[This pre­sen­ta­tion was in response to Tarleton Gillespie’s ​“The Relevance of Algorithms”]

Good morn­ing, every­one. It is a com­plete plea­sure to be respond­ing to Tarleton [Gillespie] today because I have found his work so gen­er­a­tive over the last few years, and have enjoyed many con­ver­sa­tions where we’ve grap­pled with these sorts of ideas that Tarleton has raised in his talk this morning. 

And in fact, just lis­ten­ing to you today made me think about a whole new set of ques­tions. In par­tic­u­lar in fact, the anx­i­ety around the female body, which I think recurred three times in your talk, through abor­tion, through the Target preg­nan­cy case, and of course through biki­nis. I’m think­ing, well, that’s a whole oth­er sub­ject for a paper, is why that is such a focus of algo­rith­mic anxiety. 

But in actu­al fact there’s some­thing else I’d like to dig deep­er into today. This is your claim that we need to pay atten­tion to the way that algo­rithms may pro­duce par­tic­u­lar kinds of polit­i­cal effects. But what exact­ly do you mean by the ​“polit­i­cal” here?

So what I would like to do, rather than walk­ing away from the realm of the­o­ry, which Tarleton offered this morn­ing, I’m actu­al­ly going to take us right back there. But from the per­spec­tive of polit­i­cal the­o­ry. And I’d like to think about the log­ics of what Tarleton describes as these cal­cu­lat­ed publics. I’m going to do this by break­ing it down into eight or so—depending how we go for time—scenes about life in cal­cu­lat­ed publics.

Scene 1

A woman is sit­ting in a chair with a lap­top on her knees, and she’s try­ing to buy some books for a con­fer­ence that she’s about to go to called ​“Governing Algorithms.” When she tries to buy Tarleton’s book, Wired Shut, she finds that ​“cus­tomers who bought this item also bought” James Boyle’s The Public Domain, William Patry’s How to Fix Copyright, and Biella Coleman’s Coding Freedom.

So she starts imag­in­ing who this group of imag­ined shop­pers might be. Are they inter­est­ed in the same top­ics as she is? Should she buy a book about reform­ing copy­right law, or should she buy a book which is an ethno­graph­ic account of the Debian com­mu­ni­ty? I mean, they seem like fair­ly dif­fer­ent topics.

So, who are these cus­tomers and what unites them in these par­tic­u­lar tastes? I think we can imag­ine some of these answers, but we can’t know for sure how Amazon has deter­mined them. In fact, even senior Amazon devel­op­ers may not be able to tell us exact­ly how these imag­ined com­mu­ni­ties of cus­tomers have been cre­at­ed and how it’s changed over time as mil­lions of books have been pur­chased, and mil­lions of pro­files have been updated.

Algorithms sim­ply don’t always behave in pre­dictable ways. And this is why we have A/B test­ing, exten­sive, ran­dom­ized test­ing, to observe just how algo­rithms actu­al­ly behave in the field with large datasets. So Tarleton argues that algo­rithms, and I quote, 

…not only struc­ture our inter­ac­tions with oth­ers as mem­bers of net­work publics, but they also traf­fic in these cal­cu­lat­ed publics that they them­selves pro­duce.” Thus Amazon is both invok­ing and claim­ing to know a pub­lic with which we’re invit­ed to feel an affin­i­ty even if they have noth­ing what­so­ev­er to do with the kind of pub­lic that we were orig­i­nal­ly seek­ing out. 

So the woman at the lap­top types in a dif­fer­ent author’s name, Evgeny Morozov. And she’s told that cus­tomers who bought this item also bought, amongst oth­er things, Eric Schmidt’s The New Digital Age, and Kevin Kelly’s What Technology Wants. Are these books sim­i­lar? Well… Have peo­ple like her bought Morozov and Gillespie’s books togeth­er? Not that we know. Instead we’re shown a cal­cu­lat­ed pub­lic. But we don’t know the mem­ber­ship, their con­cerns, whether they loved or hat­ed these books. There’s sim­ply a con­sen­sus. These books and peo­ple are fre­quent­ly rep­re­sent­ed together.

Scene 2

Is talk­ing about the polit­i­cal ram­i­fi­ca­tions of algo­rithms enough? Or can we go a step fur­ther. McKenzie Wark argues that tech­nol­o­gy and the polit­i­cal are not sep­a­rate things. ​“One is sim­ply look­ing at the same sys­tem,” he writes, ​“through dif­fer­ent lens­es when one speaks of the polit­i­cal or the technical.”

Likewise, Alex Galloway notes that we should­n’t focus so much on devices or plat­forms or algo­rithms and such, and more on the sys­tems of pow­er that they mobi­lize. So let’s speak for a moment about algo­rithms as polit­i­cal the­o­ry, and vice versa.

Some thinkers think about algo­rithms as being essen­tial­ly auto­crat­ic sys­tems. We have no input, they make the deci­sions, and we don’t get to see the process­es by which those deci­sions are made. Barbara Cassin has described, on the oth­er hand, how algo­rithms like PageRank appear to have a more delib­er­a­tive, demo­c­ra­t­ic, ethos. And I quote, ​“using graph the­o­ry to val­orize pure het­ero­gene­ity, show­ing how qual­i­ty is an emer­gent prop­er­ty of quantity.”

But what about alter­na­tive polit­i­cal frame­works to this autoc­ra­cy vs. delib­er­a­tive democ­ra­cy? What if say for exam­ple we start­ed to think ago­nis­tic plu­ral­ism? Which is to way we start with the premise of ongo­ing strug­gle (ago­nism), between dif­fer­ent groups and enti­ties (plu­ral­ism), and rec­og­nize that com­plex, shift­ing nego­ti­a­tions are occur­ring between peo­ple, insti­tu­tions, and algo­rithms, all the time and that they’re act­ing in rela­tion to each other?

Scene 3

Chantal Mouffe is being inter­viewed for a polit­i­cal mag­a­zine. She’s sit­ting on a very large, com­fy chair. She’s asked, ​“How do you define democ­ra­cy, if not as a con­sen­sus?” In response she describes the dif­fer­ence between the mod­el of tra­di­tion­al democ­ra­cy, and her notion of ago­nis­tic plu­ral­ism. And I quote,

I use the con­cept of ago­nis­tic plu­ral­ism to present a new way to think about democ­ra­cy, which is dif­fer­ent from the tra­di­tion­al lib­er­al con­cep­tion of democ­ra­cy as a nego­ti­a­tion between inter­ests. While they have many dif­fer­ences, Rawls and Habermas have in com­mon the idea that the aim of a demo­c­ra­t­ic soci­ety is the cre­ation of a con­sen­sus, and that con­sen­sus is pos­si­ble if peo­ple are only able to leave aside their pas­sions and their par­tic­u­lar inter­ests and think like ratio­nal beings. However, while we desire an end to con­flict, if we want peo­ple to be free we must always allow for the pos­si­bil­i­ty that con­flict may appear and to pro­vide an are­na where dif­fer­ences can be confronted.
Mouffe, C. (2000) The Democratic Paradox.

Scene 4

New York City. There’s a group chat hap­pen­ing in the Reddit office. The dis­cus­sion is about what they call their ​“hot sort­ing algo­rithm,” and how posts in some areas of the site become front-page sto­ries with rel­a­tive­ly few upvotes. 

At the same time, in Southern Nebraska, a group of fif­teen year-old girls meet at a friend’s house to dis­cuss how they could influ­ence, or game, Reddit’s sys­tem. They aim to band peo­ple togeth­er to upvote a sto­ry of homo­pho­bic harass­ment of a boy at their school in order to gain media atten­tion and shame the perpetrators.

Scene 5

Can an algo­rithm be ago­nis­tic? So, algo­rithms may be rule-based mech­a­nisms, but they’re also, and some­times we could argue, gov­ern­ing agents, that are choos­ing between com­pet­ing and some­times con­flict­ing data objects. 

So if algo­rithms present us with a new knowl­edge log­ic, as Tarleton has con­vinced us, then it’s impor­tant to con­sid­er the con­tours of that log­ic. What are the his­to­ries and philoso­phies that have most strong­ly shaped them? 

Certainly I think it’s going to be dif­fi­cult to describe any of these algo­rithms as ago­nis­tic. So much of the messy busi­ness of choos­ing between par­tic­u­lar kinds of data points is essen­tial­ly hid­den from us, whether it’s search results, which books are sold togeth­er, which news sto­ries are most rel­e­vant to us.

Much of the algo­rith­mic work of pick­ing win­ners between infor­ma­tion con­tests is going to remain invis­i­ble. Yet these delib­er­a­tions are cru­cial. This is the stuff of lower‑g gov­er­nance. What Maurizio Lazzarato describes as, ​“the ensem­ble of tech­niques and pro­ce­dures put into place to direct the con­duct of men and to take account of the prob­a­bil­i­ties of their action and relations.”

Scene 6

If the pol­i­tics of many of these algo­rithms is com­mon­ly locat­ed on a spec­trum between autoc­ra­cy and delib­er­a­tive democ­ra­cy, I think we could start to dis­cuss the lim­i­ta­tions of those approach­es. In Mouffe’s words, ​“when we accept that every con­sen­sus exists as a tem­po­rary result of a pro­vi­sion­al hege­mo­ny as a sta­bi­liza­tion of pow­er that always entails some form of exclu­sion, we can begin to envis­age the nature of a demo­c­ra­t­ic pub­lic sphere in a dif­fer­ent way.”

And so I think we reach her strongest argu­ment for why think­ing about ago­nism is impor­tant. This is why a plu­ral­ist democ­ra­cy, she writes, ​“needs to make room for dis­sent, and for the insti­tu­tions through which it can be man­i­fest­ed. It’s sur­vival depends on col­lec­tive iden­ti­ties form­ing around clear­ly dif­fer­en­ti­at­ed posi­tions, as well as on the pos­si­bil­i­ty of choos­ing between real alter­na­tives.” And I think that’s a fair­ly key con­cept here.

So this is why it mat­ters whether algo­rithms can be ago­nist, giv­en their roles in gov­er­nance. When the log­ic of algo­rithms is under­stood as auto­crat­ic, we’re going to feel pow­er­less and pan­icked because we can’t pos­si­bly inter­vene. If we assume that they’re delib­er­ate­ly demo­c­ra­t­ic, we’ll assume an Internet of equal agents, ratio­nal debate, and emerg­ing con­sen­sus posi­tions, which prob­a­bly does­n’t sound like the Internet that many of us actu­al­ly recognize.

So instead, per­haps if we start­ed to think about this idea of ago­nis­tic plu­ral­ism, we might start to think about the way in which algo­rithms are choos­ing from coun­ter­posed per­spec­tives with­in a field where ratio­nal­i­ty and emo­tion are giv­en. As an ethos, it assumes per­pet­u­al con­flict and con­stant con­tes­ta­tion. It would ide­al­ly offer the path to choose, I think, away from these dis­ap­point­ing­ly lim­it­ed calls for ​“trans­paren­cy” in algo­rithms, which are ulti­mate­ly kind of doomed to fail, giv­en that com­pa­nies like Facebook and Twitter are not going to give their algo­rithms away, for a whole host of com­pet­i­tive rea­sons, and also because they’re afraid of users gam­ing the system.

Instead, I think to rec­og­nize val­ue of dif­fer­ent per­spec­tives and oppos­ing inter­ests involves an accep­tance of what Howarth calls ​“the rules of the game” and an under­stand­ing that algo­rithms are par­tic­i­pants in wider insti­tu­tion­al and cap­i­tal­ist logics.

Scene 7

Where else do we find ago­nism in the field of algo­rithms? Perhaps the prob­lem here is actu­al­ly the fetishiz­ing of algo­rithms them­selves, with­out widen­ing the per­spec­tive to include the many ways in which algo­rithms are not sta­ble, and they’re always in rela­tion to oth­er peo­ple. That is, they’re in flux and they’re embed­ded in hybrid systems.

For exam­ple, we can look to the offices and the spaces where devel­op­ers are cur­rent­ly com­ing up with algo­rithms, and I think this is where Nick Seaver’s work is real­ly use­ful, where he’s actu­al­ly spend­ing time with peo­ple who are design­ing music rec­om­men­da­tion algo­rithms. We could also look at the spaces where peo­ple and algo­rithms are actu­al­ly play­ing par­tic­u­lar kinds of games. I’m think­ing of Reddit here and the fact that Reddit makes much of its algo­rith­mic process public.

And I think peo­ple actu­al­ly like the way that they can see some of the rules of the game and at least imag­ine how they might game them. It offers a kind of legit­i­ma­cy that I think some of these more closed, opaque sys­tems like Facebook instead pro­duce a kind of suspicion.

Or we could even look to the ways that peo­ple are cur­rent­ly reverse-engineering algo­rithms, where the troll and the hack­er become key play­ers in an ago­nis­tic sys­tem. So by using this wider optic, I think we can see that algo­rithms are always work­ing in con­test­ed, human spaces.

Scene 8

The final word has to go to Tarleton.

In attempt­ing to say some­thing of sub­stance about the way algo­rithms are shift­ing our pub­lic dis­course, we must firm­ly resist putting the tech­nol­o­gy in the explana­to­ry dri­ver’s seat. While recent soci­o­log­i­cal stud­ies of the Internet have tried to undo all the sim­plis­tic tech­no­log­i­cal deter­min­ism that plagued ear­li­er work, that deter­min­ism still remains as a fair­ly attrac­tive ana­lyt­ic stance. Our analy­sis must not con­ceive of algo­rithms as abstract tech­ni­cal achieve­ments, but must unpack the warm, human, and insti­tu­tion­al choic­es that lie behind these cold mechanisms. 

I take this as a use­ful reminder that we need to look beyond algo­rithms as kind of fetish objects, to con­sid­er the devel­op­ers in their cubi­cle farms, the teenage hack­ers who are play­ing on Reddit, the Amazon book buy­ers, and the mul­ti­tude of flesh and blood scenes where humans and algo­rithms engage.

Thanks.