Speaker 1: Welcome to tech Stuff, a production from I Heart Radio.
Speaker 1: Hey there, and welcome to tech Stuff. I'm your host,
Speaker 1: Jonathan Strickland. I'm an executive producer with I Heart Radio
Speaker 1: and I love all things tech and I was listening
Speaker 1: to a recent episode of pod Save America's offline series
Speaker 1: in which journalist Charlie Warzel joined the show to talk
Speaker 1: about Facebook and its role in causing harm on a
Speaker 1: global scale, which inspired me to do this episode. Now,
Speaker 1: before we get started, I guess I should apologize for
Speaker 1: the somewhat click baity title of this episode. We're going
Speaker 1: to be exploring algorithms and their unintended consequences, and we're
Speaker 1: focusing on the Facebook algorithm. That is, the algorithm that
Speaker 1: determines what appears in your news feed. But algorithms by
Speaker 1: themselves are not necessarily good or evil on their own.
Speaker 1: You know. It's kind of like what Hamlet said, Now,
Speaker 1: there's nothing neither good nor bad, but thinking makes it so.
Speaker 1: So let's start just by defining what an algorithm is. So,
Speaker 1: an algorithm is essentially a set of rules or directions
Speaker 1: that a system follows in order to process information and
Speaker 1: produce results. And that's it. So it's just a set
Speaker 1: of rules. Let's use a really simple analogy to explain this.
Speaker 1: Let's say I've hired you to sit on a bench
Speaker 1: by a road. Say it's a road that gets decent
Speaker 1: but not heavy traffic, And I say it's your job
Speaker 1: to make a tally mark on a sheet of paper
Speaker 1: whenever a silver car drives past you along this road,
Speaker 1: and you're to ignore all other cars, only make a
Speaker 1: tally when a silver car goes by. I just, you know,
Speaker 1: want to see how many tally marks are there at
Speaker 1: the end of a certain amount of time. Let's say
Speaker 1: it's an hour, and I have given you an algorithm
Speaker 1: tally every single silver car that drives past you. So
Speaker 1: you observe the vehicles that drive by you, you follow
Speaker 1: the directions, and that's the whole concept right there. Now.
Speaker 1: I feel like a lot of folks, including myself, sometimes
Speaker 1: use the word algorithm as a kind of way to
Speaker 1: save a bit of time, But it also tends to
Speaker 1: create a gap in understanding. Like, you know, the word
Speaker 1: algorithm acts kind of like the curtain between Dorothy and
Speaker 1: the Wizard of Oz. You know something's going on back
Speaker 1: behind the curtain, but you can't actually see what it is,
Speaker 1: so we use the word algorithm to describe it, and
Speaker 1: then we just move on. Now. Part of the reason
Speaker 1: for that is that a lot of companies, big ones
Speaker 1: like Google and Facebook jealously guard their algorithms from critical view.
Speaker 1: To the outsider, it would be impossible to say whether
Speaker 1: the algorithm was working well or if it wasn't, because
Speaker 1: we don't necessarily know what the goal of the algorithm
Speaker 1: is in the first place. We know it is doing work,
Speaker 1: we know it's doing something, it's creating the results that
Speaker 1: we see, but we don't know if it's doing the
Speaker 1: best job at that. So this lack of transparency becomes
Speaker 1: a big issue in some cases, like with Facebook. And
Speaker 1: there are times when an algorithm is technically doing what
Speaker 1: it's supposed to do and it is doing it well
Speaker 1: by that definition, but that there are unintended consequences and
Speaker 1: sometimes really bad ones. I would argue that this is
Speaker 1: what we see with Facebook in particular. It's what's led
Speaker 1: the company Meta, you know, the company that owns Facebook,
Speaker 1: to get into hot water around the world because of
Speaker 1: issues like the spread of misinformation and hate speech. Now,
Speaker 1: to be clear, I'm not saying Facebook engineered an algorithm
Speaker 1: to spread that kind of bad content. Rather, Facebook engineers
Speaker 1: create a system that prioritizes that kind of content because
Speaker 1: that content fulfills other goals. So let's back up a
Speaker 1: bit and really get to grips with what's actually going on. First,
Speaker 1: let us consider what Facebook started out as, because it
Speaker 1: was a much less expansive and influential site when it
Speaker 1: launched way back in two thousand four. Back then, it was,
Speaker 1: in Mark Zuckerberg's own estimation, a tool for Harvard students,
Speaker 1: presumably mostly male ones, to rank the quote unquote hot
Speaker 1: girls on campus. So Facebook, the site has always been
Speaker 1: a creep. It's just now it's a much older and
Speaker 1: much more influential creep. Anyway, running a site costs money.
Speaker 1: There are hosting services and bandwidth fees and other stuff
Speaker 1: that you have to cover, so there needed to be
Speaker 1: a way to offset the costs of running this pretty
Speaker 1: basic social network. In April of two thousand four, Zuckerberg
Speaker 1: introduced flyers and you know f L y e r s.
Speaker 1: These were essentially banner ads on Facebook's homepage. So these
Speaker 1: are the same kind of banner ads that would appear,
Speaker 1: you know, on the top, bottom or sides of any
Speaker 1: website that you visited. The ads were really mostly for
Speaker 1: local businesses, So this was really small potatoes stuff, but
Speaker 1: it meant that there was some money coming in that
Speaker 1: would help offset Facebook's costs. Facebook group pretty rapidly and
Speaker 1: the company received some investment capital, but it needed to
Speaker 1: establish a way to generate more revenue. See, in the
Speaker 1: world of startups, there are a couple of different pathways
Speaker 1: you can try to take. Actually there's more than a couple,
Speaker 1: but there's really only a couple of successful pathways. One
Speaker 1: is to become attractive enough as a product, service, or
Speaker 1: business that some other bigger fish is going to come
Speaker 1: along and scoop you up in an acquisition and you'll
Speaker 1: cash out with millions of dollars. In fact, that fuels
Speaker 1: a ton of the startup culture these days, and I've
Speaker 1: talked about it in the past about how I think
Speaker 1: it's a pretty dangerous and unhealthy trend. But the other
Speaker 1: way is to build a business that generates more money
Speaker 1: and revenue than it costs to operate the business, and
Speaker 1: to build it in such a way that you can
Speaker 1: scale up the business as it grows, making more money
Speaker 1: while also spending more to maintain a larger business. This
Speaker 1: is a really hard thing to do. A lot of
Speaker 1: companies struggle with it, and I'm guessing this is why
Speaker 1: the acquisition culture runs so strong in startups. It's not
Speaker 1: easy to be seen as important enough to acquire. That's
Speaker 1: I'm not trying to downplay that. It is tough. You've
Speaker 1: got to make something that is flashy enough and and
Speaker 1: potentially important enough for someone else to come along and
Speaker 1: say we want that. But that can be easier than
Speaker 1: creating a business model that supports itself throughout the various
Speaker 1: phases of a company's growth. That is really hard to
Speaker 1: do well. Facebook was looking to go that second route,
Speaker 1: you know, the actual business route, as opposed to getting acquired,
Speaker 1: and in November two thousand seven, the site introduced Facebook
Speaker 1: Ads Now. That product had a few different facets. One
Speaker 1: was that businesses would be allowed to create Facebook pages
Speaker 1: that could operate in ways similar to an actual human
Speaker 1: beings Facebook page works, and that would give folks the
Speaker 1: chance to quote unquote like a business that they were
Speaker 1: interested in. Another facet was the Facebook Marketplace, which exists
Speaker 1: to this day, and a third was a product called Beacon. Now.
Speaker 1: This product would be one of the first to inspire
Speaker 1: legal action against Facebook. You see, Beacon was a tool
Speaker 1: that would collect data from external websites sites that were
Speaker 1: not Facebook, and send that data back to Facebook. These
Speaker 1: were partnered websites companies that had partnered with Facebook to
Speaker 1: be part of this program. So if you went online
Speaker 1: and you started shopping for shoes, and if you were visiting,
Speaker 1: you know, these sites that were part of this Beacon program,
Speaker 1: your activities would be sent back to Facebook for the
Speaker 1: purposes of targeted advertising, which meant the next time you
Speaker 1: jumped on Facebook, you would start seeing shoe adds. The
Speaker 1: problem was Facebook didn't alert users to this program, nor
Speaker 1: did it allow people the chance to opt out of
Speaker 1: the service, and so Facebook was tracking users even if
Speaker 1: they weren't actively connected to Facebook at the time, as
Speaker 1: long as they were logged in and they were, you know,
Speaker 1: not necessarily logged in and active on the site, but
Speaker 1: like they hadn't logged out of their account, then this
Speaker 1: activity would continue to be tracked as they went to
Speaker 1: other sites. After users brought a class action lawsuit against Facebook,
Speaker 1: the company shut down Beacon in two thousand nine. That
Speaker 1: doesn't mean Facebook said goodbye to targeted ads. Far from it,
Speaker 1: and that brings us to something really important. Facebook makes
Speaker 1: the majority of its revenue from advertising, and ads only
Speaker 1: make money if there are people to see them. It
Speaker 1: would not make any sense to put up a billboard
Speaker 1: in the middle of Antarctica, right, I mean, no one
Speaker 1: would ever see the billboard. That would just be a
Speaker 1: waste of money. So you've got to put ads where
Speaker 1: people are going to see them. So Facebook's business model
Speaker 1: revolves around getting as many people to see as many
Speaker 1: ads as is possible. So for Facebook, that means getting
Speaker 1: as many people to log into Facebook as they can
Speaker 1: and then keeping those people on Facebook as much as
Speaker 1: is possible. That's the end goal, because it means serving
Speaker 1: more ads to more people. Well, we'll talk about stuff
Speaker 1: like engagement a bit later, but really engagement isn't the
Speaker 1: important bit like that engagement on Facebook. Like, if if
Speaker 1: Facebook could guarantee that it would get the same number
Speaker 1: of ads viewed without worrying about engagement, they would drop
Speaker 1: the whole thing about engagement, trust me. So the important
Speaker 1: bit is really just getting eyeballs on ads. That's it. Now,
Speaker 1: you could argue that the sole purpose of Facebook, at
Speaker 1: least from the business standpoint is just that getting eyes
Speaker 1: on ads. The features, the connectivity, all of that stuff
Speaker 1: is just the bit that brings folks in to use
Speaker 1: the platform. But from a revenue side, it's just about
Speaker 1: getting as many folks to look at ads as as possible.
Speaker 1: That's where the algorithm comes into play. And when people
Speaker 1: talk about Facebook algorithms, they typically mean a couple of
Speaker 1: different ones. One is the way that Facebook determines what
Speaker 1: shows up in a user's news feed. What do you
Speaker 1: see when you log into Facebook. Longtime Facebook users often
Speaker 1: limit the fact that the site no longer posts stuff
Speaker 1: in reverse chronological order on your news feed. You used
Speaker 1: to be able to really do that for real, Like
Speaker 1: you would see the most recent posts at the top,
Speaker 1: and you could just scroll down and you go back
Speaker 1: in time. You would see the older posts, like the
Speaker 1: from most recent to the oldest, and you could get
Speaker 1: caught up. Like you could actually do that, But that
Speaker 1: means that your time on Facebook would be kept too
Speaker 1: fairly short bursts unless you've just got a lot of
Speaker 1: chatty friends who are constantly posting, And since revenue comes
Speaker 1: from having more people seeing the site for as long
Speaker 1: as possible, that's not great for Facebook, right That's why
Speaker 1: the reverse chronological order is not a huge priority for Facebook,
Speaker 1: because even though users might love it, they wouldn't necessarily
Speaker 1: spend as much time on the platform. So the company
Speaker 1: set out to make algorithms that would select content across
Speaker 1: your friends and interests. In an effort to keep users
Speaker 1: glued to the site longer. You might end up missing
Speaker 1: stuff from your friends. In fact, I guarantee that's happening
Speaker 1: to you if you are on Facebook, that you are
Speaker 1: not seeing stuff that some of your friends are posting
Speaker 1: because the algorithm isn't promoting it to you, And it's
Speaker 1: because the algorithm chose to promote something else for you
Speaker 1: to see instead of the stuff that your friends are posting.
Speaker 1: We can also talk about algorithms in the sense of
Speaker 1: advertising algorithms, that being the algorithms that determine which ads
Speaker 1: get displayed to a specific user, But the news feed
Speaker 1: algorithm tends to be the big one that most people
Speaker 1: talk about when they say the Facebook algorithm. So this
Speaker 1: has actually gotten Facebook into trouble a few times, even
Speaker 1: before we started seeing stuff like the Cambridge Analytica scandal,
Speaker 1: or we started seeing the various times that that Congress
Speaker 1: has called Facebook executives to testify about stuff like misinformation
Speaker 1: and hate speech. Way back in two thousand fifteen, content
Speaker 1: sites in general saw a seismic shift because of something
Speaker 1: Facebook did, and this would end up disrupting the entire
Speaker 1: industry of online content, from news organizations to entertainment sites.
Speaker 1: And that shift had a name. It was called pivot
Speaker 1: to video. Just saying those words fills me with dread.
Speaker 1: So making content is hard. I do it nearly every day.
Speaker 1: It can be grueling, you know, writing up long pieces
Speaker 1: takes a lot of time and research and a lot
Speaker 1: of specialized talent. If you want to do it well,
Speaker 1: I mean you could just be a content farm and
Speaker 1: dump endless numbers of articles that are hastily written, badly researched,
Speaker 1: and poorly edited. You can do that, Uh it doesn't
Speaker 1: you know. You can try and make it up in volume,
Speaker 1: but if you go the quality route, you tend to
Speaker 1: see better results. Uh. And in two thousand and fifteen,
Speaker 1: we saw a convergence of several things that would prompt
Speaker 1: a lot of content companies to change the way they
Speaker 1: do business. First, AD revenue for owned and operated sites
Speaker 1: was hurting. So that by that, I mean if you
Speaker 1: were a media company and you had your own website,
Speaker 1: you were starting to see lower amounts of traffic, which
Speaker 1: meant you were also seeing lower payouts and ads. It
Speaker 1: was probably devaluing the ads that were on your site.
Speaker 1: In other words, when companies make these ad deals, they
Speaker 1: negotiate with the advertisers a certain amount per view or
Speaker 1: per click or per action or whatever the criteria are,
Speaker 1: and the as a whole, like, if you're doing really well,
Speaker 1: then you can demand a higher rate. It's kind of
Speaker 1: like how in the US commercials during the Super Bowl
Speaker 1: are incredibly expensive because everyone knows that that's where a
Speaker 1: ton of attention happens to be focused at that particular time,
Speaker 1: So the ad space on a game of the super
Speaker 1: Bowl ends up being really, really, really valuable. The same
Speaker 1: sort of thing. If your site is doing really well,
Speaker 1: then you can command a higher price. But at this point,
Speaker 1: content companies were starting to have difficulty. They were seeing
Speaker 1: there there the value of their ad deals going down,
Speaker 1: not up. Traffic was going down, not up, And a
Speaker 1: lot of sites are dependent upon stuff like search engines
Speaker 1: as well. If you rank high in Google, that's really important.
Speaker 1: The Google algorithm is another example of an algorithm that
Speaker 1: you could argue could be evil, but it means that
Speaker 1: there are more chances for people to find your work.
Speaker 1: If you're ranking high in search, right, someone searches a
Speaker 1: particular term, your site comes up. That's great for you,
Speaker 1: and thus more people will end up going to your
Speaker 1: site and seeing the ads that are on your site,
Speaker 1: and you generate revenue. We saw some companies experiment with
Speaker 1: stuff like paywalls, you know, getting away from the whole
Speaker 1: advertising thing and saying, well, we will instead uh invite
Speaker 1: users to pay a subscription to get our content. A
Speaker 1: lot of users balked at that because they were used
Speaker 1: to getting their content for quote unquote free, though we
Speaker 1: know it wasn't really for free. It was just that
Speaker 1: the money wasn't coming directly out of the user's pocket
Speaker 1: in those cases. Now, a big part of the problem
Speaker 1: was that rather than go on owned and operated sites,
Speaker 1: a lot of people were just gobbling up content on
Speaker 1: places like Facebook. So social network platforms became a competitive
Speaker 1: marketplace for content creators, with many trying to find ways
Speaker 1: to craft their work. Uh. Just so that it would
Speaker 1: be effective when you share it on social media doesn't
Speaker 1: mean it would be the best work you've ever made,
Speaker 1: but rather you were trying to make stuff that was
Speaker 1: share able. Oh man, I remember this era and it
Speaker 1: was bleak anyway. At the same time, you had smartphone
Speaker 1: companies that were really coming into their own I mean,
Speaker 1: the smartphone was starting to dominate the computer space. They
Speaker 1: had premiered less than a decade earlier, but the swift
Speaker 1: proliferation of smartphones meant that people were starting to consume
Speaker 1: content a little bit differently than they had before. A
Speaker 1: good site would optimize for mobile access, and we started
Speaker 1: seeing people say that the future of the web was
Speaker 1: really and how it would cater to mobile devices, and
Speaker 1: we saw various content sites looking for ways to cut costs.
Speaker 1: This was the other big element here. And one way
Speaker 1: is you can really reduce your writing staff. You can
Speaker 1: have layoffs, but you still need to make a lot
Speaker 1: of content or else you have no inventory to sell
Speaker 1: to advertisers, and then the revenue drives up. And that's
Speaker 1: what would set the stage for a really big problem.
Speaker 1: Alex lay More after we take this short break. Okay,
Speaker 1: this all brings us up to the pivoting to video movement.
Speaker 1: So in early Facebook announced a shift to video, indicating
Speaker 1: that the platform would prioritize video content from third party publishers,
Speaker 1: and that implies that it would simultaneously de emphasize content
Speaker 1: that wasn't videos. So, if you were a third party
Speaker 1: publisher and you were making stuff like articles like how
Speaker 1: staff works is a great example. I used to write
Speaker 1: for how Stuff Works. And if you were doing these
Speaker 1: articles and you were hoping that at least some of
Speaker 1: your traffic was going to come from social networking sites,
Speaker 1: you hear this news and you think, oh, well, now,
Speaker 1: even if I write a great article and if not
Speaker 1: given a fantastic title and it's really share able, the
Speaker 1: Facebook algorithm is going to de emphasize it because it's
Speaker 1: not video. It's written con tent, and the Facebook algorithm
Speaker 1: has decided to promote video content instead. Uh. There were
Speaker 1: a lot of content companies that legitimately got real nervous
Speaker 1: about this for good reason. So the message appeared to be,
Speaker 1: if you want your content to be seen on Facebook,
Speaker 1: you should probably put it in short form video content form.
Speaker 1: And now, now why would Facebook even do this? Well,
Speaker 1: one big reason is that if you click on a
Speaker 1: link in Facebook to go read an article, you leave Facebook.
Speaker 1: And since the revenue model for Facebook is again all
Speaker 1: about keeping as many eyeballs on the site for as
Speaker 1: long as possible. That means Facebook hates that but video
Speaker 1: and Facebook could build a media player, and they did
Speaker 1: that could work within the news feed and just host
Speaker 1: videos natively on the Facebook site so you didn't go
Speaker 1: away from Facebook to watch the videos. They played within
Speaker 1: the Facebook page, so people could just click on those
Speaker 1: videos and watch them and not leave face book. Facebook
Speaker 1: loved that idea. If the user news feeds just filled
Speaker 1: up with video after video and all of them called,
Speaker 1: you know, Facebook home, even though the actual content was
Speaker 1: coming from other companies, well, that would just work out
Speaker 1: fine for Facebook. The shift to video would have an
Speaker 1: enormous impact on content companies. Several companies began cutting back
Speaker 1: on staff, keeping a small group of writers and editors
Speaker 1: whose main job wasn't to publish articles, but rather write
Speaker 1: and produce as many videos as possible. I saw this
Speaker 1: happen in front of my own eyes. But that's a
Speaker 1: story for a different time. Anyway, a lot of talented
Speaker 1: people found themselves out of a job as dozens of
Speaker 1: content companies made the pivot to video. You also heard
Speaker 1: a lot of stories about this is kind of around
Speaker 1: the same time where the perception of journalism was taking
Speaker 1: a pretty big hit, like people were starting to say
Speaker 1: that journalism was dead. That kind of ties into this
Speaker 1: too well. Anyway, companies chose to pivot to video in
Speaker 1: part because they could have a smaller video department than
Speaker 1: a writing staff. Often that would also involve bringing in
Speaker 1: new employees out of college to work on the video team,
Speaker 1: because new employees often have lower salaries than more established
Speaker 1: employees who might be let go. But companies wouldn't have
Speaker 1: done this unless the revenue side was also in place, right, Like,
Speaker 1: it's one thing to cut costs, but it means nothing
Speaker 1: if you do that if you're not also bringing in
Speaker 1: the cash. You have to be bringing in revenue. And
Speaker 1: the problem was the industry was responding to a misrepresentation
Speaker 1: of the facts uh an error in other words, or,
Speaker 1: if you are particularly cynical, a lie. See. In January,
Speaker 1: Facebook presented some pretty startling figures saying that Facebook users
Speaker 1: were watching more than a billion videos per day. What's more,
Speaker 1: the company said that users were watching tons of ads
Speaker 1: in the videos in the process, that, in other words,
Speaker 1: producing videos to publish on Facebook would be a great
Speaker 1: way to show a lot of ads to a lot
Speaker 1: of people, and the revenue would come flowing in for
Speaker 1: everyone concerned. But things were not quite playing out that way.
Speaker 1: Some companies had gone so far as to ditch their
Speaker 1: owned and operated sites and they relied exclusively on building
Speaker 1: out content to live on sites like Facebook, which I
Speaker 1: need to say, in case you didn't pick it up
Speaker 1: from my tone, is a terrible idea. They were trying
Speaker 1: to respond to a rapidly shifting landscape, so in their
Speaker 1: minds they were saying, well, if no one's coming to
Speaker 1: our website, then we're just wasting money maintaining it, so
Speaker 1: let's just change over to Facebook. So the pivot to
Speaker 1: video phrase would also end up taking on an additional meaning.
Speaker 1: A couple of them, for example, one of them was
Speaker 1: a cheeky way to refer to layoffs. You know, layoffs
Speaker 1: are coming up. It's because the company is quote unquote
Speaker 1: pivoting to video. Um, so that that's kind of tells
Speaker 1: you all you need to know about that particular phrase,
Speaker 1: like it became a euphemism. Meanwhile, the revenue numbers weren't
Speaker 1: actually matching up with what was to be expected based
Speaker 1: upon Facebook's kind of sales pitch to the industry, and
Speaker 1: in February two sixteen, Facebook essentially said, whoops are bad.
Speaker 1: Remember when we talked about how many ads the average
Speaker 1: person was watching in videos, It turns out we overestimated
Speaker 1: that a bit, perhaps by as much as eighty percent.
Speaker 1: So imagine for a moment that you want to open
Speaker 1: up a business. Let's say it's a bakery and you're
Speaker 1: looking for the perfect place to locate it. And you
Speaker 1: have a realtor who tells you that they have a
Speaker 1: spot that's in an area that gets a ton of
Speaker 1: foot traffic, and it's ideal for your location, it's in
Speaker 1: your price range, it's ready to go. So you signed
Speaker 1: the deal, you rent out the spot, you build out
Speaker 1: your bakery. But then you find out the realtor quote
Speaker 1: unquote or estimated the foot traffic by That would be
Speaker 1: a huge blow to your bakery business, right, I mean, like,
Speaker 1: now you don't have that foot traffic to depend upon
Speaker 1: to get customers. It's gonna be way harder. Doesn't mean
Speaker 1: that you've necessarily outright failed, but you're not going to
Speaker 1: have the path to success you thought you were. You
Speaker 1: might not even be able to stay in business. Well,
Speaker 1: here you had all these advertising companies that had banked
Speaker 1: on this, and all these content companies that had put
Speaker 1: all their eggs in the Facebook video basket. Some of
Speaker 1: the content companies no longer had their own websites, so
Speaker 1: they had really decided to throw all in on short
Speaker 1: video content that being the future of content creation. And
Speaker 1: it turned out that Facebook had fudged, or at the
Speaker 1: very least misinterpreted the numbers. A lawsuit in two thousand
Speaker 1: eighteen alleged that Facebook learned of this overestimation error earlier
Speaker 1: but kept it a secret, not admitting to the problem
Speaker 1: until it became unavoidable. In fact, the lawsuit alleged that
Speaker 1: the overestimation wasn't six like you know, Facebook, uh. The
Speaker 1: argument was that they or Facebook had said that it
Speaker 1: accidentally overstated the numbers of people who are watching ads
Speaker 1: by six. The lawsuits said, no, no, no, it was
Speaker 1: more like you you misrepresented it by a hundred fifty
Speaker 1: to nine hundred percent, drastically overstating how many people were
Speaker 1: watching ads in these little videos. Facebook would eventually settle
Speaker 1: with advertisers out of court, agreeing to pay around forty
Speaker 1: million dollars to the advertisers, but the content companies were
Speaker 1: kind of left in the lurch. Now, during this era,
Speaker 1: from around late two thousand fourteen to two thousand sixteen
Speaker 1: or so, Facebook's algorithm was favoring video over other types
Speaker 1: of content. But since people weren't actually watching an endless
Speaker 1: stream of videos with ads, that meant that the strategy
Speaker 1: of video wasn't working. It wasn't working for the content companies,
Speaker 1: and more importantly, for Facebook, it wasn't working for Facebook.
Speaker 1: It wasn't keeping people on Facebook the way they wanted
Speaker 1: it to, and so the company would change its algorithm.
Speaker 1: Now you could say that Facebook pivoted away from video. Meanwhile,
Speaker 1: all those companies were, you know, left behind. And granted,
Speaker 1: there were tons of folks who had been saying, you know,
Speaker 1: don't do this, and then they could say I told
Speaker 1: you so to the people that were relying on a
Speaker 1: third party. You know, there are a lot of people
Speaker 1: who say that's a bad idea to rely on a
Speaker 1: third party for distributing your content, that if you don't
Speaker 1: own it, when something changes your you can be hurt.
Speaker 1: And this happens all the time. It happens with Facebook,
Speaker 1: it happens with Google, it happens with YouTube. Every time
Speaker 1: there's a change in the algorithm, you'll hear about how
Speaker 1: certain sites benefit or certain content creators benefit and others suffer.
Speaker 1: But you know the fact is that a ton of
Speaker 1: folks jumped on that bandwagon already and they were all
Speaker 1: hit negatively by this whole uh shift. Anyway, let's talk
Speaker 1: about what Facebook's shift in its algorithm actually meant. Now.
Speaker 1: I have to talk about this kind of in vague
Speaker 1: and high level ways because Facebook, like Google, is not
Speaker 1: transparent about its algorithms. Now we know a lot of
Speaker 1: stuff because of the leaked internal documents that came to
Speaker 1: light recently, but the company has never been super upfront
Speaker 1: with how much you know or how it determines the
Speaker 1: content you've seen on your news feed. Generally speaking, Facebook
Speaker 1: shifted its focus towards content that quote unquote drives engagement.
Speaker 1: That is, content that seems to inspire people to interact
Speaker 1: with that content in some way, like leaving a comment
Speaker 1: or clicking like or dislike, or sharing a post of
Speaker 1: Facebook really loves it when people share posts. The actual
Speaker 1: content of the post doesn't matter to Facebook. They are
Speaker 1: content agnostic when it comes to that. What matters to
Speaker 1: Facebook is that people are engaging with that content and
Speaker 1: thus spending more time on the platform. That yeah, that's
Speaker 1: what it really boils down to. If you're engaging in content,
Speaker 1: it means you're still on Facebook. You haven't left. And
Speaker 1: like I said in the beginning, at the end of
Speaker 1: the day, that's what it's all about. Facebook's just concerned
Speaker 1: with keeping as many people on the platform for as
Speaker 1: long as possible and that's it. So promoting material that
Speaker 1: gets people to spend more time on the platform just
Speaker 1: makes sense from that business perspective. Unfortunately, one of the
Speaker 1: crappy things about humans is that we tend to respond
Speaker 1: with or to outrage more readily than just about anything else.
Speaker 1: If something makes you mad, you're way more likely to
Speaker 1: act on that, and a lot of posts that quote
Speaker 1: unquote drive engagement are really all about outrage from different perspectives.
Speaker 1: Like a post could be about how a certain group
Speaker 1: of people are awful. Whether those people are awful or
Speaker 1: not doesn't matter. It's the fact that someone has made
Speaker 1: a post saying that. That's what matters. So the people
Speaker 1: who agree with the post, who might harbor strong negative
Speaker 1: feelings about the people who are mentioned in the post,
Speaker 1: they chime in others who sympathize with the people you
Speaker 1: singled out, maybe they are members of that group. They
Speaker 1: leap to the defense or they go on a counter
Speaker 1: attack against the person who posted it. There's enough outrage
Speaker 1: to go around, so you end up with a bunch
Speaker 1: of angry people waging battles across Facebook comments sections, and
Speaker 1: the algorithm, seeing that certain posts are generating a ton
Speaker 1: of quote unquote engagement, steps it up to promote those
Speaker 1: posts into more news feeds and thus spreads them further
Speaker 1: and wider. Because if the engagement is going up, it
Speaker 1: means more people are spending more time on Facebook, so
Speaker 1: there are more ads to serve. Now there's a lot
Speaker 1: going on here from a sociological standpoint, right. I mean,
Speaker 1: we've seen hates speech, racism, and misogyny spread like wildfire
Speaker 1: across Facebook. And while the battles in the comments rage,
Speaker 1: the algorithm just keeps stirring things up. We have to
Speaker 1: remember there are real world consequences to this online activity.
Speaker 1: People and vulnerable populations can be made to feel unsafe.
Speaker 1: That's a powerful and destructive thing. Folks can be driven
Speaker 1: to extremist views, joining echo chambers that reinforce beliefs and
Speaker 1: stereotypes that are outright harmful. People who are neither targeted
Speaker 1: nor pulled into groupthink might find themselves just distressed over
Speaker 1: the whole thing. It's pretty ugly stuff. And this is
Speaker 1: how misinformation and hate speech takes hold on Facebook. The algorithm,
Speaker 1: which is again content agnostic, recognizes that whatever is being
Speaker 1: posted is effective, and that's all that really matters, so
Speaker 1: we get an amplification chamber. Now, don't think anyone at
Speaker 1: Facebook necessarily saw this coming, at least not early on,
Speaker 1: or that the folks who worked on the algorithm intended
Speaker 1: it to spread hard, full material in a way that
Speaker 1: is alarmingly effective. I think they just didn't bank on
Speaker 1: human nature being what it is, or the fact that
Speaker 1: you have certain agents out there, Russian backed and Chinese
Speaker 1: backed agents who, once they figured out how to game
Speaker 1: the system, would flood Facebook with posts designed to drive
Speaker 1: engagement and spread misinformation and thus get caught up in
Speaker 1: this algorithm promotion and spread harmful messages. But the fact
Speaker 1: remains that this is what we're seeing play out. Facebook
Speaker 1: has attempted to address this with various content moderation strategies,
Speaker 1: but the company does so while also trying to walk
Speaker 1: a fine line and not trigger criticism from various sources
Speaker 1: such as the conservative right. The fear is that too
Speaker 1: much moderation will be perceived as censorship, and that the
Speaker 1: company is actively trying to silence conservative voices. Facebook has
Speaker 1: been the target of such criticism on multiple occasions, so
Speaker 1: the solution tends to be to use a very light
Speaker 1: touch when moderating content. Meanwhile, the messages continue to populate
Speaker 1: Facebook users news feeds. Now. I called this episode the
Speaker 1: evil Algorithm, And again, I don't necessarily think an algorithm
Speaker 1: is on its own evil, but I do think continuing
Speaker 1: to rely on an algorithm that is demonstrably causing harm
Speaker 1: is pretty darn evil. At the very least, it is
Speaker 1: unethical and irresponsible. However, you know, again, it's like at
Speaker 1: the very heart of Facebook's business strategy. And that was
Speaker 1: something that that Charlie was saying on Pod Save America
Speaker 1: that the very core of Facebook's purpose, like it's it's
Speaker 1: mission as far as a business is concerned, is at
Speaker 1: odds with you know, not causing harm, like that those
Speaker 1: two things can't really coexist because of just the way
Speaker 1: it has evolved from this site. That was meant to
Speaker 1: rank the attractiveness of female students at Harvard. Who would
Speaker 1: have thought that's such a thing could go so horribly wrong. Anyway,
Speaker 1: that's it for this episode. I really wanted to lay
Speaker 1: it out because I feel like when we talk about algorithms,
Speaker 1: we get so so lucy goosey with our words that
Speaker 1: it just becomes a like a blanket term that doesn't
Speaker 1: really mean anything. If you have suggestions for topics I
Speaker 1: should cover on future episodes of tech Stuff, please reach
Speaker 1: out to me. The best way to do that is
Speaker 1: over on Twitter. To handle for the show is text
Speaker 1: stuff hs W and I'll talk to you again really soon.
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