We often struggle to teach our students what "social construction" actually means. (For the record, I am with Woolgar and Latour for taking out "social" and just saying "construction."). Well, here is a Voxsplainer article by Andrew Prokop explaining the outsized importance of the Iowa caucuses that could serve as a great introduction to undergrads on what we STS-types actually mean by social construction. For my money, it makes the a number of points:
"Social construction" doesn't mean that something is not real.
Socially constructed things take other things for granted. These things, while real enough, tend to be also socially constructed and on and on.
Socially constructed things can be really hard to change (see point 2). They require real long-term work to create cultural change, itself a very unpredictable thing.
Over the years, journalist Chris Mooney has made a name for himself as a chronicler of what he has called The Republican War on Science: the numerous battles being fought within/across America's political landscape over issues like global warming, pollution and regulation. As time has gone by, Mooney has also started to draw on social psychological and brain imaging research on political bias: how people interpret scientific findings and facts in the light of their ideological convictions, or as Mooney's article for Mother Jones was titled, "The Science of Why We Don't Believe Science: How our brains fool us on climate, creationism, and the vaccine-autism link." From an STS perspective, these findings, even though couched in the slightly problematic scientistic idiom of social psychology, make perfect sense: they suggest that "data" is always interpreted in the light of previously held beliefs; that facts and values are not easily separable in practice. (Mooney's second book is titled "The Republican Brain" which does sound problematic. But since I haven't read it, I'm not going to comment on it. See this discussion between him and Mother Jones' Kevin Drum: here, here and here.)
In a new article in the Washington Post, Mooney reports on a recent experiment from social psychologist Dan Kahan to argue that you should, yes, trust experts more than ordinary people. Kahan and his collaborators asked the subjects in their pool (judges, lawyers, lawyers-in-training and laypeople, statistically representative of Americans) to interpret whether a given law was applicable to a hypothetical incident; the question was: would they apply the rules of statutory interpretation correctly? So first, they were informed about the law that bans littering in a wildlife preserve. Next they were told that a group of people had left litter behind, in this case, reusable water containers. But there was a catch: some were told that these were left behind by immigration workers helping illegal immigrants cross over the US-Mexico border safely. Others were told that the litter belonged to a construction crew building a border fence. All were polled to understand their political and ideological affiliations. Predictably, depending on their ideological beliefs, people came down on different sides of the issue: Republicans tended to be more forgiving of the construction workers, etc. What was different was that judges and trained lawyers tended, more than laypeople, to avoid this bias. They interpreted the law correctly (the correct answer here was that it didn't constitute littering because the water bottles were reusable) despite their ideological convictions. Well, so far so good. As an anthropologist, I interpret the experiment to be saying that lawyers are subjected to special institutional training, unlike the rest of us, and that this habitus lets them reach the "correct" result far more than us. Experts are different from the rest of us, in some way.
But what's interesting is the conclusion that Mooney draws from this experiment: that while experts are biased, they are less biased than the rest of us, and that therefore, experts should be trusted more often than not. Well. Scientific American's John Horgan has a pragmatic take on this: that this, of course, leaves open the question of which experts to trust, and scientists, like other experts, have been known to be wrong many many many times. To trust experts because they are experts, seems, well, against the spirit of a democratic society. (Another Horgan reponse to Mooney here.)
But I think there's something here about the particular result that Mooney is using to make his point. Something that I can think can help to show that yes, experts matter, but no, that doesn't mean that there's a blanket case for trusting experts more than others. Lawyers and judges do come to different conclusions than the rest of us when it comes to statutory interpretation. But there is one huge elephant in the room: the US Supreme Court, at this very moment we speak, is considering King vs. Burwell, a challenge to the Affordable Care Act that hinges precisely on questions of statutory interpretation. How do you interpret a law that says that the federal government will provide subsidies to insurance exchanges created by "States"? Does "States" mean the states that constitute the United States or does it mean state, in the abstract, whether it's the federal government or the states? How difficult can that be? It seemed very clear in the long battle over the ACA that the subsidies were meant for everyone. But no, the question was contentious enough that that courts disagreed with each other and the Supreme Court took it up. With a good chance that they might rule in a way that destroys the very foundations of the Affordable Care Act.
How might one reconcile the findings of the Kahan study with what's happening with the Supreme Court? The Supreme Court judges are certainly experts, elite, well-trained, and at the top of their respective games. And yet, here they are, right at the center of a storm over what journalist David Leonhardt has called the "federal government's biggest attack on inequality." I think there's a way. Experts are conditioned to think in certain ways, by virtue of their institutional training and practice, and when stakes are fairly low, they do. But once stakes are high enough, things change. What might seem like a fairly regular problem in ordinary times, a mere question of technicality, may not look like one in times of crisis. At this point, regular expert-thinking breaks down and things become a little more contested.
And we do live in a polarized time. As political scientists have shown time andtime again, the polity of the United States experienced a realignment after the Civil Rights movement. The two major parties had substantial overlaps before but now they don't. They cater to entirely different constituencies: the Republicans being the party of managers, evangelicals and the white working class, the Democrats being the party of organized labor, affluent professionals and minorities. Political polarization has meant that even institutions which are supposed to be non-political (but really have never been so) start to look more and more political, because there are basic questions of disagreement over things that may have seemed really simple and technical. This explains the spate of decisions from the Supreme Court where the conservatives and liberals on the bench have split neatly along ideological lines.
But does that mean that judges are just politicians in robes? (Which is the thesis that Dan Kahan and others set out to debunk.) Not really. The US Supreme Court actually resolves many many cases with fairly clear majorities; more than a third of them through unanimous decisions. These cases hardly ever make it into the public eye, and they involve, to us at least, what seem like arcane questions of regulation and jurisdiction. Another way to interpret this is to say that these cases are "technical" because they are not in the public eye, no great "stakes" attach to these decisions, unless it's to the parties in question. When stakes are high -- Obamacare, campaign finance funding, abortion, gay marriage -- the Supreme Court, just like the rest of the country, is hopelessly polarized. And a good thing too because fundamental crises in values are best addressed through Politics (with a capital P) rather than leaving them to bodies of experts.
Does this sound at all familiar to you? STS has come a long way since The Structure of Scientific Revolutions but this is not unfamiliar to what Kuhn calls a time of crisis. Scientists and others have (often in self-serving ways) taken up the message of the book to be that science moves in cycles of innovation: a time of normal science, and then a time of revolutionary science (ergo, starting a new paradigm is the best way to do science). But really, the point of the book that's missed is that the crises that Kuhn talks about (that happen through a buildup of anomalies) are organizational crises; at such times, fundamentally taken-for-granted understandings of what is right and wrong break down. New taken-for-granted understandings emerge, but they emerge along-side a different organizational order.
Social psychological experiments on political bias in the "public understanding of science" need to be understood not as grand truths about how people interpret, but as historically contingent findings. Yes, judges will vote more "correctly" than laypeople, but a toy case presented as part of a social psychological study is not the same as an actual case. Real cases have audiences, as do the judges and the lawyers. I remember when the first original challenge to Obamacare was floated, many liberals (including me) found the question of the constitutionality of the individual mandate ridiculous. Of course, the federal government could mandate that everyone needed to purchase health insurance, that's what governments do! (Not to mention that it provided subsidies to those who couldn't afford it, so it was hardly unjust.) But the case just about squeaked through the Supreme Court in our favor and it could have well gone the other way. Burrell vs King is, if anything, an even sillier case, but no one is underestimating it anymore.
It seems like social psychological studies of "bias" might be doing in this day and age what the social studies of scientific expertise did many years ago. Although Mooney seems to misunderstand the point of science studies. These studies weren't meant to show that experts are "biased." They were meant to show that that expert practices and discourse are designed to construct certain questions as "technical." This is not necessarily a bad thing, but it does, at certain points, drown out other voices who disagree with the experts' conclusion (again, this is true of all political choices, usually). What is more, once experts are framed as objective and arguing only from facts rather than values, opposing voices, who have no recourse to the language of facts, get delegitimized even further. STS recommendations were not that you need to trust experts more or less, but that questions about competing values needed to be brought to the fore in public debates that involved science and technology (along with technical expertise, of course). And while scientific and legal experts work in different institutional ecologies, all experts work within institutional ecologies, which means their work is shaped by their collective understandings of what is technical and what is not. The solution is not to trust experts more but to find better ways to debate differences in fundamental values, while still using what we can from experts.
This blog has been quiet for a while but I had two posts at the CASTAC blog in the past two months.
The first one, titled Crowdsourcing the Expert, points out that computer scientists have now turned their attention to more sophisticated forms of crowdsourcing: not just crowds of uniform homogeneous click-workers, but also crowds of experts. The crowdsourcing platform is now seen as a manager, not just for the unskilled worker, but also for the creative classes? And what about the expertise of computer scientists themselves which is left fairly undefined? Anyway, read the whole thing if it strikes your interest.
The second one is about Alan Turing. I summarize some recent articles on Alan Turing and computer science published by historians Thomas Haigh and Edgar Daylight, where they suggest that some of the recent commemorations of Alan Turing are not quite historically accurate. But fascinating nonetheless because they show us how computer science, as a discipline, was constituted.
I wrote up a post for the CASTAC blog suggesting that the recent debates about airline seat space (do we have a right to recline? do we have a right to have more knee-space?) might be good fodder for teaching undergraduates about the relationship between technology and politics. Particularly, the device known as the Knee Defender.
I submit that the Knee Defender might be a great test-case for an introductory STS class (right there with the speed-bump) to teach undergraduates about the relationship between technology and politics. Three reasons: there is a big-picture story about the air-line industry that undergraduates might enjoy parsing; there is a concrete material environment–the inside of an aircraft–that the Knee Defender operates in; and finally, debates over this device can be a great introduction to the vexed concept of ideology.
Recently, I talked to a doctor and public health professional about the relationship between science and policy; he told me, in a vivid metaphor, of how things work, and should work, in the regulatory process. The science produces the facts, which then get funneled through our values through the process of politics. What comes out of this machine, he said, are policies.
It was quite a beguiling vision, but as an STS person, I couldn't help asking: did he really believe in it? Yes, he said. I pressed on. How, I asked, would he explain the controversy over global warming? Why was it difficult to implement policy when the scientists had a decent agreement over the facts? His answer was that it was Fox News, fed by the big bad industry, which had fooled certain people into not believing the scientists. I asked if it might not be more useful to wonder whether this disagreement over what to do about climate change (or about whether anthropogenic climate change even exists) might be an indication of something deeper: perhaps a reflection on the particular ways in which American society is now polarized rather than about Fox News brainwashing susceptible viewers. He didn't think so, he said. (He objected strenuously to my use of the word "brainwashing"; I took it back, but I maintain that it was an accurate descriptor of what he was saying.) I asked at the end what he thought should be done about all of this. He said it was a long-term project; but it began with education; scientific literacy had to begin at a very early age. Only then would people stop listening to Fox News. At that point, I gave up.
I admit that there is something really alluring about this picture of a science that produces facts which are then funneled through our values by the process of politics, all of which combines to produce rational public policy. Even if we admit that this isn't really how it works in practice, perhaps this is how it should work.
But even holding on to this vision as a normative ideal may not be in our best interests. As Sheila Jasanoff and Bryan Wynne have shown, this is because the process of science is shot through and through with values. Wynne suggests that scientific models to measure risk (e.g. risk analysis, cost-benefit calculations) often contain hidden assumptions and prescriptions: about what it means to be social and human, and what an ideal social order should be. These visions of the human and the social are often found wanting by different publics. E.g., the language of risk analysis comes coded with what a risk is or is not, and what things humans should worry about, points about which different publics disagreed but a) did not have the tools to express their disagreement, and b) were not taken seriously by experts and understood as only lacking an understanding of the science. One of Jasanoff's suggestions is that rather than trying to cure science of its values, or create a politics that is based on "facts," we accept the value-riddenness of science and use that to think about how expert advice fits into the political process. (Needless to say, I agree.)
All of which brings me the real reason why I'm writing this: this Scientific American blog-post which the worst combination, in my mind, of two overlapping tendencies: the plague-on-both-houses bipartisan strategy of journalism (something that journalist James Fallows calls "false equivalence"), and the dichotomous conception of "science" and "politics" as two mutually opposing entities.
The post details the ways in which the EPA's efforts to establish a new regulatory standard for drinking water, with an even smaller permitted amount of arsenic in it, were stymied by a Republican Congress. The contours of the story itself will not surprise anyone. Surveying some of the research that had been conducted, the EPA was on the verge of making official its stance that arsenic was a more dangerous carcinogen than it had originally thought. This would be a prelude to a tougher drinking water standard. Naturally, this meant that corporations that produced arsenic or used arsenic in their products lobbied hard to make sure this didn't happen. In these polarized days of American politics, it made sense to turn to the Republican party. And the Republicans delivered by delaying the process. Essentially, they got the the National Academy of Sciences (NAS) do an independent review. Read the whole piece; it's detailed and precise to the point where it can exhaust the reader.
And here my problems begin. Take the headline:
Politics Derail Science on Arsenic, Endangering Public Health
Why "Politics" and "Science"? Why not say "Republicans Derail Science on Arsenic"? Or even better and my personal preference: "Republicans derail EPA on Arsenic"?
Then take the leading line after the headline:
A ban on arsenic-containing pesticides was lifted after a lawmaker disrupted a scientific assessment by the EPA.
Again, why this coyness about the identity of this "lawmaker"? Why not mention upfront that that this is a Republican congressman? Why does it take until well into half-way into the article to identify the offending Congressman: Mike Simpson of Idaho?
Why, for example, is this sentence worded in this particular way when we know we're talking about the Bush White House?
The White House at that point had become a nemesis of EPA scientists, requiring them to clear their science through OMB starting in 2004.
The piece, for all its commendable whistle-blower reporting, contains the worst tendencies of what journalist James Fallows has called "false equivalence" in journalism, which is the plague-on-both-houses stance (see Fallows' copiouscollection of examples). Essentially, newspaper reporting has a tendency to blame both political parties, or politics in the abstract, when things reach a bad state. Here the newspaper is seen as above politics, which is what grubby politicians do. And therefore the contrast between the policy that the newspaper is advocating (which is not politics but merely good moral sensible stuff), and that what the politicians are doing, which is bad, i.e. politics. E.g., the tendency to see the US Congress itself as dysfunctional, rather than the threats of the Republican Congressmen to filibuster pretty much any legislation.
The same forces are at work in the Scientific American piece. Notice that the piece is not explicitly portrayed as a Republicans vs. the EPA piece but rather as a Politics vs. Science piece. If I had to caricature it, the main point is: science good, politics bad. The problem is that this often serves to paint politics itself as grubby and well, dishonest.
This also leads to a manifest lack of curiosity about certain topics. You might wonder why the makers of the arsenic-containing herbicide choose to work through the Republican Party and not the Democratic Party. There's no way you could answer this question without looking at the broader trends in American politics over the last 50 years. The two parties now occupy non-overlapping spaces on the political spectrum: the Democrats are a hodge-podge of interest groups: minorities, relatively affluent social liberals, unions, etc; the Republicans, on the other hand, have only two constituencies: evangelicals and big business. Perhaps, 50 years ago, a business that wanted to fight a piece of regulation, would have had to think harder before deciding which political channel to use; today, it doesn't take more than a minute to decide what to do.
I understand that this is perhaps unfair criticism. The piece is long enough, and talking about the realignment of American politics will only make it longer. But that's exactly the point: if you black-box both science and politics, and paint the regulatory battle in question as a contest between them, then you don't need to think deeply about either. Framing the article as the Republicans' battle against the EPA would have required the writers to ask the question of why these two actors are arrayed against each other. Editorial choices matter.
But the worst thing about the article is what's NOT even in it. What, one would wonder, is a citizen to do after reading it? The article doesn't say but I have an answer: call or write to your Congressman (especially the Republican ones but it doesn't really matter). Tell him or her that you think the gutting of the EPA's power is something you don't agree with. That you believe in a robust regulatory structure with teeth. That perhaps you believe in a more take-precautions-first European style of regulation rather than a do-it-first-deal-with-consequences-later American style of regulation. Why couldn't the SciAm article include a link for us to call or email our Congressmen? Because that would have been too political, that's why. And why should we bother with grubby politics when the science is in our favor?
One of the recent revelations for me has been how easy the Web can make it for us to call or email our legislators to inform them about our opinions on particular issues. The techies did it really effectively with their "blackout" in protest of SOPA and PIPA. Recently, in protest against the FCC's proposal to gut net neutrality, we were able to flood the FCC's comment-solicitation notice board with some good arguments for net neutrality. At heart, this is just good old-fashioned politics, trying to convince our fellow-citizens about the rightness and wrongness of certain causes, sometimes celebrating victory, at other times, accepting defeat and vowing to fight another day [1].
Now I understand that explicitly political action might not be feasible for certain organizations responsible for the article, a collaboration between the Center for Public Integrity, and the Center for Investigative Reporting, both of which may have explicit prohibitions (because of their funding model, for e.g.) against participating explicitly in politics. But that's part of what's got to change because that's the most important shortcoming of the science-vs.-politics narrative. It precludes avenues of action for citizens. What do you do? Trust science, which is what the SciAm investigative piece seems to suggest? Despair that your representatives are morally and politically corrupt [2]? Or do the hard work of politics and convince your fellow-citizens that they're better off having a robust EPA? I vote for the latter.
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Notes
[1] Certainly, citizens are starting to participate in science-politics in other ways, most importantly, through the practices of citizen science. Citizen science is perhaps the most interesting way of making science "impure." But making phone-calls to your legislators, voting, giving money to causes you deem fit, are also equally good ways of participating in the political process.
[2] And that, perhaps, explains why the show of our times is Netflix's House of Cards. More on that another time.
In the past few months, I've been blogging at multiple places and as a result, have completely neglected this blog. In the future, when I post somewhere else, I will cross-post it here, or at least, post a link. In the meantime, though, here are some of the posts I wrote recently:
Also, for the CASTAC blog, a revised post on the phenomenon called "data science" where I speculate that the proliferation of claims about "big data" is more about a crisis in professional identities (who has the expertise to work on particular problems: those with domain knowledge or those with data manipulation skills?) rather than an epistemological crisis (can we analyze phenomena without pre-existing theory?).
The Annual Meeting of the Society of the Social Studies of Science this year (i.e. 4S 2013) was full of "big data" panels (Tom Boellstorff has convinced me to not capitalize the term). Many of these talks were critiques; the authors saw big data as a new form of positivism, and the rhetoric of big data as a sort of false consciousness that was sweeping the sciences*.
But what do scientists think of big data?
In a blog-post titled "The Big Data Brain Drain: Why Science is in Trouble," physicist Jake VanderPlas (his CV lists his interests as "Astronomy" and "Machine Learning") makes the argument that the real reason big data is dangerous because it moves scientists from the academy to corporations.
But where scientific research is concerned, this recently accelerated shift to data-centric science has a dark side, which boils down to this: the skills required to be a successful scientific researcher are increasingly indistinguishable from the skills required to be successful in industry. While academia, with typical inertia, gradually shifts to accommodate this, the rest of the world has already begun to embrace and reward these skills to a much greater degree. The unfortunate result is that some of the most promising upcoming researchers are finding no place for themselves in the academic community, while the for-profit world of industry stands by with deep pockets and open arms. [all emphasis in the original]
His argument proceeds in three steps: first, he argues that yes, new data is indeed being produced, and in stupendously large quantities. Second, processing this data (whether it's in biology or physics) requires a certain kind of scientist who is both skilled in statistics and software. Third, because of this, "scientific software" which can be used to clean, process, and visualize data becomes a key part of the research process. And finally, this scientific software needs to be built and maintained, and because the academy evaluates its scientists not for the software they build but for the papers they publish, all of these talented scientists are now moving to doing corporate research jobs (where they are appreciated not just for their results but also for their software). That, the author argues, is not good for science.
Clearly, to those familiar with the history of 20th century science, this argument has the ring of deja vu. In The Scientific Life, for example, Steven Shapin argued that the fear that corporate research labs would cause a tear in the prevailing (Mertonian) norms of science, by attracting the best scientists away from the academy, was a big part of the scientific (and social scientific) landscape of the middle of the 20th century. And these fears were largely unfounded (partly, because they were largely based on a picture of science that never existed, and partly because, as Shapin finds, scientific virtue remained nearly intact in its move from the academy to the corporate research lab.) [And indeed, Lee Vinsel makes a similar point in his comment on a Scientific American blog-post that links to VanderPlas' post.]
But there's more here, I think, for STS to think about. First, notice the description of the new scientist in the world of big data:
In short, the new breed of scientist must be a broadly-trained expert in statistics, in computing, in algorithm-building, in software design, and (perhaps as an afterthought) in domain knowledge as well. [emphasis in the original].
This is an interesting description on so many levels. But the reason it's most interesting to me is that it fits exactly with the description of what a computer scientist does. I admit this is a bit of a speculation, so feel free to disagree. But in the last few years, computer scientists have increasingly turned their attention to a variety of domains: for example, biology, romance, learning. And in each of these cases, their work looks exactly like the work that VanderPlas' "new breed of scientist" does. [Exactly? Probably not. But you get the idea.] Some of the computer scientists I observe who design software to help students learn work exactly in this way: they need some domain knowledge, but mostly they need the ability to code, and they need to know statistics both, in order to create, machine learning algorithms, as well as to validate their argument to other practitioners.
In other words, what VanderPlas is saying that practitioners of the sciences are starting to look more and more like computer scientists. His own CV, which I alluded to above, is a case in point: he lists his interests as both astronomy and machine learning. [Again, my point is not so much to argue that he is right or wrong, but that his blog-post is an indication of changes that are afoot.]
His solution to solving the "brain drain" is even more interesting, from an STS perspective. He suggests that the institutional structure of science should recognize and reward software-building so that the most talented people stay in academia and do not migrate to industry. In other words, become even more like computer science institutionally so that the best people stay in academia. Interesting, no?
Computer science is an interesting field. The digital computer's development went hand-in-hand with the development of cybernetics and “systems theory”—theories that saw themselves as generalizable to any kind of human activity. Not surprisingly, the emerging discipline of computer science made it clear that it was not about computers per se; rather, computers were the tools that it would use to understand computation—which potentially applied to any kind of intelligent human activity that could be described as symbol processing e.g. see Artificial Intelligence pioneers Newell and Simon’s Turing award speech. This has meant that computer science has had a wayward existence: it has typically flowed where the wind (meaning funding!) took it. In that sense, its path has been the polar opposite to that of mathematics, whose practitioners, as Alma's dissertation shows, have consciously policed the boundaries of mathematics. (Proving theorems was seen to be the essence of math; anything else was moved to adjoining disciplines.)
*The only exception to this that I found was Stuart Geiger's talk which was titled "Hadoop as Grounded Theory: Is an STS Approach to Big Data Possible?," the abstract of which is worth citing in full:
In this paper, I challenge the monolithic critical narratives which have emerged in response to “big data,” particularly from STS scholars. I argue that in critiquing “big data” as if it was a stable entity capable of being discussed in the abstract, we are at risk of reifying the very phenomenon we seek to interrogate. There are instead many approaches to the study of large data sets, some quite deserving of critique, but others which deserve a different response from STS. Based on participant-observation with one data science team and case studies of other data science projects, I relate the many ways in which data science is practiced on the ground. There are a diverse array of approaches to the study of large data sets, some of which are implicitly based on the same kinds of iterative, inductive, non-positivist, relational, and theory building (versus theory testing) principles that guide ethnography, grounded theory, and other methodologies used in STS. Furthermore, I argue that many of the software packages most closely associated with the big data movement, like Hadoop, are built in a way that affords many “qualitative” ontological practices. These emergent practices in the fields around data science lead us towards a much different vision of “big data” than what has been imagined by proponents and critics alike. I conclude by introducing an STS manifesto to the study of large data sets, based on cases of successful collaborations between groups who are often improperly referred to as quantitative and qualitative researchers.
Frankly, that's the only word that I can think of. [****SPOILERS FOLLOW****]. The show ended with what can only be called a bang for Walt. He found a way to give his family his money without them knowing, found a way to see them, he killed the evil Nazis, he set Jesse free and then, well, and then he died. Or something. The whole thing was a wish-fulfillment fantasy from start to finish.
Why do I care? Not so much because I think that characters that are bad need to be punished. But because there is a coherence and an atmosphere to any show or a movie and this finale violated every one of them.
Take Elliott and Gretchen for instance. Breaking Bad has been very coy about what exactly transpired between Walt and the Schwartzes or why he and Gretchen broke up. But the show took the characters seriously. It made it seem as if the story behind Grey Matter Inc. had substance. Walt and Skyler's visit to Elliott's birthday party had a pathos to it, and Walt's last confrontation with Gretchen had bite.
None of that mattered yesterday. The Schwartzes were completely transformed--they were cartoons; rich and pampered people who had robbed Walt of what was rightfully his. I laughed when Gretchen screamed as Walt did his "Boo" thing to them. But it only subtracted from what the show has spent the last 6 seasons doing: carefully, assiduously, building even its peripheral characters.
And my beef isn't that the episode was wildly unrealistic and implausible. (Walt not only gets out of New Hampshire, but manages to drive all the way to New Mexico, threaten Elliott and Gretchen, talk to Skyler (slipping through a police dragnet) and then kill all the villains.) No. For all its virtues, Breaking Bad has never been what one might call a "realistic" show. In a sense, the Season 5 finale was similar to the Season 4 finale where Walt, improbably, vanquishes Gus Fring, the drug king ("I won," he declares at the end of that season). I should confess that I enjoyed that ending (and I wish that the show that ended without a fifth season). But the show's tone was different then. It was unquestionably a thriller, even as its characters suffered and made ambiguous choices. In the second half of Season 5, it had tipped from being a thriller into full-fledged tragedy. Jesse and Walt were irrevocably estranged, as were Walt and Hank Schraeder, Hank is killed and Jesse had probably been subjected to every humiliating situation one could think of (meth slavery seemed like a fitting climax). In the face of such tragedy (Hank dies in "Ozymandias," and Jesse's ex-girlfriend Andrea is brutally executed in "Granite State"), the last episode's almost upbeat tone came as a bit of a shock. This is how thrillers end, and not tragedies, and at this point, I don't think Breaking Bad was a thriller. I confess I have no idea how the show should have ended -- but this particular ending was, just, unseemly.
The hoity-toity magazine N+1 has a long, rambling editorial about sociology [1]. The editorial is long -- far too long -- and I'm inclined to think that
it is facetious and tongue-in-cheek. Still, I think it contains within
it an important misconception about what sociology is and does.
The argument, if I have it right, goes something like this: sociology, the Editors think, has gone too far in taking a calculative, demystifying stance
on human affairs. And as sociology never stays within the academy but
leaks out, this has made the public (or at least the public that the N+1
editors have dinner parties with) far too calculative as well.
Naturally, the Editors aren't really worried about other things that sociology has
demystified, say, religion or technology. They are mostly concerned about art and the
novel. They worry that far too many works of art are discussed in terms of the gain and loss of cultural capital by the artist. People interpret various moves that artists make as merely strategies or positioning. We are not earnest anymore, not passionate; we are merely cold and calculating analysts, never more so than with respect to art. Sociology's analysis of art -- the works of Bourdieu or Becker, say, and many others -- often makes it seem as if "art mostly expresses class and status hierarchies, and only secondarily might have snippets of aesthetic value." The Editors are worried about aesthetics. "There is still," they suggest, "a space where the aesthetic may be
encountered immediately and give pleasure and joy uninhibited by
surrounding frameworks and networks of rules and class habits."
I get the argument, as far as it goes [2]. And let's also grant that in certain circles frequented by the Editors, this does happen. There's far too much sociologizing, far too much analyzing of the moves that people make as an expression of their effort to conserve their cultural position, and far too little discussion of aesthetics. How new is this? And how much should we blame cultural sociology for this, especially the post-structuralist variety?
Let's take one example that the editorial cites, the case of Jeff Bezos:
We’ve reached the point at which the CEO of
Amazon, a giant corporation, in his attempt to integrate bookselling and
book production, has perfectly adapted the language of a critique of
the cultural sphere that views any claim to “expertise” as a mere mask
of prejudice, class, and cultural privilege. Writing in praise of his
self-publishing initiative, Jeff Bezos notes that “even well-meaning
gatekeepers slow innovation. . . . Authors that might have been rejected
by establishment publishing channels now get their chance in the
marketplace. Take a look at the Kindle bestseller list and compare it to
the New York Times bestseller list — which is more diverse?”
Bezos isn’t talking about Samuel Delany; he’s adopting the sociological
analysis of cultural capital and appeals to diversity to validate the
commercial success of books like Fifty Shades of Grey, a badly
written fantasy of a young woman liberated from her modern freedom
through erotic domination by a rich, powerful male. Publishers have
responded by reducing the number of their own “well-meaning
gatekeepers,” actual editors actually editing books, since quality or
standards are deemed less important than a work’s potential appeal to
various communities of readers. [my emphasis.]
The Editors seem to imply that Bezos read Bourdieu and then came up with his strategy of how to attack those who opposed Amazon's self-publishing initiatives on aesthetic grounds (exhibit one: the N+1 Editors themselves) i.e. characterize them as gatekeepers trying to protect their fiefdom.
How true is this? My guess is not at all. Bezos may well have read Bourdieu but there is nothing new whatsoever about his strategy; it's hundreds of years old and definitely older than when the word "cultural capital" was invented. Take a look, for example, at Andrew Abbott's brilliant sociological history of the professions. When different groups warred over a task (doctors and nurses over medical care, accountants and lawyers over certain kinds of corporate money management, psychiatrists and psychologists over how mental problems should be treated), they have always resorted to some version of this language of gate-keeping to characterize the other side. As Wendy Espeland says: "our tendency [is] to see others as having interests where we have commitments." Sociologists have often taken this as their fundamental problem asking: how does this come to be? What does this say about the production of the social order? And so on.
In other words, sociologists did NOT invent demystification in the academy from where it supposedly diffused across society so that now even Jeff Bezos adopts the language of cultural capital, interests and gate-keeping. It was already there, has always been there, and usually comes to the fore when controversies arise [3].
Take the passing of the Affordable Care Act, for instance. Throughout the debate, Republicans alleged that the ACA was a thinly veiled attempt at the redistribution of income, and an effort to take control (of medical decisions) away from families and into the hands of the federal government. They portrayed themselves as standing for seniors, and Obama as a socialist. Democrats, for their part, suggested that Republicans did not care about the uninsured, and only cared about protecting the interests of the insurance companies. Insurance companies, often working behind the scenes, were demonized by everyone but doctors were usually not. Seniors were quite sure that the ACA was an effort to take away the health-care that they rightfully deserved. Throughout the debate, you saw actors imputing tawdry "interests" to their opponents and portraying themselves as being committed to certain values. You might say that they had all gone and read Bourdieu. Or you might say that this is how social controversies are fought and settled.
Or, take MOOCs (MassiveOpenOnline Courses, for those who haven't heard of them), for instance. MOOCs have been the topic of great dispute in the public sphere. And in the debate, you see the same confluence of imputed interests and personal commitments. The much-famous open letter that the philosophy faculty at San Jose State University wrote to Michael Sandel suggested that MOOCs might be part of a neoliberal transformation of the university and an ongoing commodification of education (classes produced at a factory at Harvard, then distributed to community colleges and state universities, which then only need to hire TAs, and so on), and not so much about improving access for students. On the other hand, MOOC inventor Sebastian Thrun emphasizes the kind of easy acccess that made his Artificial Intelligence course at Stanford so famous:
Yet there is one project he's happy to talk about. Frustrated that
his (and fellow Googler Peter Norvig's) Stanford artificial intelligence
class only reached 200 students, they put up a website offering an
online version. They got few takers. Then he mentioned the online course
at a conference with 80 attendees and 80 people signed up. On a Friday,
he sent an offer to the mailing list of a top AI association. On
Saturday morning he had 3,000 sign-ups—by Monday morning, 14,000.
In the midst of this, there was a slight hitch, Mr. Thrun says. "I
had forgotten to tell Stanford about it. There was my authority problem.
Stanford said 'If you give the same exams and the same certificate of
completion [as Stanford does], then you are really messing with what
certificates really are. People are going to go out with the
certificates and ask for admission [at the university] and how do we
even know who they really are?' And I said: I. Don't. Care."
Aaron Bady, a graduate student at Berkeley and one of the hottest voices in the blogosphere says: "not so fast!" Bady plays up Thrun's tenure at Google, suggests that Thrun is interested not so much in improving access as much as increasing Google's bottom line:
The MOOC that debuted in IHE in December 2011 was Sebastian Thrun’s
“Artificial Intelligence” MOOC, a course that was offered at Stanford
but opened up to anyone with a broadband. The way this story is usually
told is that his incredible success—160,000 students, from 190
countries—encouraged Thrun to leave Stanford to try the new mode of
pedagogy that he had stumbled upon. He had seen a TED talk given by
Salman Khan, the founder of Khan Academy, and when he decided to give it
a whirl and it was a huge success, the rest is history. In January,
2012, he would found the startup Udacity.
However, another way to tell the story would be that Thrun was a
Google executive—who was already well known for his work on Google’s
driverless car project—and that he had already resigned his tenure at
Stanford in April 2011, before he even offered that Artifical
Intelligence class. Ending his affiliation with Stanford could be
described as completing his transition to Silicon Valley proper. In
fact, despite IHE’s singular “a Stanford University professor,” Thrun
co-taught the famous course with Google’s Director of Research, Peter
Norvig.
It’s important to tell the story this way, too, because the first
story makes us imagine a groundswell of market forces and unmet need, a
world of students begging to be taught by a Stanford professor and
Google, and the technological marvels that suddenly make it possible.
But it’s not education that’s driving this shifting conversation; as the
MOOC became something very different in migrating to Silicon Valley,
it’s in stories told by the New York Times, the WSJ, and TIME magazine
that the MOOC comes to seem like an immanent revolution, whose pace is
set by necessity and inevitability.
You might say that this actually proves the Editors' point because Bady is a graduate student and has definitely read his Bourdieu. I would suggest that that would be missing the big picture. The point is: this kind of debate, with imputations of nefarious interests and declarations of personal commitment, are routine, especially in the midst of social controversies. Blaming cultural sociology for this is giving academics too much credit [4].
In fact, sociologists (and historians, and anthropologists, and literary studies scholars, and most scholars of the humanities) have always grappled with a strange paradox. Sociologist study "society"--an object that is itself a can of worms. Society is more than the sum of the people who constitute it. Yet, when one starts investigating the social world, one discovers that most people are themselves lay-sociologists. Or to put it in a different way, sociologists themselves are trying to come up with a more systematic version of what people do routinely in their life. They analyze their own social world, their "society" and strategize. Parents spend a great deal of time managing their children's spare time because they know this will serve the child well later on in life. Teenagers routinely think about what they want to do for a living; they know that going to a good college is a big part of achieving it. People spend a great deal of time picking spouses and friends. They may not always succeed in getting what they want, but they think about it nevertheless.
Academic sociology then is built on the foundation of everyday reasoning [this, in fact, is the central insight of Harold Garfinkel's ethnomethodology]. All sociological concepts--power, prestige, cultural capital, class, race, gender--are based on everyday versions of these categories. And in fact, one of the divides in sociology--between qualitative and quantitative sociologists--is based precisely on different understandings of this relationship between this scholarly and lay sociology. At the risk of over-simplifying, most quantitative sociologists will acknowledge this relationship but suggest that a reliance on large numbers, aggregates and the methods of statistics can be a useful way of differentiating specialist sociology from its lay variant. And qualitative sociologists believe that because actors are always theorizing about their own circumstances, this understanding needs to be part of any theory about society.
Let me end on a tongue-in-cheek note (which will probably drive the Editors up a wall). A while ago, A. O. Scott wrote on an essay on a number of smart young men and women who had all teamed up to start two little magazines.
"You'd better mean something enough to live by it," Kunkel told me,
echoing both his fictional creation and, as it happens, one of his
comrades in another literary enterprise. On the last page of the first
issue of n+1, a little magazine that made its debut last year, the
reader learns that "it is time to say what you mean." The author of that
declaration, a forceful variation on some of Dwight Wilmerding's more
tentative complaints, is Keith Gessen, who edits n+1 along with Kunkel,
Mark Greif and Marco Roth. All four editors are around Dwight's age -
he's 28 when the main action in the book takes place; they're 30 or a
little older. Like him, they often glance anxiously and a bit
nostalgically backward to a pre-9/11, pre-Florida-recount moment that
seems freer and more irresponsible than the present. You wouldn't,
however, call any of them any kind of idiot. Nor, based on their
pointed, closely argued and often brilliantly original critiques of
contemporary life and letters, would you accuse them of indecision,
though they do sometimes display a certain pained 21st-century
ambivalence about the culture they inhabit.
N+1 is not the first
small magazine to come out of this ambivalence or the first to have its
mission encapsulated by a memoiristic account of the attempt to figure
out one's life. Consider the following scrap of dialogue from Dave
Eggers's "Heartbreaking Work of Staggering Genius," famously hailed as
the manifesto of a slightly earlier generational moment:
"And how will you do this?" she wants to know. "A political party? A march? A revolution? A coup?""A magazine."
Eggers
is talking about an old (in fact, a defunct) magazine called Might, but
never mind. Even with a bit of historical distance - five years after
the book's publication, a decade and more after the events it describes -
these lines capture both a moment and the general spirit of the
magazine-starting enterprise. A bunch of ambitious, like-minded young
friends get together to assemble pictures and words into a sensibility -
a voice, a look, an attitude - that they hope will resonate beyond
their immediate circle.
And yet, look at how these nice young men met:
The four editors of n+1 are also connected by shared sensibilities and
school ties. Kunkel, who grew up in Colorado, went from Deep Springs
College, a tiny, all-male school in the California desert devoted to the
classical ideal of rigorous study in a pastoral setting, to Harvard,
where he met Greif, though not Gessen, who was also there at the time.
(Actually, they later discovered that they did have one brief encounter
as undergraduates, about which Kunkel would say only that at least one
of them was drunk and that one suggested the other should get a
lobotomy.) Gessen, who lived in the Soviet Union until he was 6, was a
football player at Harvard and went on to get an M.F.A. in fiction from
Syracuse. Greif entered the Ph.D. program in American studies at Yale,
where he met Roth, who had arrived via Oberlin and Columbia to pursue
his doctorate in comparative literature. After talking about it for
years - another friend from Harvard, Chad Harbach, who edits the n+1 Web
site, thought of the name back in 1998 - they decided the moment was
right to put their ideas and aspirations into print.
Harvard and Yale. Hmmm. I'm dying to use the term "cultural privilege" but I won't.
I don't mean to doubt the Editors' sincerity or commitment to producing a certain kind of literature. But the fact remains that in order to fulfill any high-minded goals, you need to descend to the ground, to use existing resources. The Editors all meant through social networks that were spawned by attending elite universities. They decided to start a magazine--not a blog, and not an only-online publication. They made -- or were constrained to make -- certain kinds of choices to reach their goals. And finally, they were the object of a piece in --of all places! -- the New York Times Magazine that vastly improved their magazine's visibility (I, certainly, had not heard of N+1 until I read Scott's piece). In Scott's article, the Editors go out of their way to assert what makes their magazine different, their commitment to a certain style of writing, of seeing the world. Other magazines, they suggest, are moribund, caught up in a rut; N+1 is fresh and young.
To me, what the Editors are doing in that piece is a version of the "impute interests to others, values to self" rhetoric that they then criticize in an editorial published many years later and blame on academic cultural sociology. Which only goes to show that the phenomenon itself has been around a long long time.
[1] And of course, written in its characteristic style with the imperial
"we," that, to me at least, often feels like a reference to the small
segment of the cultural elite they feel an ineffable bond with.
[2] I am not sure who these people are who analyze art at dinner parties
using cultural sociology. In the circles I hang out with, art is still
discussed with reference to aesthetics. And nothing that I read in high
culture magazines like the New York Review of Books or the New Republic
convinces me that we now discuss art in terms of art-makers managing
cultural capital rather than its deep aesthetic value.
[3] "Always" may be an overstatement. But certainly one sees examples of this from the early modern period.
[4] That said, it's always flattering when someone credits the humanities with that much influence.
Ian Hacking, in one his articles, praises the uniquely French form of
the interview as a great way to understand the author's thoughts. He's
talking about Foucault--and indeed, some of Foucault's interviews are
far easier to understand than his books. In that same spirit--i.e. it
lays out the lay of the land on which these debates are staged--I liked
this interview with Vivek Chibber in Jacobin
on his new book "Post Colonial Theory and the Specter of Capital,"
which criticizes post-colonial theory and urges a return to good
old-fashioned Marxism.
The argument goes like
this: the universalizing categories associated with Enlightenment
thought are only as legitimate as the universalizing tendency of
capital. And postcolonial theorists deny that capital has in fact
universalized — or more importantly, that it ever could universalize
around the globe. Since capitalism has not and cannot universalize, the
categories that people like Marx developed for understanding capitalism
also cannot be universalized.
What this means for postcolonial
theory is that the parts of the globe where the universalization of
capital has failed need to generate their own local categories. And more
importantly, it means that theories like Marxism, which try to utilize
the categories of political economy, are not only wrong, but they’re
Eurocentric, and not only Eurocentric, but they’re part of the colonial
and imperial drive of the West. And so they’re implicated in
imperialism. Again, this is a pretty novel argument on the Left.
This
is probably cartoonish--as is probably the rest of the interview--but
if I was teaching a class, I'd use it as a text for setting out the
background arguments.
It’s
kind of hard to say. Chibber does not expend anything like the same
amount of time unpacking—much less justifying—his own Marxist normative
and epistemological presuppositions as he does in showing that Guha,
Chatterjee, and Chakrabarty are anti-Marxist. In broad outlines,
Chibber’s Marxism depends on “a defense of two universalisms,
one pertaining to capital and the other to labor.” More specifically,
Chibber’s Marxism is bound to the idea that ”the modern epoch is driven
by the twin forces of, on the one side, capital’s unrelenting drive to
expand, to conquer new markets, and to impose its domination on the
laboring classes [the first universalism], and, on the other side, the
unceasing struggle by these classes to defend themselves, their
well-being, against this onslaught [the second universalism] (208).” So
far, nothing objectionable: welcome to the Communist Manifesto.
The problem emerges, however, when Chibber attempts moving from the
universal to the particular, from the universality of capitalism’s
antagonism to the particular social zoning of its enactment. If
postcolonial theorists want to hold onto the particularity of the
particular, and engage the universal through it, Chibber uses these “two
universalisms” to denude the particular, to remove the peculiarity of
the particular in order to reduce it to the universal. Methodologically,
Chibber’s Marxism is pre-Hegelian. Indeed, his Marxism is the kind of
“monochrome formalism” derided by Hegel, an epistemology for which the
universal dominates the particular, one through which “the living
essence of the matter [is] stripped away or boxed up dead.”
And then later:
In
part, I think that “Marxism versus postcolonial theory” is simply
running interference for a set of disciplinary battles over
methodological and theoretical orientation. The antinomy that Chibber
continually establishes is one between a realist sociology (with an
investment in abstract structures that prime and cause human action) and
hermeneutically inclined fields of anthropology, history, and literary
studies. (Don’t mention literary studies to Chibber. He doesn’t seem to
like it very much.) In each of Chibber’s chapters, the explanatory
triumph of universalist accounts over particularist accounts can be read
as the triumph of a certain form of sociological reason over its
others.
More importantly, I think that Chibber is desperate for the resurgence of a particular kind of Marxism, one that was displaced not
by postcolonial theorists but by anticolonial Marxists like Fanon,
James, and so on. That’s why he can’t incorporate them into his account
of postcolonial theory: they are Marxists who mount critiques of
formalist universalisms by keeping close to the particular, by
maintaining the tension that obtains between economic structure and
lived phenomenology, between structuralist accounts of the world and
hermeneutic investigations into worlds. I have no idea why one would
wish to return to the days of CP sloganeering. (I can’t be the only one
who heard echoes of “black and white, unite and fight!” in his book.)
But the desire is there, and it shapes the way he constructs
postcolonial theory. Chibber’s fantasy that an anti-Marxist postcolonial
theory reigns hegemonic in the academy enables him to maintain the
fantasy that the once and future king of Marxism might some day be
restored to rule. But, in order to elaborate this fantasy, he needs to
transform a tension internal to postcolonial theory (between Marxist
accounts of structure and hermeneutic approaches to the particular—which
can still be, of course, Marxist) into a struggle exterior to it.
Everyone should all listen to this latest This American Life episode on what the reporter of the piece, Chana Joffe-Walt, calls the "disability industrial complex." The simple factoid with which it begins? The rise in the number of people all over America on disability. Joffe-Walt starts with this and starts to burrow in deeper. She finds that disability is a slippery concept: how does it get defined in practice? When she meets the doctor in Hale County, Alabama where 1 out of every 4 people is on disability (and he's responsible for many of these diagnoses), he tells her some of the criteria he uses. One among them is education level. Why, she wonders, is education level a criterion for disability? The answer is, of course, that he's trying to think about the kinds of jobs they will be working in, and if he estimates that they can't work those jobs successfully, well, then for all practical purposes, they are disabled. (See transcript.)
But Joffe-Walt doesn't stop there. She wants to explore this whole ecosystem of disability. So she looks at lawyers. What role have lawyers played in getting people on disability? (And lawyers here come off surprisingly well, I think--crass, yes, money-minded, definitely, but also fulfilling a deep need.) The answer: a lot. And what of the political economy? Aside from the problem of inequality--that the number of good jobs that don't require college degrees is steadily decreasing--she also points to federal and state regulations. States, she finds, have an active interest in moving off people from their welfare rolls onto the federally funded disability program. This work, naturally, is done by consultants who charge a fee for every successful transfer.
It's all deeply fascinating stuff that moves fluidly on a number of different levels. Sometimes Joffe-Walt is down on the ground, talking to people, seeking their opinions, wondering what they think. At other times, she is taking an eagle-eyed view of the scene, talking to economists, and regulators. [The web-site has a number of interesting graphs that are worth checking out.]
[Update: Okay, perhaps I should say this upfront. This is not a review of Morozov's book; rather it's a set of reflections on what we do as STS scholars based on two really outstandingreviews of Morozov's book. I've made some minor changes to reflect this.]
Reflecting on what Slee and Madrigal say about the book, I found myself thinking about STS scholarship in general. Morozov is particularly against Internet-centric solutionism which usually ends up using an approach that, as Slee rightly observes is often an application of "engineering,
neuroscience, [and] an understanding of incentives (in the narrowly
utilitarian sense)." But what ends up happening though in this criticism of solutionism is that, as both Slee and Madrigal point out, Morozov ends up using tropes that are usually used by conservatives--and worse, by reactionaries.
And then there is the idea of critique itself. It was illuminating to read that Morozov is actually inspired by what historians of science have done to their topic, that he wants to destroy
"the Internet" the same way STS scholars have destroyed "science" as a natural category. As Madrigal (using Paul Rabinow) rightly points out, this destruction of science is all but unnoticed outside the human sciences. Actual working scientists are hardly aware of it, and if they were, they would just shrug and carry on with their work. It isn't that science studies hasn't been revolutionary--but it has been revolutionary within the humanities and social sciences. It's almost as if freed from the cultural authority that science enjoyed, we, the human sciences--sociology, history, anthropology, literary studies--can now discover, analyze, and understand, on our own terms. But their influence on science itself and even more importantly, on public life, has been minimal.
And I'm afraid something similar might happen with Morozov.
Some people will read Morozov's book, it might even change some people's minds but Silicon Valley solutionism will
carry on as it did before.
The more I think about it, the more I realize
that the late Richard Rorty had it right. He consistently upheld the
poet, the novelist, and the politician as roles that are higher than a
philosopher–higher he said, because they are the ones who expand or
change ideas about humanness. The problem with Morozov (and with science studies) is that they are stuck at the level of philosophy or critique. Critique is good, but critique is not the same as doing things. Even Thomas Kuhn's The Structure of Scientific Revolutions, though dated as a science studies text, points out that a scientific paradigm is never discarded unless an option is available; old paradigms fall only because new ones appear and until a new one does appear, an old paradigm can carry on with infinite ad-hoc additions to itself. Morozov doesn't provide that paradigm; even if he does, he provides it in the spirit of critique and that may not work because the people he is arguing with are not in the business of critique. They
are in the business of doing things and while it may be a Silicon-Valley-corporate-profit-driven
thing, it still manages to shift people's ideas and experiences in the way that critique does not. STS scholarship has the same problem.
Can critique change things? Again, it's useful to go back to Rorty who points out that certainly something came of the attack on the canon in the 60s and 70s. Attuned to ideas about race, class and gender, literary theorists went back into the past and re-discovered books that had been neglected because they had not been written by dead white men. Today, these books, like Zora Neale Hurston's Their Eyes Were Watching God are no longer just texts in graduate seminars; they are now on school syllabi and increasingly read by school-children. In that sense, the critique of the canon has indeed borne fruit. Will critiques like Morozov's and other STS-type critiques yield something similar in the future? And what will that be? Only time will tell.
**Slee is good at describing the intellectual moves Morozov makes in his effort to take down Internet Triumphalism.
Morozov
undertakes two projects, one successfully and one less so. The first
is to provide a framework in which to think about the new inventions
that are being sold to us, and the patterns of thought behind them.
[...] Morozov identifies a twin-tracked ideology behind the
inventions and inventiveness of the digital world. One track is
“Internet-centrism” – the practice of “taking a model of how the
Internet works and applying it to other endeavours”. Writers have
imbued the Internet with “a way of working”; it has a “grain” to which
we must adapt; it has a culture, a “way it is meant to be used”, and
it comes with a mythology in which iTunes and Wikipedia become models
to think about the future of politics, and Zynga is a model for civic
engagement (15). The second track is “solutionism”: the recasting
of social situations as problems with definite solutions;
processes to be optimized (23).
Morozov
does a fine job of articulating Internet-centrism and
solutionism as two facets of a single Silicon Valley ideology,
[...] The common assumptions, shared biases, and individualistic
predilictions give a cohesiveness and homogeneity to the new ideas
and inventions, actively constructing and shaping the digital
environment from which they claim to draw their inspiration. The
insistence on “disrupting” our social and environmental lives; the
idea that the solutions inspired by and enabled by the Internet mark a
clean break from historical patterns, a never-before-seen
opportunity – these mean that the only lessons to learn from history
are those of previous technological disruptions. The view of
society as an institution-free network of autonomous individuals
practicing free exchange makes the social sciences, with the
exception of economics, irrelevant. What’s left is engineering,
neuroscience, an understanding of incentives (in the narrowly
utilitarian sense): just right for those whose intellectual
predispositions are to algorithms, design, and data structures.
Slee thinks that Morozov's analysis of the "solutionism" that he sees coming from the Valley is less satisfying,.
Morozov’s approach to unpicking the hidden assumptions of
solutionism, and the unpalatable consequences of its application,
is impressive but less successful. In order to avoid a blanket
technopessimism he makes two moves. The first is to adopt a broadly
social constructionist approach to the world of digital
technologies. The Internet does not shape us, it is shaped by the
society in which it is growing. He is with Raymond Williams, against
Marshall McLuhan. His stance here is blunt: he refuses to see “the
Internet” as an agent of change, for good or bad. “The Internet” is
not a cause; it does not explain things, it is the thing that needs to
be explained. Chapter 2 is titled The Internet Tells Us Nothing (Because It Doesn’t Actually Exist).
The second, more surprising move, is to adopt a critique that was
first described in a pejorative sense by Albert Hirschmann. “In his
influential book The Rhetoric of Reaction, Hirschmann argued
that all progressive reforms usually attract conservative
criticisms that build on one of the following three themes:
perversity (whereby the proposed intervention only worsens the
problem at hand), futility (whereby the intervention yields no
results whatsoever), and jeopardy (whereby the intervention
threatens to undermine some previous, hard-earned accomplishment)”
(6). Morozov does not see himself as a conservative, but instead
places himself in the tradition of other thinkers who have stood
against programs of organized efficiency; “Jane Jacobs... Michael Oakeshott [and] ... James Scott "
Madrigal
in his Atlantic review does a great close-reading of passages of the
book to show that Morozov arguments are often high-ideology. Which
means that he often counters the ideological set-pieces that Silicon
Valley types routinely use--visions of a future where a certain
technology seems to solve all our problems--with one of his own that
paints a completely opposite picture. And as Madrigal goes on to note,
he's really good at it except that at some point, he loses sight of real
people doing real things. This analysis is worth quoting because it is
an example of how one can write a fine, principled, rigorous piece of
criticism while still basically agreeing with the author on the
important things:
Morozov's book is an innovation- and product-centered account of the
deployment of technology. It focuses on marketing rhetoric, on the
stories Silicon Valley tells about itself. And it refutes these stories
with all the withering contempt that a brilliant person can muster over
the course of a few years of dedicated reading and writing. But it does
not devote any time to the stories the bulk of technology users tell
themselves. It relies on wild anecdotes from newspaper accounts as if
they were an adequate representation of the user base of these
technologies. In fact, the sample is obviously biased by reporters
writing about the people who sound the most out there.
"Celebrating quantification in the abstract, away from the context of
its use, is a pointless exercise," Morozov writes, and yet he ends up
doing excoriating quantification in the abstract. When he does apply his
thinking to the specific case of nutrition aids, it is with some
serious handwaving. Calories are not an adequate measure of overall
nutrition content, he writes, and thinking narrowly about nutritional
content is a boon for food companies, and maybe calories aren't even
really the problem. All fine and valid ideas, but knowing how many
calories you eat is a good starting point for good health, no? This has
been well-established by the medical and public-health literature. And,
in any case, tracking one's caloric intake is not a search for a "core
and stable self." And if your calorie counter doesn't share your data,
it could be a private practice. What if you write it in a book as has
been done for decades, or in the iPhone's notes, rather than an official
app? Is that OK? What about non-tweeting scales, are those anathema as
well? Should the ethical concerns Morozov presents really prevent actual
human beings from trying to understand the basics of their food intake?
Or take the use of pedometers, gussied up into packages like the Nike
Fuel Band, Jawbone Up, or Fitbit. There are literally hundreds of
thousands of pedometers and other activity monitors out there in
America, but Morozov does not try to investigate how such devices are
used. Are the people buying FitBits and Nike Fuel Bands trying to reveal
deep inner truths about themselves? Are they sharing every bit and bite
with friends? Or are they trying to lose a few pounds in private?
Look at what Amazon can tell you about the market for these devices: people who bought FitBits recently also bought diet books, scales, and multivitamins.
While Morozov locates self-tracking "against the modern narcissistic
quest for uniqueness and exceptionalism," it strikes me that I've yet to
meet someone wearing a fitness tracker who wasn't engaged in that least
unique American activity: weight management.
Coming into the 2011 US Open
with a track record of winning all but one of the Grand Slam matches that he
played that year, Novak Djokovic was facing Roger Federer in the semi-finals,
the very man who had beaten him in his only Grand Slam loss of 2011.And ominously, he lost the first two sets,
6-7(7), 4-6 before rallying to take the next two 6-3, 6-2.It was now the final set and Federer, having
just broken Djokovic's serve in the final set to go up 5-3, was serving at
40-15, with two match-points on his own serve.Upset at the crowd which was cheering Federer on wildly, Djokovic seemed
out of sorts, angry at himself, perhaps, for being in this position despite
playing a flawless third and fourth set.
[See the video from the first minute.] The interpretation of what
happened next remains a matter of dispute, hotly debated in tennis forums, YouTube
comments, and the blogosphere. Serving from the ad-court, Federer served out
wide to Djokovic's forehand.It was not
a bad serve, but Djokovic swung at it hard, and literally smashed it
cross-court for a clean winner.There
was shocked silence for a second before cheering erupted.Djokovic walked to the other side of the
court, raised his hands and looked at the crowd.Appreciate me, he seemed to be saying.The crowd obliged even as a bemused Federer
stood waiting to serve on the other side of the court.
It was still match-point.Federer threw a good serve straight at Djokovic's
body, and a rally ensued, which ended, heartbreakingly for Federer, with his
shot striking the net-chord and then dropping back on his own side.Deuce.Djokovic went on to win the game breaking Federer in the process.He then won the next three games as well,
winning the final set 7-5 to defeat Federer and reach the final.
What was going on in Djokovic's
mind when he hit that screaming forehand winner off Federer's serve?Was it hit in anger or was it a calculated
risk?How much did Djokovic's gamesmanship
– seeking the crowd’s approval – affect Federer on his next serve?Tennis fans and analysts continue to debate
this.My own thought, as I was watching
the match, was that Djokovic, who can often be peevish and irritable on court,
was angry with himself and swung at the ball, more out of pique than anything
else.But the shot went in, and Djokovic used it to
rally the crowd to his own side.On the
other side of the net, Federer suffered a dent in his own confidence, and this
allowed Djokovic (who is undoubtedly the best and fittest player on the tour
today) to put himself back into the match.
Both players themselves offered
contradictoryinterpretations of the return.“It’s a risk you have to take,” Djokovic told
Mary- Joe Fernandez in the on-court interview. “It’s in, you have a second
chance. If it’s out, you are gone. So it’s a little bit of gambling.” Federer,
on the other hand, was having none of it.“Confidence, are you kidding me?” he scoffed in his post-match interview.
“I never played that way. For me, this is very hard to understand how you can
play a shot like that on match point.” Djokovic acknowledged that he needed to
"get some energy from the crowd."“Look, I was a little bit lucky in that moment because he was playing
tremendously well with the inside-out forehand throughout the whole match. This
is what happens at this level. You know, a couple of points can really decide
the winner.”
The Federer-Djokovic first match
point is often what both tennis players and tennis analysts refer to as a
"key point."These key points,
as Djokovic points out in his post-match interview, are often the ones that
"decide the winner."In the
rest of this essay, I hope to show that this idea of "key points" as
relevant to the outcome of a tennis match is possibly of interest to historians
of technology.
What is a "key
point"?A key point is a point
(possibly among a set of points) which can be seen to have determined the
outcome of the match, as seen by the players or the analysts (or both).Players often sense that a point will be key
during the match itself and go all out in their effort to win it, perhaps by
hitting extra hard, taking a risk, or by running down a ball they would rather
have left alone to conserve their energy.Analysts too, as interested observers of a match, can sense whether a
point will be key to the outcome, although they have no agency when compared to
the players themselves.
But while an upcoming key point
can be sensed by the players and the spectators, key points can be definitively identified only after the
match is over.In other words, the identification of key points is
contingent on the outcome.In the
Federer-Djokovic match we saw above, the courageous (or reckless) Djokovic
return at 15-40 is a key point only because Djokovic won the next four games to
win the match.If Djokovic had lost the
next match-point, this point would no longer be talked about as a key point but
as a fluke.Instead the game in which
Federer broke Djokovic at 4-3 in the final set would have turned out to be the key
to the outcome of the match.To restate
this point, the key to winning a match is
to win the key points, but the points that are key to winning a match can only
be determined after the match is won (or lost).
It is worth discussing an
alternative explanation of match outcomes: that the more talented, or better,
player wins the match.I quoted a part
of Djokovic's post-match interview above.On actually watching the interview, it
turned out that the quote left out a crucial part.Djokovic actually said: "This is what
happens at this level – when two top
players meet. You know, a couple of
points can really decide the winner."[Italics mine.]The implication
here is that it is only when players are evenly matched in terms of
"talent" that the outcome hinges on a few key points.When players have wildly different talents,
the outcome hinges on, say, the "talent" they possess (which will not
be the same) and not on the key points.
How might the key point analytic
relate to what historians – especially historians of technology – do to understand
the past?As I see it, the topic of
historians of technology is technological change.Our aim is to understand the past and to
answer the question: why do certain things change while others remain the
same?One might see this question as
similar to those that tennis analysts pose to themselves: why did player X win
against player Y?Why has player X
consistently beaten player Y in their previous 5 matches?
Somewhat analogous to the two
theories to explain the outcome of a tennis match – the "key point"
theory vs. the "more talent" theory – one could oversimplify theories
about technological change into two kinds.One theory might be that technological change happens because a certain
technology is better at producing certain desirable outcomes (more profits,
more efficiency, better living conditions, progress and so on).This theory would go under the name of
"technological determinism" and would be similar to the "more
talent" theory of tennis match outcomes.The other theory would postulate that technological change happens
because certain groups of people – I will call them “interest groups” – are able
to defeat, or persuade, their opponents through the channels available to them
at certain crucial junctures.This
theory would be similar to the "key point" theory.
How would the "key
point" theory of technological change help avoid the pitfalls of
technological determinism?As I see it,
the main dilemma of any social science is the issue of predictability.Unlike the natural sciences which can predict
the future behavior of their "actors" (the trajectory of a missile,
the motion of the planets, the quantum states of atoms), the social sciences
cannot (and with good reason) predict the changes of the future.They cannot because assemblages of human
actors are unpredictable.They have
agency.Harry Collins has shown how even
the behavior of natural scientists – who produce natural science, the most “rational”
of all the disciplines – is still unpredictable, and is better understood as
the application of certain tacit skills, than as the brute application of some
rule-bound "scientific method."
The social sciences thus face
two different questions.On the one
hand, social scientists need to account for the sense of contingency and
unpredictability that their actors often feel while thinking about the
future.They also need to account for
why their actors feel that certain actions are the key to changing the
future.On the other hand, they (and
here I speak of historians in particular) need to account for why the events of
the past seem so inevitable, the way they seem to lead to the present so unproblematically.Clearly actors in the past who experienced
these "same" events did not know how things would turn out.How can historians account for the inevitability
of the past for us and its contingency for the actors experiencing the past?
A theory of technological change
that looked at "key points" as determining certain (technological/social)
outcomes could be one solution to this.Key points in history would need to have the following
characteristics.First, historical
actors themselves should have some dim awareness that something important was
happening and that different visions of the future are at stake.Second, the outcomes of these key points
should result in the victory of one set of interest group over others, thereby
setting in motion a certain kind of future.Third, these key points can only be determined retrospectively once the
outcome is known (as historians always do).Fourth, key points preserve the agency of historical actors.Finally, key points in history can change as
newer and newer outcomes arise.For example,
historians now agree that Barry Goldwater's defeat by Lyndon Johnson in the
1964 presidential election, and the subsequent rise of grass-rootsconservatism, is a key to understanding American politics today, even if no one
seemed to be paying attention to it back then.It was a key point for certain actors who
were mobilizing to achieve their vision of the future, even if their
ideological opponents were largely unaware of them.
Tennis key points are heuristics, of course. And they have their limitations, even in sports. For instance, it is much more difficult to locate key points in soccer, for instance, where the notion of discrete points does not exist. Soccer is, for lack of a better word, continuous, while tennis is more discrete, with precisely demarcated "points." And even in tennis, determining key points is difficult. Because one point seemingly leads to the next: if the Djokovic screaming forehand winner was a key point, what about the points before that one? What about those that decided the first four sets? Would it have mattered if Djokovic had won the first set--which he lost narrowly in a tie-breaker (9-7)?
But I do think that determining the key points of a tennis match is like doing history. The boiling down of a match outcome to a series of key points shows us how contingent events are. And at the end of the day, match outcomes are predictable to some extent: a match between Federer and David Ferrer is far likely to lead to a Federer victory (although not always). Those are the kinds of explanations/narratives of technological change that the key point theory would ask us to look for: highly contingent, built out of specific events, but with specific patterns that are by no means law-like.
