The Facebook “It’s Not Our Fault” Study

Today in Science, members of the Facebook data science team released a provocative study about adult Facebook users in the US “who volunteer their ideological affiliation in their profile.” The study “quantified the extent to which individuals encounter comparatively more or less diverse” hard news “while interacting via Facebook’s algorithmically ranked News Feed.”*

  • The research found that the user’s click rate on hard news is affected by the positioning of the content on the page by the filtering algorithm. The same link placed at the top of the feed is about 10-15% more likely to get a click than a link at position #40 (figure S5).
  • The Facebook news feed curation algorithm, “based on many factors,” removes hard news from diverse sources that you are less likely to agree with but it does not remove the hard news that you are likely to agree with (S7). They call news from a source you are less likely to agree with “cross-cutting.”*
  • The study then found that the algorithm filters out 1 in 20 cross-cutting hard news stories that a self-identified conservative sees (or 5%) and 1 in 13 cross-cutting hard news stories that a self-identified liberal sees (8%).
  • Finally, the research then showed that “individuals’ choices about what to consume” further limits their “exposure to cross-cutting content.” Conservatives will click on only 17% a little less than 30% of cross-cutting hard news, while liberals will click 7% a little more than 20% (figure 3).

My interpretation in three sentences:

  1. We would expect that people who are given the choice of what news they want to read will select sources they tend to agree with–more choice leads to more selectivity and polarization in news sources.
  2. Increasing political polarization is normatively a bad thing.
  3. Selectivity and polarization are happening on Facebook, and the news feed curation algorithm acts to modestly accelerate selectivity and polarization.

I think this should not be hugely surprising. For example, what else would a good filter algorithm be doing other than filtering for what it thinks you will like?

But what’s really provocative about this research is the unusual framing. This may go down in history as the “it’s not our fault” study.

Facebook: It’s not our fault.

I carefully wrote the above based on my interpretation of the results. Now that I’ve got that off my chest, let me tell you about how the Facebook data science team interprets these results. To start, my assumption was that news polarization is bad.  But the end of the Facebook study says:

“we do not pass judgment on the normative value of cross-cutting exposure”

This is strange, because there is a wide consensus that exposure to diverse news sources is foundational to democracy. Scholarly research about social media has–almost universally–expressed concern about the dangers of increasing selectivity and polarization. But it may be that you do not want to say that polarization is bad when you have just found that your own product increases it. (Modestly.)

And the sources cited just after this quote sure do say that exposure to diverse news sources is important. But the Facebook authors write:

“though normative scholars often argue that exposure to a diverse ‘marketplace of ideas’ is key to a healthy democracy (25), a number of studies find that exposure to cross-cutting viewpoints is associated with lower levels of political participation (22, 26, 27).”

So the authors present reduced exposure to diverse news as a “could be good, could be bad” but that’s just not fair. It’s just “bad.” There is no gang of political scientists arguing against exposure to diverse news sources.**

The Facebook study says it is important because:

“our work suggests that individuals are exposed to more cross-cutting discourse in social media they would be under the digital reality envisioned by some

Why so defensive? If you look at what is cited here, this quote is saying that this study showed that Facebook is better than a speculative dystopian future.*** Yet the people referred to by this word “some” didn’t provide any sort of point estimates that were meant to allow specific comparisons. On the subject of comparisons, the study goes on to say that:

“we conclusively establish that…individual choices more than algorithms limit exposure to attitude-challenging content.”

compared to algorithmic ranking, individuals’ choices about what to consume had a stronger effect”

Alarm bells are ringing for me. The tobacco industry might once have funded a study that says that smoking is less dangerous than coal mining, but here we have a study about coal miners smoking. Probably while they are in the coal mine. What I mean to say is that there is no scenario in which “user choices” vs. “the algorithm” can be traded off, because they happen together (Fig. 3 [top]). Users select from what the algorithm already filtered for them. It is a sequence.**** I think the proper statement about these two things is that they’re both bad — they both increase polarization and selectivity. As I said above, the algorithm appears to modestly increase the selectivity of users.

The only reason I can think of that the study is framed this way is as a kind of alibi. Facebook is saying: It’s not our fault! You do it too!

Are we the 4%?

In my summary at the top of this post, I wrote that the study was about people “who volunteer their ideological affiliation in their profile.” But the study also describes itself by saying:

“we utilize a large, comprehensive dataset from Facebook.”

“we examined how 10.1 million U.S. Facebook users interact”

These statements may be factually correct but I found them to be misleading. At first, I read this quickly and I took this to mean that out of the at least 200 million Americans who have used Facebook, the researchers selected a “large” sample that was representative of Facebook users, although this would not be representative of the US population. The “limitations” section discusses the demographics of “Facebook’s users,” as would be the normal thing to do if they were sampled. There is no information about the selection procedure in the article itself.

Instead, after reading down in the appendices, I realized that “comprehensive” refers to the survey research concept: “complete,” meaning that this was a non-probability, non-representative sample that included everyone on the Facebook platform. But out of hundreds of millions, we ended up with a study of 10.1m because users were excluded unless they met these four criteria:

  1. “18 or older”
  2. “log in at least 4/7 days per week”
  3. “have interacted with at least one link shared on Facebook that we classified as hard news”
  4. “self-report their ideological affiliation” in a way that was “interpretable”

That #4 is very significant. Who reports their ideological affiliation on their profile?

add your political views

It turns out that only 9% of Facebook users do that. Of those that report an affiliation, only 46% reported an affiliation in a way that was “interpretable.” That means this is a study about the 4% of Facebook users unusual enough to want to tell people their political affiliation on the profile page. That is a rare behavior.

More important than the frequency, though, is the fact that this selection procedure confounds the findings. We would expect that a small minority who publicly identifies an interpretable political orientation to be very likely to behave quite differently than the average person with respect to consuming ideological political news.  The research claims just don’t stand up against the selection procedure.

But the study is at pains to argue that (italics mine):

“we conclusively establish that on average in the context of Facebook, individual choices more than algorithms limit exposure to attitude-challenging content.”

The italicized portion is incorrect because the appendices explain that this is actually a study of a specific, unusual group of Facebook users. The study is designed in such a way that the selection for inclusion in the study is related to the results. (“Conclusively” therefore also feels out of place.)

Algorithmium: A Natural Element?

Last year there was a tremendous controversy about Facebook’s manipulation of the news feed for research. In the fracas it was revealed by one of the controversial study’s co-authors that based on the feedback received after the event, many people didn’t realize that the Facebook news feed was filtered at all. We also recently presented research with similar findings.

I mention this because when the study states it is about selection of content, who does the selection is important. There is no sense in this study that a user who chooses something is fundamentally different from the algorithm hiding something from them. While in fact the the filtering algorithm is driven by user choices (among other things), users don’t understand the relationship that their choices have to the outcome.

not sure if i hate facebook or everyone i know
In other words, the article’s strange comparison between “individual’s choices” and “the algorithm,” should be read as “things I choose to do” vs. the effect of “a process Facebook has designed without my knowledge or understanding.” Again, they can’t be compared in the way the article proposes because they aren’t equivalent.

I struggled with the framing of the article because the research talks about “the algorithm” as though it were an element of nature, or a naturally occurring process like convection or mitosis. There is also no sense that it changes over time or that it could be changed intentionally to support a different scenario.*****

Facebook is a private corporation with a terrible public relations problem. It is periodically rated one of the least popular companies in existence. It is currently facing serious government investigations into illegal practices in many countries, some of which stem from the manipulation of its news feed algorithm. In this context, I have to say that it doesn’t seem wise for these Facebook researchers to have spun these data so hard in this direction, which I would summarize as: the algorithm is less selective and less polarizing. Particularly when the research finding in their own study is actually that the Facebook algorithm is modestly more selective and more polarizing than living your life without it.

Update: (6pm Eastern)

Wow, if you think I was critical have a look at these. It turns out I am the moderate one.

Eszter Hargittai from Northwestern posted on Crooked Timber that we should “stop being mesmerized by large numbers and go back to taking the fundamentals of social science seriously.” And (my favorite): “I thought Science was a serious peer-reviewed publication.”

Nathan Jurgenson from Maryland and Snapchat wrote on Cyborgology (“in a fury“) that Facebook is intentionally “evading” its own role in the production of the news feed. “Facebook cannot take its own role in news seriously.” He accuses the authors of using the “Big-N trick” to intentionally distract from methodological shortcomings. He tweeted that “we need to discuss how very poor corporate big data research gets fast tracked into being published.”

Zeynep Tufekci from UNC wrote on Medium that “I cannot remember a worse apples to oranges comparison” and that the key take-away from the study is actually the ordering effects of the algorithm (which I did not address in this post). “Newsfeed placement is a profoundly powerful gatekeeper for click-through rates.”

Update: (5/10)

A comment helpfully pointed out that I used the wrong percentages in my fourth point when summarizing the piece. Fixed it, with changes marked.

Update: (5/15)

It’s now one week since the Science study. This post has now been cited/linked in The New York Times, Fortune, Time, Wired, Ars Technica, Fast Company, Engaget, and maybe even a few more. I am still getting emails. The conversation has fixated on the <4% sample, often saying something like: "So, Facebook said this was a study about cars, but it was actually only about blue cars.” That’s fine, but the other point in my post is about what is being claimed at all, no matter the sample.

I thought my “coal mine” metaphor about the algorithm would work but it has not always worked. So I’ve clamped my Webcam to my desk lamp and recorded a four-minute video to explain it again, this time with a drawing.******

If the coal mine metaphor failed me, what would be a better metaphor? I’m not sure. Suggestions?

 

 

Notes:

* Diversity in hard news, in their study, would be a self-identified liberal who receives a story from FoxNews.com, or a self-identified conservative who receives one from the HuffingtonPost.com, where the stories are about “national news, politics, [or] world affairs.” In more precise terms, for each user “cross-cutting content” was defined as stories that are more likely to be shared by partisans who do not have the same self-identified ideological affiliation that you do.

** I don’t want to make this even more nitpicky, so I’ll put this in a footnote. The paper’s citations to Mutz and Huckfeldt et al. to mean that “exposure to cross-cutting viewpoints is associated with lower levels of political participation” is just bizarre. I hope it is a typo. These authors don’t advocate against exposure to cross-cutting viewpoints.

*** Perhaps this could be a new Facebook motto used in advertising: “Facebook: Better than one speculative dystopian future!”

**** In fact, algorithm and user form a coupled system of at least two feedback loops. But that’s not helpful to measure “amount” in the way the study wants to, so I’ll just tuck it away down here.

***** Facebook is behind the algorithm but they are trying to peer-review research about it without disclosing how it works — which is a key part of the study. There is also no way to reproduce the research (or do a second study on a primary phenomenon under study, the algorithm) without access to the Facebook platform.

****** In this video, I intentionally conflate (1) the number of posts filtered and (2) the magnitude of the bias of the filtering. I did so because the difficulty with the comparison works the same way for both, and I was trying to make the example simpler. Thanks to Cedric Langbort for pointing out that “baseline error” is the clearest way of explaining this.

(This was cross-posted to multicast and Wired.)

Why LGBT Communities and Our Allies Should Care about Net Neutrality

topic_net-neutrality

It’s easy to forget the larger, community benefits of an Open Internet that doesn’t discriminate based on the content flowing through the fiber (or however it gets to you). But let’s get specific. How does this open network nurture and support underserved and marginalized LGBT communities and why does something like Net Neutrality matter to our future?

Earlier this year, The LGBT Technology Partnership released research that I co-authored with media scholar and sociologist Jessie Daniels. In it, we lay out the reasons that LGBT-identifying individuals and our communities became early adopters of broadband technology and why the Internet continues to play such a pivotal part in our political and social lives. Maintaining Net Neutrality–keeping all information equally accessible on the Internet–is something that all LGBT-identifying people and our allies should care about and fight to maintain.

I have researched the Internet’s role in LGBT life for more than a decade. I study how and why LGBT-identifying young people and youth questioning their identities use the Internet and other media. There are 2 main reasons that marginalized communities, including LGBT people, use the Internet more than the typical U.S. citizen: 1) we are able to go online and connect to people we identify with, without having to battle the stigma and potential physical threat that comes with accessing LGBT-supportive physical spaces and 2) we are able to access services and information specifically for us–from dating sites to health information–tailored to our needs…not just a clumsy version of what’s made available to our heterosexual peers.

Let me give 2 concrete examples from my fieldwork among LGBT youth in rural towns throughout Southeast Appalachia. When Brandon, a young person living in Eastern Kentucky, wanted to find other young African-American, bi-identifying people to talk with about the pros and cons of coming out before turning 18, he literally knew no one and found no organizations in his town of 5,000 where he could meet other out, bi-identifying youth. He went online and found chat rooms for his region. All of them were dominated by adults. He had to spend a significant amount of time, searching through various websites and YouTube videos to access other kids his age to talk with. In a perfect world, he wouldn’t need to work so hard to find someone just like himself online and he’d have neighbors and friends in his high school to turn to for support. But there’s no critical mass of LGBT-identifying people in his home town (yet! We can hope that changes for him). That makes the Internet an important communication channel connecting him to a broader community of LGBT-identifying folks. But the Internet is not just for accessing other LGBT-identifying people online.

As I said, the Internet has become a vital resource for accessing information specifically tailored to us. So, for example, many of the towns I worked in had no LGBT-specific public health services or HIV prevention information available for LGBT-identifying youth. That meant braving the school nurse or walking into a local health clinic and talking with someone who they could not assume to be an advocate for LGBT rights. Adults in big cities like DC might struggle with doing that. Imagine being a 14 year old in a very small town doing that. Youth I work with depend on web-based resources, like Trevor Project, Advocates for Youth, YouTube, and other non-profits that list resources for LGBT-specific health information. The Internet is a vital communication and information channel. The presumption that heterosexuality is the default setting makes the Internet a precious resource for LGBT-identifying people. LGBT and questioning youth in particular need places for them and information written for them readily available. It’s not a perk. The Internet has become a basic need and a public good.

From my perspective, the Net Neutrality debate is important to LGBT communities because, simply put, LGBT-identifying people will be collateral damage if Internet Service Providers (ISPs) are allowed to discriminate among content, apps, or services. without Net Neutrality protections, content providers generating critical information would likely have to pay more to get their content into (and from!) the hands of LGBT people. That means ISPs become the defacto gatekeepers controlling what content survives and what content falls by the wayside in the wake of a market-driven content tsunami. This, in turn, will raise the cost of providing LGBT content, reducing the overall amount of LGBT content available. This will be a significant barrier to the non-profit sources of content that have proven critical to LGBT communities, including information provided by the U.S. Government.

Net Neutrality is a simple principle: don’t make it harder to access or download something on the Internet based on the content of that information or service. Individuals, not our Internet Service Providers, should determine the information that they can access online. ISPs should not be legally allowed to block content or limit a private citizen’s opportunity to see what information is available online for them to purchase or made available to them for free.

Like broadcast TV, phones, and libraries, the Internet plays a special and critical role in connecting and educating citizens. I wish that every public school, community center, and local radio and public access TV station offered a wealth of LGBT-specific resources. They do not. The Internet, currently, picks up this important duty for the public.

Right now, like all citizens, LGBT people and our allies have the basic right to access any information available on the Internet. LGBT-specific information on the Internet–from other young people’s websites to the It Gets Better campaign on YouTube–can be vital to LGBT lives, particularly young people looking for affirmation and reflections of themselves. LGBT-specific information is typically hosted or created by non-profits and private individuals who care about LGBT people’s needs. In the same way that it should not be harder at the public library to see the stack of books most relevant to LGBT communities, it shouldn’t be harder or cost more to access information specific to LGBT communities.

The providers of Internet access are not just delivering binge TV through Netflix. They are serving up those webpages that LGBT-identifying and questioning young people rely on to survive and thrive. As much as I love the entire catalogue of Queer as Folk, it is not the same content–and cannot do the same vital community-building work–as coming out videos accessible on YouTube or HIV prevention information, local resource lists, and opportunities to access other LGBT-identifying people available through non-profit websites. If ISPs are allowed to sort content differently, those random, youth-created and driven websites that offer crucial, eclectic information to small, niche audiences, are, potentially, at risk of being lost to us. I don’t think we, as LGBT people and allies, can afford that loss.

On Monday November 10, 2014, President Obama made a statement outlining four “bright-line rules” for maintaining Net Neutrality, including no blocking, no throttling, increased transparency and no paid prioritization. I wish that we could achieve keeping content equally accessible without regulation. I sincerely do. But, right now, all we have are promises from the Internet service provider’s major companies that they will not block content, throttle download/upload rates, decrease transparency behind their billing or let content owners pay ISPs to “cut to the front of the line” of the information buffet that is the Internet.

There are several cases, dating back to the beginning of the content-rich web of the mid-2000s, that suggest Internet service providers will block or slow down content delivery and price some content differently to keep competition at bay. There are 3 options: 1) make it illegal for Internet service providers to discriminate among content, apps, or services online or 2) fund municipal broadband for every community in the United States so that all citizens have access to the Internet’s content or 3) do both 1 and 2 and let the market and innovations, like playing with unlicensed spectrum, handle the rest. The Internet operates as a public good. We need it to register for many government services at this point. We can’t go back and say, “Internet content and services are just extras that society can do without.” We’ve got to have clear guidance and enforceable rules to maintain the deep investments we’ve already made in making the Internet one of the world’s greatest information repositories and sites for community connection, particularly among communities, like those of LGBT folks, with limited resources and social opposition offline.

Having worked in the rural U.S. for some time, my sense is that the best solution for ensuring an open Internet is by recognizing what ISPs have become: stewards of a critical public resource. We use our Internet connections to talk to people, pay our parking tickets, and make appointments to get our drivers licenses. LGBT communities use Internet connections to reach people like them and share strategies on how to move through a world that still can’t decide if we have the right to marry the people we love. Those are services and information resources necessary for a robust and healthy civic and civil society. It’s too late to treat the Internet like an expendable, frivolity. LGBT communities are particularly dependent on the Internet to find and connect with the people and information that we need to live healthy and productive lives. What can you do about all of this? Get the facts, advocate for a free and open Internet to your local representatives, and support your local LGBT activists creating content that reflects the richness and diversity of our lives and communities.

Cross-posted to http://marylgray.org | Image Source

Why We Like Pinterest for Fieldwork

(written up with Nikki Usher, GWU)

Anyone tackling fieldwork these days can chose from a wide selection of digital tools to put in their methodological toolkit.  Among the best of these tools are platforms that let you archive, analyze, and disseminate at the same time.  It used to be that these were fairly distinct stages of research, especially for the most positivist among us.  You came up with research questions, chose a field site, entered the field site, left the field site, analyzed your findings, got them published, and shared your research output with friends and colleagues.

But the post-positivist approach that many of us like involves adapting your research questions—reflexively and responsively—while doing fieldwork.  Entering and leaving your field site is not a cool, clean and complete process.  We analyze findings as we go, and involve our research subjects in the analysis.  We publish, but often in journals or books that can’t reproduce the myriad digital artifacts that are meaningful in network ethnography.  Actor network theory, activity theory, science and technology studies and several other modes of social and humanistic inquiry approach research as something that involves both people and devices. (Yes yes we know but these wikipedia entries aren’t bad.) Moreover, the dissemination of work doesn’t have to be something that happens after publication or even at the end of a research plan.

Nikki’s work involves qualitative ethnographic work at field sites where research can last from five months to a brief week visit to a quick drop in day. She learned the hard way from her research for Making News at The New York Times that failing to find a good way to organize and capture images was a missed opportunity post-data collection. Since then, Nikki’s been using Pinterest for fieldwork image gathering quite a bit.  Phil’s work on The Managed Citizen was set back when he lost two weeks of field notes on the chaotic floor of the Republican National Convention in 2000 (security incinerates all the detritus left by convention goers).  He’s been digitizing field observations ever since.

Some people put together personal websites about their research journey.  Some share over Twitter.  And there are plenty of beta tools, open source or otherwise, that people play with.  We’ve both enjoyed using Pinterest for our research projects.  Here are some points on how we use it and why we like it.

How To Use It

  1. When you start, think of this as your research tool and your resource.   If you dedicate yourself to this as your primary archiving system for digital artifacts you are more likely to build it up over time.  If you think of this as a social media publicity gimmick for your research, you’ll eventually lose interest and it is less likely to be useful for anyone else.
  2. Integrate it with your mobile phone because this amps up your capacity for portable, taggable, image data collection.
  3. Link the board posts to Twitter or your other social media feeds.  Pinterest itself isn’t that lively a place for researchers yet.  The people who want to visit your Pinterest page are probably actively following your activities on other platforms so be sure to let content flow across platforms.
  4. Pin lots of things, and lots of different kinds of things.  Include decent captions though be aware that if you are feeding Twitter you need to fit character limits.
  5. Use it to collect images you have found online, images you’ve taken yourself during your fieldwork, and invite the communities you are working with to contribute.
  6. Backup and export things once in a while for safe keeping.  There is no built-in export function, but there are a wide variety of hacks and workarounds for transporting your archive.

What You Get

  1. Pinterest makes it easy to track the progress of the image data you gather.  You may find yourself taking more photos in the field because they can be easily arranged, saved and categorized.
  2. Using it regularly adds another level of data as photos and documents captured on phone and then added on Pinterest can be quickly field captioned and then re-catalogued, giving you a chance to review the visual and built environment of your field site and interrogate your observations afresh.
  3. Visually-enhanced constant comparative methods: post-data collection, you can go beyond notes to images and captions that are easily scanned for patterns and points of divergence. This may be  going far beyond what Glaser and Strauss had imagined, of course.
  4. Perhaps most important, when you forget what something looks like when you’re writing up your results, you’ve got an instant, easily searchable database of images and clues to refresh your memory.

Why We Like It

  1. It’s great for spontaneous presentations.  Images are such an important part of presenting any research.  Having a quick publically accessible archive of content allows you to speak, on the fly, about what you are up to.  You can’t give a tour of your Pinterest page for a job talk.  But having the resource there means you can call on images quickly during a Q&A period, or quickly load something relevant on a phone or browser during a casual conversation about your work.
  2. It gives you a way to interact with subjects.  Having the Pinterest link allows you to show a potential research subject what you are up to and what you are interested in.  During interviews it allows you to engage people on their interpretation of things.  Having visual prompts handy can enrich and enliven any focus group or single subject interview.  These don’t only prompt further conversation, they can prompt subjects to give you even more links, images, videos and other digital artifacts.
  3. It makes your research interests transparent. Having the images, videos and artifacts for anyone to see is a way for us to show what we are doing.  Anyone with interest in the project and the board link is privy to our research goals. Our Pinterest page may be far less complicated than many of our other efforts to explain our work to a general audience.
  4. You can disseminate as you go.  If you get the content flow right, you can tell people about your research as you are doing it.  Letting people know about what you are working on is always a good career strategy.  Giving people images rather than article abstracts and draft chapters gives them something to visualize and improves the ambient contact with your research community
  5. It makes digital artifacts more permanent. As long as you keep your Pinterest, what you have gathered can become a stable resource for anyone interested in your subjects. As sites and material artifacts change, what you have gathered offers a permanent and easily accessible snapshot of a particular moment of inquiry for posterity.

Pinterest Wish-list

One of us is a Windows Phone user (yes really) and it would be great if there was a real Pinterest app for the Windows Phone. One touch integration from the iPhone, much like Twitter, Facebook, and Flicker from the camera roll would be great (though there is an easy hack).

We wish it would be easier to have open, collaborative boards. Right now, the only person who can add to a board is you, at least at first.  You can invite other people to join a “group board” via email, but Pinterest does not have open boards that allow anyone with a board link to add content.

Here’s a look at our Pinboards: Phil Howard’s Tech + Politics board, and Nikki Usher’s boards on U.S. Newspapers.  We welcome your thoughts…and send us images!

 

What does the Facebook experiment teach us?

I’m intrigued by the reaction that has unfolded around the Facebook “emotion contagion” study. (If you aren’t familiar with this, read this primer.) As others have pointed out, the practice of A/B testing content is quite common. And Facebook has a long history of experimenting on how it can influence people’s attitudes and practices, even in the realm of research. An earlier study showed that Facebook decisions could shape voters’ practices. But why is it that *this* study has sparked a firestorm?

In asking people about this, I’ve been given two dominant reasons:

  1. People’s emotional well-being is sacred.
  2. Research is different than marketing practices.

I don’t find either of these responses satisfying.

The Consequences of Facebook’s Experiment

Facebook’s research team is not truly independent of product. They have a license to do research and publish it, provided that it contributes to the positive development of the company. If Facebook knew that this research would spark the negative PR backlash, they never would’ve allowed it to go forward or be published. I can only imagine the ugliness of the fight inside the company now, but I’m confident that PR is demanding silence from researchers.

I do believe that the research was intended to be helpful to Facebook. So what was the intended positive contribution of this study? I get the sense from Adam Kramer’s comments that the goal was to determine if content sentiment could affect people’s emotional response after being on Facebook. In other words, given that Facebook wants to keep people on Facebook, if people came away from Facebook feeling sadder, presumably they’d not want to come back to Facebook again. Thus, it’s in Facebook’s better interest to leave people feeling happier. And this study suggests that the sentiment of the content influences this. This suggests that one applied take-away for product is to downplay negative content. Presumably this is better for users and better for Facebook.

We can debate all day long as to whether or not this is what that study actually shows, but let’s work with this for a second. Let’s say that pre-study Facebook showed 1 negative post for every 3 positive and now, because of this study, Facebook shows 1 negative post for every 10 positive ones. If that’s the case, was the one week treatment worth the outcome for longer term content exposure? Who gets to make that decision?

Folks keep talking about all of the potential harm that could’ve happened by the study – the possibility of suicides, the mental health consequences. But what about the potential harm of negative content on Facebook more generally? Even if we believe that there were subtle negative costs to those who received the treatment, the ongoing costs of negative content on Facebook every week other than that 1 week experiment must be more costly. How then do we account for positive benefits to users if Facebook increased positive treatments en masse as a result of this study? Of course, the problem is that Facebook is a black box. We don’t know what they did with this study. The only thing we know is what is published in PNAS and that ain’t much.

Of course, if Facebook did make the content that users see more positive, should we simply be happy? What would it mean that you’re more likely to see announcements from your friends when they are celebrating a new child or a fun night on the town, but less likely to see their posts when they’re offering depressive missives or angsting over a relationship in shambles? If Alice is happier when she is oblivious to Bob’s pain because Facebook chooses to keep that from her, are we willing to sacrifice Bob’s need for support and validation? This is a hard ethical choice at the crux of any decision of what content to show when you’re making choices. And the reality is that Facebook is making these choices every day without oversight, transparency, or informed consent.

Algorithmic Manipulation of Attention and Emotions

Facebook actively alters the content you see. Most people focus on the practice of marketing, but most of what Facebook’s algorithms do involve curating content to provide you with what they think you want to see. Facebook algorithmically determines which of your friends’ posts you see. They don’t do this for marketing reasons. They do this because they want you to want to come back to the site day after day. They want you to be happy. They don’t want you to be overwhelmed. Their everyday algorithms are meant to manipulate your emotions. What factors go into this? We don’t know.

Facebook is not alone in algorithmically predicting what content you wish to see. Any recommendation system or curatorial system is prioritizing some content over others. But let’s compare what we glean from this study with standard practice. Most sites, from major news media to social media, have some algorithm that shows you the content that people click on the most. This is what drives media entities to produce listicals, flashy headlines, and car crash news stories. What do you think garners more traffic – a detailed analysis of what’s happening in Syria or 29 pictures of the cutest members of the animal kingdom? Part of what media learned long ago is that fear and salacious gossip sell papers. 4chan taught us that grotesque imagery and cute kittens work too. What this means online is that stories about child abductions, dangerous islands filled with snakes, and celebrity sex tape scandals are often the most clicked on, retweeted, favorited, etc. So an entire industry has emerged to produce crappy click bait content under the banner of “news.”

Guess what? When people are surrounded by fear-mongering news media, they get anxious. They fear the wrong things. Moral panics emerge. And yet, we as a society believe that it’s totally acceptable for news media – and its click bait brethren – to manipulate people’s emotions through the headlines they produce and the content they cover. And we generally accept that algorithmic curators are perfectly well within their right to prioritize that heavily clicked content over others, regardless of the psychological toll on individuals or the society. What makes their practice different? (Other than the fact that the media wouldn’t hold itself accountable for its own manipulative practices…)

Somehow, shrugging our shoulders and saying that we promoted content because it was popular is acceptable because those actors don’t voice that their intention is to manipulate your emotions so that you keep viewing their reporting and advertisements. And it’s also acceptable to manipulate people for advertising because that’s just business. But when researchers admit that they’re trying to learn if they can manipulate people’s emotions, they’re shunned. What this suggests is that the practice is acceptable, but admitting the intention and being transparent about the process is not.

But Research is Different!!

As this debate has unfolded, whenever people point out that these business practices are commonplace, folks respond by highlighting that research or science is different. What unfolds is a high-browed notion about the purity of research and its exclusive claims on ethical standards.

Do I think that we need to have a serious conversation about informed consent? Absolutely. Do I think that we need to have a serious conversation about the ethical decisions companies make with user data? Absolutely. But I do not believe that this conversation should ever apply just to that which is categorized under “research.” Nor do I believe that academe is necessarily providing a golden standard.

Academe has many problems that need to be accounted for. Researchers are incentivized to figure out how to get through IRBs rather than to think critically and collectively about the ethics of their research protocols. IRBs are incentivized to protect the university rather than truly work out an ethical framework for these issues. Journals relish corporate datasets even when replicability is impossible. And for that matter, even in a post-paper era, journals have ridiculous word count limits that demotivate researchers from spelling out all of the gory details of their methods. But there are also broader structural issues. Academe is so stupidly competitive and peer review is so much of a game that researchers have little incentive to share their studies-in-progress with their peers for true feedback and critique. And the status games of academe reward those who get access to private coffers of data while prompting those who don’t to chastise those who do. And there’s generally no incentive for corporates to play nice with researchers unless it helps their prestige, hiring opportunities, or product.

IRBs are an abysmal mechanism for actually accounting for ethics in research. By and large, they’re structured to make certain that the university will not be liable. Ethics aren’t a checklist. Nor are they a universal. Navigating ethics involves a process of working through the benefits and costs of a research act and making a conscientious decision about how to move forward. Reasonable people differ on what they think is ethical. And disciplines have different standards for how to navigate ethics. But we’ve trained an entire generation of scholars that ethics equals “that which gets past the IRB” which is a travesty. We need researchers to systematically think about how their practices alter the world in ways that benefit and harm people. We need ethics to not just be tacked on, but to be an integral part of how *everyone* thinks about what they study, build, and do.

There’s a lot of research that has serious consequences on the people who are part of the study. I think about the work that some of my colleagues do with child victims of sexual abuse. Getting children to talk about these awful experiences can be quite psychologically tolling. Yet, better understanding what they experienced has huge benefits for society. So we make our trade-offs and we do research that can have consequences. But what warms my heart is how my colleagues work hard to help those children by providing counseling immediately following the interview (and, in some cases, follow-up counseling). They think long and hard about each question they ask, and how they go about asking it. And yet most IRBs wouldn’t let them do this work because no university wants to touch anything that involves kids and sexual abuse. Doing research involves trade-offs and finding an ethical path forward requires effort and risk.

It’s far too easy to say “informed consent” and then not take responsibility for the costs of the research process, just as it’s far too easy to point to an IRB as proof of ethical thought. For any study that involves manipulation – common in economics, psychology, and other social science disciplines – people are only so informed about what they’re getting themselves into. You may think that you know what you’re consenting to, but do you? And then there are studies like discrimination audit studies in which we purposefully don’t inform people that they’re part of a study. So what are the right trade-offs? When is it OK to eschew consent altogether? What does it mean to truly be informed? When it being informed not enough? These aren’t easy questions and there aren’t easy answers.

I’m not necessarily saying that Facebook made the right trade-offs with this study, but I think that the scholarly reaction of research is only acceptable with IRB plus informed consent is disingenuous. Of course, a huge part of what’s at stake has to do with the fact that what counts as a contract legally is not the same as consent. Most people haven’t consented to all of Facebook’s terms of service. They’ve agreed to a contract because they feel as though they have no other choice. And this really upsets people.

A Different Theory

The more I read people’s reactions to this study, the more that I’ve started to think that the outrage has nothing to do with the study at all. There is a growing amount of negative sentiment towards Facebook and other companies that collect and use data about people. In short, there’s anger at the practice of big data. This paper provided ammunition for people’s anger because it’s so hard to talk about harm in the abstract.

For better or worse, people imagine that Facebook is offered by a benevolent dictator, that the site is there to enable people to better connect with others. In some senses, this is true. But Facebook is also a company. And a public company for that matter. It has to find ways to become more profitable with each passing quarter. This means that it designs its algorithms not just to market to you directly but to convince you to keep coming back over and over again. People have an abstract notion of how that operates, but they don’t really know, or even want to know. They just want the hot dog to taste good. Whether it’s couched as research or operations, people don’t want to think that they’re being manipulated. So when they find out what soylent green is made of, they’re outraged. This study isn’t really what’s at stake. What’s at stake is the underlying dynamic of how Facebook runs its business, operates its system, and makes decisions that have nothing to do with how its users want Facebook to operate. It’s not about research. It’s a question of power.

I get the anger. I personally loathe Facebook and I have for a long time, even as I appreciate and study its importance in people’s lives. But on a personal level, I hate the fact that Facebook thinks it’s better than me at deciding which of my friends’ posts I should see. I hate that I have no meaningful mechanism of control on the site. And I am painfully aware of how my sporadic use of the site has confused their algorithms so much that what I see in my newsfeed is complete garbage. And I resent the fact that because I barely use the site, the only way that I could actually get a message out to friends is to pay to have it posted. My minimal use has made me an algorithmic pariah and if I weren’t technologically savvy enough to know better, I would feel as though I’ve been shunned by my friends rather than simply deemed unworthy by an algorithm. I also refuse to play the game to make myself look good before the altar of the algorithm. And every time I’m forced to deal with Facebook, I can’t help but resent its manipulations.

There’s also a lot that I dislike about the company and its practices. At the same time, I’m glad that they’ve started working with researchers and started publishing their findings. I think that we need more transparency in the algorithmic work done by these kinds of systems and their willingness to publish has been one of the few ways that we’ve gleaned insight into what’s going on. Of course, I also suspect that the angry reaction from this study will prompt them to clamp down on allowing researchers to be remotely public. My gut says that they will naively respond to this situation as though the practice of research is what makes them vulnerable rather than their practices as a company as a whole. Beyond what this means for researchers, I’m concerned about what increased silence will mean for a public who has no clue of what’s being done with their data, who will think that no new report of terrible misdeeds means that Facebook has stopped manipulating data.

Information companies aren’t the same as pharmaceuticals. They don’t need to do clinical trials before they put a product on the market. They can psychologically manipulate their users all they want without being remotely public about exactly what they’re doing. And as the public, we can only guess what the black box is doing.

There’s a lot that needs reformed here. We need to figure out how to have a meaningful conversation about corporate ethics, regardless of whether it’s couched as research or not. But it’s not so simple as saying that a lack of a corporate IRB or a lack of a golden standard “informed consent” means that a practice is unethical. Almost all manipulations that take place by these companies occur without either one of these. And they go unchecked because they aren’t published or public.

Ethical oversight isn’t easy and I don’t have a quick and dirty solution to how it should be implemented. But I do have a few ideas. For starters, I’d like to see any company that manipulates user data create an ethics board. Not an IRB that approves research studies, but an ethics board that has visibility into all proprietary algorithms that could affect users. For public companies, this could be done through the ethics committee of the Board of Directors. But rather than simply consisting of board members, I think that it should consist of scholars and users. I also think that there needs to be a mechanism for whistleblowing regarding ethics from within companies because I’ve found that many employees of companies like Facebook are quite concerned by certain algorithmic decisions, but feel as though there’s no path to responsibly report concerns without going fully public. This wouldn’t solve all of the problems, nor am I convinced that most companies would do so voluntarily, but it is certainly something to consider. More than anything, I want to see users have the ability to meaningfully influence what’s being done with their data and I’d love to see a way for their voices to be represented in these processes.

I’m glad that this study has prompted an intense debate among scholars and the public, but I fear that it’s turned into a simplistic attack on Facebook over this particular study rather than a nuanced debate over how we create meaningful ethical oversight in research and practice. The lines between research and practice are always blurred and information companies like Facebook make this increasingly salient. No one benefits by drawing lines in the sand. We need to address the problem more holistically. And, in the meantime, we need to hold companies accountable for how they manipulate people across the board, regardless of whether or not it’s couched as research. If we focus too much on this study, we’ll lose track of the broader issues at stake.

Corrupt Personalization

(“And also Bud Light.”)

In my last two posts I’ve been writing about my attempt to convince a group of sophomores with no background in my field that there has been a shift to the algorithmic allocation of attention — and that this is important. In this post I’ll respond to a student question. My favorite: “Sandvig says that algorithms are dangerous, but what are the the most serious repercussions that he envisions?” What is the coming social media apocalypse we should be worried about?

google flames

This is an important question because people who study this stuff are NOT as interested in this student question as they should be. Frankly, we are specialists who study media and computers and things — therefore we care about how algorithms allocate attention among cultural products almost for its own sake. Because this is the central thing that we study, we don’t spend a lot of time justifying it.

And our field’s most common response to the query “what are the dangers?” often lacks the required sense of danger. The most frequent response is: “extensive personalization is bad for democracy.” (a.k.a. Pariser’s “filter bubble,” Sunstein’s “egocentric” Internet, and so on). This framing lacks a certain house-on-fire urgency, doesn’t it?

(sarcastic tone:) “Oh, no! I’m getting to watch, hear, and read exactly what I want. Help me! Somebody do something!”

Sometimes (as Hindman points out) the contention is the opposite, that Internet-based concentration is bad for democracy.  But remember that I’m not speaking to political science majors here. The average person may not be as moved by an abstract, long-term peril to democracy as the average political science professor. As David Weinberger once said after I warned about the increasing reliance on recommendation algorithms, “So what?” Personalization sounds like a good thing.

As a side note, the second most frequent response I see is that algorithms are now everywhere. And they work differently than what came before. This also lacks a required sense of danger! Yes, they’re everywhere, but if they are a good thing

So I really like this question “what are the the most serious repercussions?” because I think there are some elements of the shift to attention-sorting algorithms that are genuinely “dangerous.” I can think of at least two, probably more, and they don’t get enough attention. In the rest of this post I’ll spell out the first one which I’ll call “corrupt personalization.”

Here we go.

Common-sense reasoning about algorithms and culture tells us that the purveyors of personalized content have the same interests we do. That is, if Netflix started recommending only movies we hate or Google started returning only useless search results we would stop using them. However: Common sense is wrong in this case. Our interests are often not the same as the providers of these selection algorithms.  As in my last post, let’s work through a few concrete examples to make the case.

In this post I’ll use Facebook examples, but the general problem of corrupt personalization is present on all of our media platforms in wide use that employ the algorithmic selection of content.

(1) Facebook “Like” Recycling

Screen Shot 2012-12-10 at 12.44.34 PM

(Image from ReadWriteWeb.)

On Facebook, in addition to advertisements along the side of the interface, perhaps you’ve noticed “featured,” “sponsored,” or “suggested” stories that appear inside your news feed, intermingled with status updates from your friends. It could be argued that this is not in your interest as a user (did you ever say, “gee, I’d like ads to look just like messages from my friends”?), but I have bigger fish to fry.

Many ads on Facebook resemble status updates in that there can be messages endorsing the ads with “likes.” For instance, here is an older screenshot from ReadWriteWeb:

pages you may like on facebook

Another example: a “suggested” post was mixed into my news feed just this morning recommending World Cup coverage on Facebook itself. It’s a Facebook ad for Facebook, in other words.  It had this intriguing addendum:

CENSORED likes facebook

So, wait… I have hundreds of friends and eleven of them “like” Facebook?  Did they go to http://www.facebook.com and click on a button like this:

Facebook like button magnified

But facebook.com doesn’t even have a “Like” button!  Did they go to Facebook’s own Facebook page (yes, there is one) and click “Like”? I know these people and that seems unlikely. And does Nicolala really like Walmart? Hmmm…

What does this “like” statement mean? Welcome to the strange world of “like” recycling. Facebook has defined “like” in ways that depart from English usage.  For instance, in the past Facebook has determined that:

  1. Anyone who clicks on a “like” button is considered to have “liked” all future content from that source. So if you clicked a “like” button because someone shared a “Fashion Don’t” from Vice magazine, you may be surprised when your dad logs into Facebook three years later and is shown a current sponsored story from Vice.com like “Happy Masturbation Month!” or “How to Make it in Porn” with the endorsement that you like it. (Vice.com example is from Craig Condon [NSFW].)
  2. Anyone who “likes” a comment on a shared link is considered to “like” wherever that link points to.  a.k.a. “‘liking a share.” So if you see a (real) FB status update from a (real) friend and it says: “Yuck! The McLobster is a disgusting product idea!” and your (real) friend include a (real) link like this one — that means if you clicked “like” your friends may see McDonald’s ads in the future that include the phrase “(Your Name) likes McDonalds.” (This example is from ReadWriteWeb.)

fauxLike_mcdonalds

This has led to some interesting results, like dead people “liking” current news stories on Facebook.

There is already controversy about advertiser “like” inflation, “like” spam, and fake “likes,” — and these things may be a problem too, but that’s not what we are talking about here.  In the examples above the system is working as Facebook designed it to. A further caveat: note that the definition of “like” in Facebook’s software changes periodically and when they are sued. Facebook now has an opt-out setting for the above two “features.”

But these incendiary examples are exceptional fiascoes — on the whole the system probably works well. You likely didn’t know that your “like” clicks are merrily producing ads on your friends pages and in your name because you cannot see them.  These “stories” do not appear on your news feed and cannot be individually deleted.

Unlike the examples from my last post you can’t quickly reproduce these results with certainty on your own account. Still, if you want to try, make a new Facebook account under a fake name (warning! dangerous!) and friend your real account. Then use the new account to watch your status updates.

Why would Facebook do this? Obviously it is a controversial practice that is not going to be popular with users. Yet Facebook’s business model is to produce attention for advertisers, not to help you — silly rabbit. So they must have felt that using your reputation to produce more ad traffic from your friends was worth the risk of irritating you. Or perhaps they thought that the practice could be successfully hidden from users — that strategy has mostly worked!

In sum this is a personalization scheme that does not serve your goals, it serves Facebook’s goals at your expense.

(2) “Organic” Content

This second group of examples concerns content that we consider to be “not advertising,” a.k.a. “organic” content. Funnily enough, algorithmic culture has produced this new use of the word “organic” — but has also made the boundary between “advertising” and “not advertising” very blurry.

funny-organic-food-ad

 

The general problem is that there are many ways in which algorithms act as mixing valves between things that can be easily valued with money (like ads) and things that can’t. And this kind of mixing is a normative problem (what should we do) and not a technical problem (how do we do it).

For instance, for years Facebook has encouraged nonprofits, community-based organizations, student clubs, other groups, and really anyone to host content on facebook.com.  If an organization creates a Facebook page for itself, the managers can update the page as though it were a profile.

Most page managers expect that people who “like” that page get to see the updates… which was true until January of this year. At that time Facebook modified its algorithm so that text updates from organizations were not widely shared. This is interesting for our purposes because Facebook clearly states that it wants page operators to run Facebook ad campaigns, and not to count on getting traffic from “organic” status updates, as it will no longer distribute as many of them.

This change likely has a very differential effect on, say, Nike‘s Facebook page, a small local business‘s Facebook page, Greenpeace International‘s Facebook page, and a small local church congregation‘s Facebook page. If you start a Facebook page for a school club, you might be surprised that you are spending your labor writing status updates that are never shown to anyone. Maybe you should buy an ad. Here’s an analytic for a page I manage:

this week page likes facebook

 

The impact isn’t just about size — at some level businesses might expect to have to insert themselves into conversations via persuasive advertising that they pay for, but it is not as clear that people expect Facebook to work this way for their local church or other domains of their lives. It’s as if on Facebook, people were using the yellow pages but they thought they were using the white pages.  And also there are no white pages.

(Oh, wait. No one knows what yellow pages and white pages are anymore. Scratch that reference, then.)

No need to stop here, in the future perhaps Facebook can monetize my family relationships. It could suggest that if I really want anyone to know about the birth of my child, or I really want my “insightful” status updates to reach anyone, I should turn to Facebook advertising.

Let me also emphasize that this mixing problem extends to the content of our personal social media conversations as well. A few months back, I posted a Facebook status update that I thought was humorous. I shared a link highlighting the hilarious product reviews for the Bic “Cristal For Her” ballpoint pen on Amazon. It’s a pen designed just for women.

bic crystal for her

The funny thing is that I happened to look at a friend of mine’s Facebook feed over their shoulder, and my status update didn’t go away. It remained, pegged at the top of my friend’s news feed, for as long as 14 days in one instance. What great exposure for my humor, right? But it did seem a little odd… I queried my other friends on Facebook and some confirmed that the post was also pegged at the top of their news feed.

I was unknowingly participating in another Facebook program that converts organic status updates into ads. It does this by changing their order in the news feed and adding the text “Sponsored” in light gray, which is very hard to see. Otherwise at least some updates are not changed. I suspect Facebook’s algorithm thought I was advertising Amazon (since that’s where the link pointed), but I am not sure.

This is similar to Twitter’s “Promoted Tweets” but there is one big difference.  In the Facebook case the advertiser promotes content — my content — that they did not write. In effect Facebook is re-ordering your conversations with your friends and family on the basis of whether or not someone mentioned Coke, Levi’s, and Anheuser Busch (confirmed advertisers in the program).

Sounds like a great personal social media strategy there–if you really want people to know about your forthcoming wedding, maybe just drop a few names? Luckily the algorithms aren’t too clever about this yet so you can mix up the word order for humorous effect.

(Facebook status update:) “I am so delighted to be engaged to this wonderful woman that I am sitting here in my Michelob drinking a Docker’s Khaki Collection. And also Coke.”

Be sure to use links. I find the interesting thing about this mixing of the commercial and non-commercial to be that it sounds to my ears like some sort of corny, unrealistic science fiction scenario and yet with the current Facebook platform I believe the above example would work. We are living in the future.

So to recap, if Nike makes a Facebook page and posts status updates to it, that’s “organic” content because they did not pay Facebook to distribute it. Although any rational human being would see it as an ad. If my school group does the same thing, that’s also organic content, but they are encouraged to buy distribution — which would make it inorganic. If I post a status update or click “like” in reaction to something that happens in my life and that happens to involve a commercial product, my action starts out as organic, but then it becomes inorganic (paid for) because a company can buy my words and likes and show them to other people without telling me. Got it? This paragraph feels like we are rethinking CHEM 402.

The upshot is that control of the content selection algorithm is used by Facebook to get people to pay for things they wouldn’t expect to pay for, and to show people personalized things that they don’t think are paid for. But these things were in fact paid for.  In sum this is again a scheme that does not serve your goals, it serves Facebook’s goals at your expense.

The Danger: Corrupt Personalization

With these concrete examples behind us, I can now more clearly answer this student question. What are the most serious repercussions of the algorithmic allocation of attention?

I’ll call this first repercussion “corrupt personalization” after C. Edwin Baker. (Baker, a distinguished legal philosopher, coined the phrase “corrupt segmentation” in 1998 as an extension of the theories of philosopher Jürgen Habermas.)

Here’s how it works: You have legitimate interests that we’ll call “authentic.” These interests arise from your values, your community, your work, your family, how you spend your time, and so on. A good example might be that as a person who is enrolled in college you might identify with the category “student,” among your many other affiliations. As a student, you might be authentically interested in an upcoming tuition increase or, more broadly, about the contention that “there are powerful forces at work in our society that are actively hostile to the college ideal.”

However, you might also be authentically interested in the fact that your cousin is getting married. Or in pictures of kittens.

Grumpy-Cat-meme-610x405

Corrupt personalization is the process by which your attention is drawn to interests that are not your own. This is a little tricky because it is impossible to clearly define an “authentic” interest. However, let’s put that off for the moment.

In the prior examples we saw some (I hope) obvious places where my interests diverged from that of algorithmic social media systems. Highlights for me were:

  • When I express my opinion about something to my friends and family, I do not want that opinion re-sold without my knowledge or consent.
  • When I explicitly endorse something, I don’t want that endorsement applied to other things that I did not endorse.
  • If I want to read a list of personalized status updates about my friends and family, I do not want my friends and family sorted by how often they mention advertisers.
  • If a list of things is chosen for me, I want the results organized by some measure of goodness for me, not by how much money someone has paid.
  • I want paid content to be clearly identified.
  • I do not want my information technology to sort my life into commercial and non-commercial content and systematically de-emphasize the noncommercial things that I do, or turn these things toward commercial purposes.

More generally, I think the danger of corrupt personalization is manifest in three ways.

  1. Things that are not necessarily commercial become commercial because of the organization of the system. (Merton called this “pseudo-gemeinschaft,” Habermas called it “colonization of the lifeworld.”)
  2. Money is used as a proxy for “best” and it does not work. That is, those with the most money to spend can prevail over those with the most useful information. The creation of a salable audience takes priority over your authentic interests. (Smythe called this the “audience commodity,” it is Baker’s “market filter.”)
  3. Over time, if people are offered things that are not aligned with their interests often enough, they can be taught what to want. That is, they may come to wrongly believe that these are their authentic interests, and it may be difficult to see the world any other way. (Similar to Chomsky and Herman’s [not Lippman’s] arguments about “manufacturing consent.”)

There is nothing inherent in the technologies of algorithmic allocation that is doing this to us, instead the economic organization of the system is producing these pressures. In fact, we could design a system to support our authentic interests, but we would then need to fund it. (Thanks, late capitalism!)

To conclude, let’s get some historical perspective. What are the other options, anyway? If cultural selection is governed by computer algorithms now, you might answer, “who cares?” It’s always going to be governed somehow. If I said in a talk about “algorithmic culture” that I don’t like the Netflix recommender algorithm, what is supposed to replace it?

This all sounds pretty bad, so you might think I am asking for a return to “pre-algorithmic” culture: Let’s reanimate the corpse of Louis B. Mayer and he can decide what I watch. That doesn’t seem good either and I’m not recommending it. We’ve always had selection systems and we could even call some of the earlier ones “algorithms” if we want to.  However, we are constructing something new and largely unprecedented here and it isn’t ideal. It isn’t that I think algorithms are inherently dangerous, or bad — quite the contrary. To me this seems like a case of squandered potential.

With algorithmic culture, computers and algorithms are allowing a new level of real-time personalization and content selection on an individual basis that just wasn’t possible before. But rather than use these tools to serve our authentic interests, we have built a system that often serves a commercial interest that is often at odds with our interests — that’s corrupt personalization.

If I use the dominant forms of communication online today (Facebook, Google, Twitter, YouTube, etc.) I can expect content customized for others to use my name and my words without my consent, in ways I wouldn’t approve of. Content “personalized” for me includes material I don’t want, and obscures material that I do want. And it does so in a way that I may not be aware of.

This isn’t an abstract problem like a long-term threat to democracy, it’s more like a mugging — or at least a confidence game or a fraud. It’s violence being done to you right now, under your nose. Just click “like.”

In answer to your question, dear student, that’s my first danger.

* * *

ADDENDUM:

This blog post is already too long, but here is a TL;DR addendum for people who already know about all this stuff.

I’m calling this corrupt personalization because I cant just apply Baker’s excellent ideas about corrupt segments — the world has changed since he wrote them. Although this post’s reasoning is an extension of Baker, it is not a straightforward extension.

Algorithmic attention is a big deal because we used to think about media and identity using categories, but the algorithms in wide use are not natively organized that way. Baker’s ideas were premised on the difference between authentic and inauthentic categories (“segments”), yet segments are just not that important anymoreBermejo calls this the era of post-demographics.

Advertisers used to group demographics together to make audiences comprehensible, but it may no longer be necessary to buy and sell demographics or categories as they are a crude proxy for purchasing behavior. If I want to sell a Subaru, why buy access to “Brite Lights, Li’l City” (My PRIZM marketing demographic from the 1990s) when I can directly detect “intent to purchase a station wagon” or “shopping for a Subaru right now”? This complicates Baker’s idea of authentic segments quite a bit. See also Gillespie’s concept of calculated publics.

Also Baker was writing in an era where content was inextricably linked to advertising because it was not feasible to decouple them. But today algorithmic attention sorting has often completely decoupled advertising from content. Online we see ads from networks that are based on user behavior over time, rather than what content the user is looking at right now. The relationship between advertising support and content is therefore more subtle than in the previous era, and this bears more investigation.

Okay, okay I’ll stop now.

* * *

(This is a cross-post from Multicast.)

Why Snapchat is Valuable: It’s All About Attention

Most people who encounter a link to this post will never read beyond this paragraph. Heck, most people who encountered a link to this post didn’t click on the link to begin with. They simply saw the headline, took note that someone over 30 thinks that maybe Snapchat is important, and moved onto the next item in their Facebook/Twitter/RSS/you-name-it stream of media. And even if they did read it, I’ll never know it because they won’t comment or retweet or favorite this in any way.

We’ve all gotten used to wading in streams of social media content. Open up Instagram or Secret on your phone and you’ll flick on through the posts in your stream, looking for a piece of content that’ll catch your eye. Maybe you don’t even bother looking at the raw stream on Twitter. You don’t have to because countless curatorial services like digg are available to tell you what was most important in your network. Facebook doesn’t even bother letting you see your raw stream; their algorithms determine what you get access to in the first place (unless, of course, someone pays to make sure their friends see their content).

Snapchat offers a different proposition. Everyone gets hung up on how the disappearance of images may (or may not) afford a new kind of privacy. Adults fret about how teens might be using this affordance to share inappropriate (read: sexy) pictures, projecting their own bad habits onto youth. But this is isn’t what makes Snapchat utterly intriguing. What makes Snapchat matter has to do with how it treats attention.

When someone sends you an image/video via Snapchat, they choose how long you get to view the image/video. The underlying message is simple: You’ve got 7 seconds. PAY ATTENTION. And when people do choose to open a Snap, they actually stop what they’re doing and look.

In a digital world where everyone’s flicking through headshots, images, and text without processing any of it, Snapchat asks you to stand still and pay attention to the gift that someone in your network just gave you. As a result, I watch teens choose not to open a Snap the moment they get it because they want to wait for the moment when they can appreciate whatever is behind that closed door. And when they do, I watch them tune out everything else and just concentrate on what’s in front of them. Rather than serving as yet-another distraction, Snapchat invites focus.

Furthermore, in an ecosystem where people “favorite” or “like” content that is inherently unlikeable just to acknowledge that they’ve consumed it, Snapchat simply notifies the creator when the receiver opens it up. This is such a subtle but beautiful way of embedding recognition into the system. Sometimes, a direct response is necessary. Sometimes, we need nothing more than a simple nod, a way of signaling acknowledgement. And that’s precisely why the small little “opened” note will bring a smile to someone’s face even if the recipient never said a word.

Snapchat is a reminder that constraints have a social purpose, that there is beauty in simplicity, and that the ephemeral is valuable. There aren’t many services out there that fundamentally question the default logic of social media and, for that, I think that we all need to pay attention to and acknowledge Snapchat’s moves in this ecosystem.

(This post was originally published on LinkedIn. More comments can be found there.)

Reddit, Mathematically the Anti-Facebook (+ other thoughts on algorithmic culture)

(or, Are We Social Insects?)

I worried that my last blog post was too short and intellectually ineffectual. But given the positive feedback I’ve received, my true calling may be to write top ten lists of other people’s ideas, based on conferences I attend. So here is another list like that.

These are my notes from my attendance at “Algorithmic Culture,” an event in the University of Michigan’s Digital Currents program. It featured a lecture by the amazing Ted Striphas. These notes also reflect discussion after the talk that included Megan Sapnar Ankerson, Mark Ackerman, John Cheney-Lippold and other people I didn’t write down.

Ted has made his work on historicizing the emergence of an “algorithmic culture” (Alex Galloway‘s term) available widely already, so my role here is really just to point at it and say: “Look!” (Then applaud.)

If you’re not familiar with this general topic area (“algorithmic culture”) see Tarleton Gillespie’s recent introduction The Relevance of Algorithms and then maybe my own writing posse’s Re-Centering the Algorithm. OK here we go:

Eight Questions About Algorithms and Culture

  1. Are algorithms centralizing? Algorithms, born from ideas of decentralized control and cybernetics, were once seen as basically anti-hierarchical. Fifty years ago we searched for algorithms in nature and found them decentralized — today engineers write them and we find them centralizing.
  2. OR, are algorithms fundamentally democratic? Even if Google and Facebook have centralized the logic, they claim “democracy!” because we provide the data. YouTube has no need of kings. The LOLcats and fail videos are there by our collective will.
  3. Many of today’s ideas about algorithms and culture can be traced to earlier ideas about social insects. Entomology once noted that termites “failed to evolve” because their algorithms, based on biology, were too inflexible. How do our algorithms work? Too inflexible? (and does this mean we are social insects?)
  4. The specific word “algorithm” is a recent phenomenon, but the idea behind it is not new. (Consider: plan, recipe, procedure, script, program, function, …) But do we think about these ideas differently now? If so, maybe it is who looks at them and where they look. In early algorithmic thinking people were the logic and housed the procedure. Now computers house the procedure and people are the operands.
  5. Can “algorithmic culture” be countercultural? Fred Turner and John Markoff have traced the links between the counterculture and computing. Striphas argued that counterculture-like influences on what would become modern computing came much earlier than the 60s: consider the influence of WWII and The Holocaust. For example, Talcott Parsons saw culture through the lens of anti-authoritarianism. He also saw culture as the opposite of state power. Is culture fundamentally anti-state? This also leads me to ask: Is everything always actually about Hitler in the end?
  6. Today, the computer science definition of “algorithm” is similar to anthropologist Clifford Geertz’s definition of culture in 1970s — that is, a recipe, plan, etc. Why is this? Is this significant?
  7. Is Reddit the conceptual anti-Facebook? Reddit publicly discloses the algorithm that it uses to sort itself. There have been calls for Facebook algorithm transparency on normative grounds. What are the consequences of Reddit’s disclosure, if any? As Reddit’s algorithm is not driven by Facebook’s business model, does that mean these two social media platform sorting algorithms are mathematically (or more properly, procedurally) opposed?
  8. Are algorithms fundamentally about homeostasis? (That’s the idea, prevalent in cybernetics and 1950s social science, that the systems being described are stable.) In other words, when algorithms are used today is there an implicit drive toward stability, equilibrium, or some other similar implied goal or similar standard of beauty for a system?

Whew, I’m done. What a great event!

I’m skeptical about that last point (algorithms = homeostasis) but the question reminds me of “The Use and Abuse of Vegetational Concepts,” part 2 of the 2011 BBC documentary/insane-music-video by Adam Curtis titled All Watched Over by Machines of Loving Grace. It is a favorite of mine. Although I think many of the implied claims are not true, it’s worth watching for the soundtrack and jump cuts alone.

It’s all about cybernetics and homeostasis. I’ll conclude with it… “THIS IS A STORY ABOUT THE RISE OF THE MACHINES”:

All Watched Over By Machines of Loving Grace 2 from SACPOP on Vimeo.

P.S.

Some of us also had an interesting side conversation about what job would be the “least algorithmic.” Presumably something that was not repeatable — it differs each time it is performed. Some form of performance art? This conversation led us to think that everything is actually algorithmic.

Are there feminist data? (+ other questions)

Here’s a quick post containing eight ideas that made it into my notes from today’s “Feminism, Technology, and the BodyFemTechNet dialogue at the University of Michigan. It featured  Alondra Nelson, Jessie Daniels, Lisa Nakamura, Sidonie Smith, Carrie Rentschler, Sharon Irish, and a bunch of other people I didn’t write down. What a crew!

Eight Ideas About Feminism, Technology, and the Body:

 

1. Early ads for the Internet wouldn’t work today. We no longer aspire to leave our bodies behind. Or we can no longer imagine it.  Remember this ad?  (c. 1997)

 

 

2. If we’ve theorized the Internet and the body, what about social media and the body?

3. Is  the selfie inherently anti-feminist?

4. Are there “feminist data?” What are they?

5. “Just add women and stir” won’t work — mixing women and tech together is not in itself progressive. (cf. bell hooks)

6. Whatever happened to the emancipatory cyborg? (Haraway) Is a woman’s body still a trap?

7. Don’t forget where all this comes from. Facebook was born in a sexist moment. It was meant to make Harvard women available to the male gaze.

8. Forget the MOOC, it’s time for the DOCC.(*)

(* – Distributed Online Collaborative Course)

Today’s Technological Middle School

Last night, I went to parent-teacher night at my daughter’s school. Here is a list of things I wrote down that differ from when I went to middle school. Since I’m a social media researcher, many of them have to do with technology and social media. I thought someone else might find them of interest.

Things in middle school today that differ from my childhood:

  • The “loaner Kindles.”
  • Everyone gets a “certificate of participation” for everything.
  • Cyber-bullying prevention assembly is held once each year.*
  • Giant flatscreen TV looks weird on a rolling cart.
  • No recess.
  • Less unstructured time.
  • 20 minute lunch.
  • School day is shorter.
  • Along with Kleenex and colored pencils, the “teacher wish list” has software licenses.
  • “No cut” athletics.
  • All of the good teachers have a Weebly.
  • Video lectures sent home on thumb drives “in case your broadband is slow.”
  • Physical Education (Phys Ed) is optional.
  • Shop classes replaced by computer classes, called “Technical Education” (Tech Ed).
  • The Concussion Awareness Campaign.
  • Most common use of Internet in school: YouTube.
  • Most FAQ from parents: “How often do you post grades on Powerschool?” (Powerschool is proprietary courseware.)
  • Many textbooks are PDFs.
  • As part of a “back strain prevention program” there are two copies of the heaviest textbooks — one for school and one for home.
  • When I was a kid: “school resource officer.” Today: “police-free schools.” (Yes Ann Arbor is liberal and affluent.)
  • Can’t make a move without a contract that the parent and the child has to sign.
  • “For safety,” students not allowed in school building before or after school.
  • Student art projects come home via the equivalent of Cafe Press. We got a mug.
  • Whole school smells strongly of Axe.

* — An actual quote from a handout: “Facebook, cellphone cameras and texting, My Space [sic], FormSpring, X-box live, etc. are just some of the ‘Weapons of Mass Destruction’ that are in your children’s hands.”  

Me: “FormSpring?!”

Me: “Also, ‘My Space’ doesn’t have a space.”

Me: “Also, also, I think ‘My Space’ is over now.”

   

(This is a cross-post from multicast.)

Legal Portraits of Web Users

This Summer I became very interested in what I think I will be calling “legal portraits of digital subjects” or something similar. I came to this through doing a study on MOOCs with SMC this summer. The title of the project is “Students as End Users in the MOOC Ecology” (the talk is available online).  In the project I am looking at what the Big 3 MOOC companies are saying publicly about the “student” and “learner” role and comparing it to how the same subject is legally constituted to try to understand the cultural implications of turning students into “end users”.

As I was working through this project, and thinking of implications outside of MOOCs and Higher Ed, I realized these legal portraits are constantly being painted in digital environments. As users of the web/internet/digital tools we are constantly in the process of accepting various clickwrap  and browse-wrap agreements without thinking twice about it, because it has become a standard cultural practice.

In writing this post I’ve already entered numerous binding legal agreements. Here are some of the institutions that have terms I am to follow:

  1. Internet Service Provider

  2. Web Browser

  3. Document Hosting Service (I wrote this in the cloud somewhere else first)

  4. Blog Hosting Company

  5. Blog Platform

  6. Various Companies I’ve Accepted Cookies From

  7. Social Media Sites

I’ve gone through and read some of the Terms (some of them I cannot find). I’ve allowed for the licensing and reproduction of this work in multiple places without even thinking twice about it.  We talk a lot about privacy concerns.  We know that by producing things like blog post, or status updates we are agreeing to being surveilled to various degrees.  I’d love to start a broader conversation on the effects of agreeing to a multitude of Terms though, not just privacy, simply by logging on and opening a browser.