker 1: became clear that Russian operatives were leveraging Facebook to manipulate
Speaker 1: Americans and spread disinformation, particularly when they came to politics.
Speaker 1: Complicating matters are fake Facebook accounts also known as bot accounts.
Speaker 1: These accounts don't represent actual users, but rather are part
Speaker 1: of larger systems designed to amplify the signal of certain messages.
Speaker 1: Every content creator out there would love for every post
Speaker 1: they make to go viral, that is, to become the
Speaker 1: sort of thing that tons of people see and share
Speaker 1: with others. Making viral content is pretty darn hard to
Speaker 1: do on purpose. Often the stuff happens organically, then it
Speaker 1: becomes difficult or even impossible to recapture that same magic
Speaker 1: on subsequent efforts. I'm sure you can think of lots
Speaker 1: of famous viral videos from people that never seemed to
Speaker 1: pop up again afterward, or if they did, it didn't
Speaker 1: have nearly the same effect. There countless examples of that.
Speaker 1: But by creating lots of fake accounts, you can amplify
Speaker 1: a message. You can get that effect of a viral
Speaker 1: breakout because you're manipulating the system. You're using bots that
Speaker 1: are either all blasting out the same post at the
Speaker 1: same time, which is actually really easy to detect. You
Speaker 1: can often see this on Twitter, where you'll find the
Speaker 1: exact same message posted by a bunch of seemingly disconnected
Speaker 1: Twitter accounts, which indicates they're all bots that are coming
Speaker 1: out of the same source, or more likely, you would
Speaker 1: have the bots interacting with a post and sharing that
Speaker 1: post and liking the post, thus amplifying the post's importance
Speaker 1: on Facebook in general and making it more visible as
Speaker 1: a result. Now, the visibility is one thing, but that
Speaker 1: interaction also creates a perception among the real humans who
Speaker 1: are using Facebook that that original post must have merit.
Speaker 1: If you look at a post and you see that
Speaker 1: it has thousands of reactions connected to it, you're more
Speaker 1: likely to pay attention and perhaps even take that post
Speaker 1: to heart. You know that that has a certain cash
Speaker 1: a that that social acceptance of a piece. And by
Speaker 1: lots of fake accounts, I really do mean lots. Last
Speaker 1: year in twenty nineteen, Facebook announced it had shut down
Speaker 1: more than three billion fake accounts over the course of
Speaker 1: half a year, three billion in six months. Even after that,
Speaker 1: Facebook estimated that somewhere around five of all accounts still
Speaker 1: on Facebook we're actually bots. Considering Facebook has more than
Speaker 1: two billion users, five percent represents a lot of fake accounts. Now,
Speaker 1: this doesn't mean that every user is going to see
Speaker 1: the posts that get that kind of engagement. The algorithm
Speaker 1: is taking a lot more into account, for example, the
Speaker 1: types of pages you like on the platform. That matters.
Speaker 1: If you like a lot of pages that have a
Speaker 1: more left leaning slant, you know, stuff that falls into
Speaker 1: like progressive politics, that category, you're less likely to see
Speaker 1: really hard right leaning posts as a rule, and in
Speaker 1: this way, Facebook can become a true echo chamber. The
Speaker 1: platform again wants to keep you there as long as possible,
Speaker 1: as many times as possible, so the algorithm is prioritizing
Speaker 1: content that it calculates has the best chance of keeping
Speaker 1: you on Facebook. If they drive you away, they've done
Speaker 1: the wrong thing, at least as far as Facebook's revenue
Speaker 1: generating plan goes. Facebook's crackdown on fake accounts was part
Speaker 1: of a larger effort to address the problems with misinformation
Speaker 1: that we're growing concerning enough for the US Congress to
Speaker 1: call Zuckerberg to Washington, d C. To answer questions about
Speaker 1: fake news and the like. Zuckerberg had long maintained that
Speaker 1: he didn't want Facebook to get into the business of
Speaker 1: arbitrating which bits of information were legit and which ones
Speaker 1: represented misinformation, as kind of this idea of it's the
Speaker 1: free market of ideas all ideas are are given equal platforms,
Speaker 1: And you can sort of understand his reasoning from a
Speaker 1: business perspective, because all that engagement really meant money for
Speaker 1: his company. But with Facebook under scrutiny and criticism, there
Speaker 1: was a very real danger of the platform being seen
Speaker 1: as a toxic place for advertisers. Companies that aren't too
Speaker 1: keen on getting looped in with content that falls in
Speaker 1: with radical ideology, we're getting nervous, and in fact, in
Speaker 1: we've seen advertisers boycott Facebook for various reasons, some of
Speaker 1: which relating back to Facebook's failure to address things like
Speaker 1: groups that are radicalizing individuals, that sort of stuff. So
Speaker 1: it does have an impact. Shutting down body accounts was
Speaker 1: one way to diminish the spread of misinformation on Facebook
Speaker 1: without actually taking the additional step of Facebook becoming a
Speaker 1: judge of what is and isn't legit information. But that
Speaker 1: wasn't quite enough to satisfy critics who are pointing out
Speaker 1: that people were using face to spread false narratives and
Speaker 1: to mislead people and to manipulate large populations, while Facebook
Speaker 1: meanwhile just raking in the profits from all of that.
Speaker 1: In fact, a recent article in The New York Times
Speaker 1: titled on Facebook, misinformation is more popular now than in
Speaker 1: Reporter Davey Alba shared research from the German Martial Fund
Speaker 1: Digital which found that people were sharing, liking, and commenting
Speaker 1: on three times as many articles from outlets that regularly
Speaker 1: published misinformation in than they were back in ten. So
Speaker 1: we're actually seeing more of it today. That's not a
Speaker 1: great trend there, and it's another indication that Facebook is
Speaker 1: reluctant to intervene in this and as Karen Cornbla, the
Speaker 1: director of the research firm, would say, counteracting this trend
Speaker 1: quote just runs against their economic incentives. In the quote,
Speaker 1: when we come back, it gets worse. But first let's
Speaker 1: take another quick break. So I mentioned before the break
Speaker 1: that it gets worse, and early in this episode I
Speaker 1: alluded to the concept of targeted advertising, and this gets
Speaker 1: into another aspect of algorithms on Facebook that can be harmful. Okay,
Speaker 1: So the basic idea behind targeted advertising is really simple,
Speaker 1: and the goal is to get the right ads in
Speaker 1: front of the right people. The goal is always to
Speaker 1: increase the odds that someone is going to act upon
Speaker 1: that ad. Otherwise advertising is just throwing money away, right,
Speaker 1: So going back to my billboard example from earlier, there's
Speaker 1: only so much targeting you can do with billboards. Now,
Speaker 1: you might choose to put up an add on a
Speaker 1: billboard that's in a part of town that most closely
Speaker 1: matches the demographic of your average customer, Meaning the people
Speaker 1: that you cater to happen to live in a certain
Speaker 1: part of town, so it makes more sense to put
Speaker 1: your billboard in that part of town. But that's a
Speaker 1: pretty primitive approach to targeted advertising. Facebook provides a laser focused,
Speaker 1: individual precision approach. Every user activity on Facebook gives Facebook
Speaker 1: more information about the the user in question and what
Speaker 1: they like, which is obvious, but we need to start there.
Speaker 1: So the pages that you visit on Facebook, the posts
Speaker 1: you interact with on Facebook, the general information in your
Speaker 1: profile like your birth date, your location, your relationship status,
Speaker 1: all of these are valuable pieces of information. You can
Speaker 1: actually go into Facebook's settings and the ad preferences page
Speaker 1: and you can see what Facebook has deduced about you.
Speaker 1: You know, the company will list out what it thinks
Speaker 1: your interests are, so you can see, oh, this is
Speaker 1: why I'm getting all of those ads for such and such.
Speaker 1: It's because Facebook thinks I'm really interested in that. For example,
Speaker 1: when I was first getting into exercising, which I really
Speaker 1: need to get back to. Uh, Facebook would serve me
Speaker 1: up all these ads for things like muscle enhancement, protein
Speaker 1: shake things. They're all these insanely buff dudes popping up
Speaker 1: on my Facebook profile news feed, and I was like, well,
Speaker 1: you know, good on you guys. You've done some great work.
Speaker 1: But that's not really it's not really my jam. But anyway,
Speaker 1: that that is one way that Facebook starts to build
Speaker 1: out information on you. But that's just the tip of
Speaker 1: the iceberg. Facebook also has marketing partners, a lot of
Speaker 1: marketing partners, and these partners are also collecting information about
Speaker 1: the people who are visiting their pages and their habits,
Speaker 1: including stuff like what items people might have purchased or
Speaker 1: perhaps just searched for or looked at. Like think of
Speaker 1: something that you've searched for, maybe on a site like Amazon,
Speaker 1: and you're looking at stuff you haven't pulled the trigger
Speaker 1: on buying anything yet, but you're just kind of comparison shopping. Well,
Speaker 1: these sort of partners share that data back with Facebook,
Speaker 1: and then Facebook can leverage that information and target specific
Speaker 1: ads to you based on what you've been doing off
Speaker 1: of Facebook in other parts of the web. So if
Speaker 1: you ever done a search for something like an air
Speaker 1: fryer and then you notice that whenever you go to
Speaker 1: Facebook you're seeing ads for air fryers and other kitchen
Speaker 1: gadgets just in your news feed, that's what's going on now.
Speaker 1: I saw this happen a lot when I was shopping
Speaker 1: around for a guitar. Every time I would log onto Facebook,
Speaker 1: I would see a ton of ads for various music shops,
Speaker 1: some of which were clearly scams. There's a lot of
Speaker 1: that on Facebook. Whether you'll see an ad for you know,
Speaker 1: you'll see an ad for something that looks like an
Speaker 1: incredible product, something there's phenomenal, amazing mask or costume piece,
Speaker 1: or you know, a special kit that seems to be
Speaker 1: catered right to your interests, and more than that, it's
Speaker 1: an unbelievably low price, like this is gonna be for
Speaker 1: forty bucks. You're like, wow, that would normally be hundreds
Speaker 1: of dollars. Well, this falls into the general category of
Speaker 1: if it sounds too good to be true, it probably is.
Speaker 1: A lot of these company pages are really just fronts
Speaker 1: for stores that sell cheap knockoffs, often with huge shipping
Speaker 1: costs because a lot of them are located in places
Speaker 1: like China. So you order the thing that looks incredible,
Speaker 1: you're like, wow, this would normally set me back a
Speaker 1: grant and they're asking for forty bucks. And then if
Speaker 1: you do get a product it doesn't resemble what you
Speaker 1: were promised. You end up getting a super cheap knockoff
Speaker 1: of whatever it was you were ordering it. But the
Speaker 1: expense of returning that product would be so much higher
Speaker 1: because of shipping costs, that it would not make any
Speaker 1: sense to return it. You would still be out more
Speaker 1: money by returning the product, so you just kind of
Speaker 1: suck it up. But that's kind of a tangent. Let's
Speaker 1: let's get back to targeting now. After some criticism, Facebook
Speaker 1: has made it possible for people to tweak their settings
Speaker 1: on the platform to bit targeted advertising, So you can
Speaker 1: change things so that the ads you get are more
Speaker 1: general and they're no longer hinging upon your identity or
Speaker 1: your behaviors. Not that Facebook isn't still collecting of these information.
Speaker 1: They are, it's just you're not seeing it in the
Speaker 1: effect of the advertising that appears on Facebook. But it's
Speaker 1: not always easy to spot these settings, and a lot
Speaker 1: of people just never bother to even check into it.
Speaker 1: And that suits Facebook just fine, because remember when I
Speaker 1: said Facebook can charge more for ads because of their
Speaker 1: high engagement, the fact that people spend so much time
Speaker 1: on Facebook. That gets boosted even more when Facebook can
Speaker 1: tell an advertiser that they're able to put their ads
Speaker 1: in front of the people who are most likely to
Speaker 1: respond to those ads. So not only are people spending
Speaker 1: more time on the platform, Facebook can tell the advertisers
Speaker 1: you want to you want to target this specific person
Speaker 1: because they're the one most likely to respond to your ad. Now,
Speaker 1: let me be clear, this doesn't have to be a
Speaker 1: bad thing necessarily. I mean, you might end up seeing
Speaker 1: ads that are really relevant to you and they could
Speaker 1: be really helpful. Maybe you would see something that you
Speaker 1: wouldn't have come across otherwise. But it can also come
Speaker 1: across as really invasive or creeping. But now let's go
Speaker 1: to something that is just a bad thing. Period See
Speaker 1: targeting ads to get your most likely customer. Sounds fairly
Speaker 1: on the up and up, except the practice can also
Speaker 1: be discriminatory. For example, let's say there's a big company
Speaker 1: and they own upscale apartment complexes in different cities, and
Speaker 1: this company wants to advertise on Facebook because it's opening
Speaker 1: up a brand new apartment building. And in the process,
Speaker 1: the company specifically opts to show the ad only to
Speaker 1: white people, because that's something Facebook used to allow advertisers
Speaker 1: to do. Facebook was allowing for racial discrimination in advertising. Now,
Speaker 1: if you took a bird's eye view of these practices,
Speaker 1: you would see some really ugly trends here. Ads for
Speaker 1: companies that were hiring fast food workers were disproportionately directed
Speaker 1: towards black users. Ads for companies hiring cleaners or nurses
Speaker 1: disproportionately targeted women users. The practice was reinforcing disparities in
Speaker 1: the job market. It was perpetuating and and and heightening
Speaker 1: these disparities. It was an effect making things worse. And
Speaker 1: this practice first came to light way back in sixteen,
Speaker 1: but it wasn't until twenty nineteen that Facebook was dealing
Speaker 1: with a lawsuit and the company promised that it would
Speaker 1: end the practice. The announcement also wasn't exactly transparent. In
Speaker 1: a post, the Facebook for Business division said that it
Speaker 1: was removing the option as part of its quote efforts
Speaker 1: to simplify and stream line are targeting options end quote,
Speaker 1: and that it would be quote removing multicultural affinity segments
Speaker 1: and encouraging advertisers to use other targeting options such as
Speaker 1: language or culture end quote. Multicultural affinity segments was the
Speaker 1: euphemism the company used to essentially talk about racial discrimination now.
Speaker 1: According to a Facebook insider named Kion Lvy, team members
Speaker 1: within Facebook had been pushing for the removal of these
Speaker 1: factors for advertisers for more than three years. In addition,
Speaker 1: it's not the only discrimination that people have faced when
Speaker 1: it comes to trying to do advertising on Facebook. One
Speaker 1: thing I didn't touch on earlier in this episode is
Speaker 1: how brands have been affected by the various tweaks to
Speaker 1: the news feed algorithm and the news feed itself. Brands
Speaker 1: can make pages, and users can visit the pages, and
Speaker 1: they can like those pages. And in the old days,
Speaker 1: if a business posted to their page, then that update
Speaker 1: would go out to a decent number of the followers
Speaker 1: who had liked that page. But Facebook tweaked the news
Speaker 1: feed a couple of times, and each time it would
Speaker 1: affect the organic reach of a business's post. So, for example,
Speaker 1: there is a text of Facebook page. I think. I
Speaker 1: mean I quit Facebook a couple of weeks ago, so
Speaker 1: I mean I assume it's still there, but it wasn't
Speaker 1: updated frequently. And I'll be up front with you why
Speaker 1: that is because there wasn't much point to updating the
Speaker 1: Facebook page due to the way the news feedworks. Posting
Speaker 1: to the text off page would mean only a small
Speaker 1: fraction of the people who were actually following that page
Speaker 1: would even see the update. So if a thousand people
Speaker 1: had liked the page, maybe only ten of them get
Speaker 1: the update. That's not a good return on investment. So
Speaker 1: ostensibly this was on an effort to deliver a better
Speaker 1: experience to users. You know, Zuckerberg always positioned this as
Speaker 1: saying the ideas they wanted the users to see more
Speaker 1: posts from the actual people they know, their friends and family,
Speaker 1: and fewer posts from businesses and media outlets, even though
Speaker 1: we should remember these were outlets and businesses that users
Speaker 1: had gone to and liked on Facebook, so presumably the
Speaker 1: posts from those entities were things that the users were
Speaker 1: interested in the first place. But what was really going
Speaker 1: on here was that Facebook was creating a market for itself.
Speaker 1: Why give away free access to users when you can
Speaker 1: create an incentive for businesses to pay for promoted posts,
Speaker 1: and that's what was really going on here. Facebook had
Speaker 1: created a system where brands felt the necessity for creating
Speaker 1: a Facebook page, and you had to have a face
Speaker 1: fcebook page. There are two billion people on Facebook, so
Speaker 1: you want to be where the people are, you gotta
Speaker 1: have a Facebook page. But to reach a significant percentage
Speaker 1: of the people who have actually gone to that page
Speaker 1: and liked it, you would also have to pay for
Speaker 1: that privilege. Now, I'm not going to argue against Facebook's
Speaker 1: strategy here. It kind of stinks if you happen to
Speaker 1: run a brand. But from Facebook's perspective, I can understand
Speaker 1: the reasoning. So while it kind of is tough if
Speaker 1: you're someone who's trying to reach your fans, uh, from
Speaker 1: Facebook's perspective, I get the I get the idea, I
Speaker 1: get the business case. However, that discrimination that we would
Speaker 1: see directed toward users would creep in again, this time
Speaker 1: towards advertisers. There's a band called Unsung Lily, which is
Speaker 1: an independent pop band. It's headed by a same sex couple,
Speaker 1: Frankie and Sarah Golding Young. These two are attempting to
Speaker 1: promote an album on Facebook this year, in because, like
Speaker 1: I think pretty much everyone in the world, the pandemic
Speaker 1: changed all of their plans for the year. They wouldn't
Speaker 1: be able to tour, they wouldn't be able to market
Speaker 1: their album the way they would typically do so, and
Speaker 1: so they decided to run and add on Facebook. But
Speaker 1: they also knew that if they relied solely on posting
Speaker 1: the the ad to the band's page, like if they
Speaker 1: just made a post on their fan page, the way
Speaker 1: Facebook serves up that kind of stuff means that they
Speaker 1: wouldn't reach nearly enough of their fans for it to
Speaker 1: make an impact. So they decided to do it as
Speaker 1: an paid ad instead. So they shot an ad, they
Speaker 1: put it together, they edited it, they submitted it. They
Speaker 1: received a rejection, and under the reason why the ad
Speaker 1: had been rejected, it said that the ad contained inappropriate
Speaker 1: sexually explicit content, except it didn't. What it did feature
Speaker 1: was an image of Sarah and Frank Key leaning into
Speaker 1: each other with their foreheads touching, kind of just an
Speaker 1: image of affection. There was nothing remotely sexual or explicit
Speaker 1: about this photograph. Now, the rejection notice didn't specify that
Speaker 1: the image was the reason for the rejection, so they
Speaker 1: decided they would run a test to see if, in
Speaker 1: fact that was the problem. First, they submitted an AD
Speaker 1: that had all the same content as the original piece,
Speaker 1: only with this one image swapped out for a quote
Speaker 1: unquote non romantic picture of the couple boom Facebook excepts
Speaker 1: the ad. To follow that up, they also submitted another ad.
Speaker 1: They still used the same video, the same copy, but
Speaker 1: they got a heterosexual couple making the same pose that
Speaker 1: they had made with the two four heads together, so
Speaker 1: it's a man and a woman foreheads touching. They just
Speaker 1: used that to replace their own image. Boom Facebook except
Speaker 1: that ad too. Okay, so I guess I don't have
Speaker 1: to explain that this is a really bad thing. The
Speaker 1: fact that Facebook ads deemed a heterosexual display of affection
Speaker 1: as perfectly acceptable and the same sex display of the
Speaker 1: exact same act of affection as offensive is beyond infuriating.
Speaker 1: The band contacted the American Civil Liberties Union, which facilitated
Speaker 1: some communication with Facebook. Facebook said, oh, no, no, no no,
Speaker 1: this whole thing was a mistake. And besides, the actual
Speaker 1: objectionable part wasn't that photograph. It was because of some
Speaker 1: of the dancing those in the video. But again, Facebook
Speaker 1: accepted two versions of the video that contained the dancing,
Speaker 1: It just didn't have that photograph of Sarah and Frankie,
Speaker 1: which seems pretty fishy to me. Meanwhile, the company continues
Speaker 1: to face criticism that it fails to curb truly objectionable
Speaker 1: stuff like hate speech. So hate speech spreads like easy
Speaker 1: on Facebook, but an ad that had a photograph of
Speaker 1: two women with their foreheads together was offensive. There are
Speaker 1: studies that are also showing that black users are disproportionately
Speaker 1: more likely to have their accounts suspended by automated moderating
Speaker 1: systems than white users are, which is another bad algorithm example.
Speaker 1: And there are real concerns that the targeting criteria Facebook
Speaker 1: continues to use exacerbate socioeconomic disparities in the real world.
Speaker 1: None of this is good news. Facebook has been under
Speaker 1: intense scrutiny recently from various governments around the world that
Speaker 1: have all floated variations of the possibility that Facebook could
Speaker 1: face some really big consequences down the road, like getting
Speaker 1: broken up. There are a lot of different entities that
Speaker 1: argue Facebook is a monopoly or is monopolistic, and it's
Speaker 1: pretty clear that Facebook and its incarnation as it exists
Speaker 1: right now really has some big problems to iron out,
Speaker 1: things that are affecting people in a truly negative way.
Speaker 1: These are all parts of the reason why I left Facebook.
Speaker 1: I did so for my own personal reasons, and I'm
Speaker 1: not advocating that anyone listening to this just go out
Speaker 1: and shut down your account right now. I'm not saying
Speaker 1: that for me that was the right decision. I needed
Speaker 1: to do it for my own mental health, honestly, So
Speaker 1: I felt like this was an important thing to talk about,
Speaker 1: because again, it's those algorithms that, at the end of
Speaker 1: the day, we're really just designed to optimize the amount
Speaker 1: of time people would spend on Facebook and the number
Speaker 1: and quality, or at least the variety of ads that
Speaker 1: they would see while they spent their time there. That
Speaker 1: was really the only thing that mattered to Facebook. It
Speaker 1: was otherwise kind of distanced from any of the content stuff.
Speaker 1: Content was not at all the concern. The concern was
Speaker 1: how long can we keep them there, how many ads
Speaker 1: can we show them, how much money can we get
Speaker 1: for those ads? That was really all that mattered. And
Speaker 1: now we're starting to see when you disassociate the content
Speaker 1: from the approach how that can have a profoundly negative
Speaker 1: impact on the world, and we're trying to get to
Speaker 1: the point where we figure out what to do next.
Speaker 1: I don't have the answers um other than I walked away.
Speaker 1: So hopefully people at Facebook will start to come up
Speaker 1: with ways to approach the business from a more ethical
Speaker 1: standpoint that will have less of a negative impact on
Speaker 1: the people who actually use the service, whether it's the
Speaker 1: advertisers or the end users. I certainly hope. So if
Speaker 1: you found this interesting, let me know if you have
Speaker 1: suggestions for future topics on tech stuff. Whether it's a company,
Speaker 1: a trend in technology, maybe it's a person in tech.
Speaker 1: Maybe it's a specific technology you've always wanted to know
Speaker 1: how it worked. Let me know. The best way to
Speaker 1: do that is clearly to go over to Twitter. Not
Speaker 1: that that's a perfect service, but that's a different podcast
Speaker 1: for a different time. But use the handle text stuff
Speaker 1: h s W and I'll talk to you again really soon.
Speaker 1: Text Stuff is an I Heart Radio production. For more
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