Archive for the ‘technology’ Category
In my course in introductory sociology, I have a module on health. One lecture describes the leading causes death, across age groups and across time periods. In modern times, one of the leading causes of death is “unintentional injury.” What does that mean? Roughly speaking, the three major categories of unintentional injury death are, in order, falling, auto accidents, and accidental poisoning.
The interesting thing is that these are all types of death that relate to economic development: cars, chemical, tall buildings, stairs and so forth. The other side is that economic development can also help us out. For example, in about one generation, driverless cars will be widespread. The implication is that drunk driving will be eliminated over night and accidents relating to drifting driver attention will disappear overnight. Truck accidents should also disappear. My hypothesis is that computer driven cars will probably be better than most people when they drive in the rain or snow. They might even automatically shut down if conditions are bad enough.
Bottom line: Economic development has unintended consequences. Sometimes they are bad, such as auto related deaths. But development can introduce solutions. The driverless car will be one such example.
Measuring such things is tough, but newly published research reports telling indicators can be found in bursts of 140 characters or less. Examining data on a county-by-county basis, it finds a strong connection between two seemingly disparate factors: deaths caused by the narrowing and hardening of coronary arteries and the language residents use on their Twitter accounts
“Given that the typical Twitter user is younger (median age 31) than the typical person at risk for atherosclerotic heart disease, it is not obvious why Twitter language should track heart disease mortality,” writes a research team led by Johannes Eichstaedt and Hansen Andrew Schwartz of the University of Pennsylvania. “The people tweeting are not the people dying. However, the tweets of younger adults may disclose characteristics of their community, reflecting a shared economic, physical, and psychological environment.”
Not a puzzle to me. I have argued that social media content is often an indicator – a smoke signal – of other trends. Thus, if people are stressed due to environmental conditions (the economy, unemployment), they will have heart attacks and write angry text. The only question is when the correlation holds. For more discussion of the more tweets/more votes/more anything phenomena, click here.
Within informatics, there is a healthy body of research showing how social media data can be used for forecasting future consumption. The latest is from a study by Nielsen, which shows some preliminary evidence that Twitter activity forecasts television program popularity. In their model, adding Twitter data increases the explained variance in how well a TV show will in addition to data on promotions and network type. Here’s the summary from Adweek.
My co-bloggers are on a roll. Zynep Tufekci and Brayden King have an op-ed in the New York Times on the topic of privacy and data:
UBER, the popular car-service app that allows you to hail a cab from your smartphone, shows your assigned car as a moving dot on a map as it makes its way toward you. It’s reassuring, especially as you wait on a rainy street corner.
Less reassuring, though, was the apparent threat from a senior vice president of Uber to spend “a million dollars” looking into the personal lives of journalists who wrote critically about Uber. The problem wasn’t just that a representative of a powerful corporation was contemplating opposition research on reporters; the problem was that Uber already had sensitive data on journalists who used it for rides.
Buzzfeed reported that one of Uber’s executives had already looked up without permission rides taken by one of its own journalists. Andaccording to The Washington Post, the company was so lax about such sensitive data that it even allowed a job applicant to view people’s rides, including those of a family member of a prominent politician. (The app is popular with members of Congress, among others.)
This is not a post about Ello. Because Ello is so last Friday. But the rapid rise of and backlash against upstart social media network Ello (if you haven’t been paying attention, see here, here, here) reminded me of something I was wondering a while back.
Lots of people are dissatisfied with Facebook — ad-heavy, curated in a way the user has little control over, privacy-poor. And it looks like Twitter, which really needs bring in more revenue, is taking steps to move in the same direction: algorithmic display of tweets, with the ultimate goal of making users more valuable to advertisers.
The question is, what’s the alternative? There have been a lot of social network flavors of the month, built on a variety of business models. Some of them, like Google Plus, are owned by already-large companies that would be subject to similar business pressures as Facebook and Twitter. Others, like Diaspora (remember Diaspora?), were startups with an anti-Facebook mission (privacy, decentralization), but collapsed under the weight of their own hype.
I can’t imagine that a public utility model would work for a social network — I just don’t see “government-owned” and “fast-moving technological change” going together successfully. But I keep wondering why a Wikipedia model couldn’t work. Make it a 501(c)3. Attract some foundation funding — it’s a pro-democracy project. Solicit gifts from pro-privacy people in the tech industry — there are lots of those. Then once it’s off the ground, ask users for donations.
Sure, there is the huge, huge hurdle of getting enough of a network base to attract new users. But it seems like the costs should not be insane. If it only takes 200 employees to run Wikipedia, as large as it is, how many would it take to get a big social network off the ground? Facebook employs 7000, but a lot of them have to be in the business of figuring out how to sell Facebook.
Maybe there have been (failed) efforts like this and I just haven’t noticed. Or maybe the getting-the-user-base issue is really insurmountable. But it seems like if a real Facebook alternative is to emerge, it can’t just be from a corporate competitor (e.g. Google), and the startup/VC model (e.g. Ello) is going to be susceptible to all the same problems as it grows. Why not a different model?
Loyal orgtheorista and sociologist Amy Binder has forwarded me this course syllabus for a course at UC San Diego. It is called Soc 211 Computational Methods in Social Science and was taught by Edward Hunter and Akos Rona-Tas. The authors are working on a textbook, the course was made open to a wide range of students, a and it was supported by the Dean at UCSD. I heard people had a nerdy good time. Click here to read the soc211_syllabus.
I’m in the Poconos this week with old college friends and only intermittently paying attention to the larger world. And I’m hesitant to opine about the latest in the world of online experimentation (see here, here, or here) because honestly, it’s not my issue. I don’t study social media. I don’t have deep answers to questions about the ethics of algorithms, or how we should live with, limit, or reshape digital practices. And plenty of virtual ink has already been spilled by people more knowledgeable about the details of these particular cases.
But I do want to make the case that it’s important to have this conversation at this particular moment. Here is why:
If there’s one thing the history of technology teaches us, it’s that technology is path-dependent, and as a particular technology becomes dominant, the social and material world develop along with it in ways that have a lasting impact.
The QWERTY story, in which an inefficient keyboard layout was created to slow down the users of jam-prone typewriters but long outlasted those machines, may be apocryphal. Perhaps a better example is streetcars.
Historian Kenneth Jackson, in the classic Crabgrass Frontier, showed how U.S. cities were first reshaped by streetcars. Streetcars made it possible to commute some distance from home to work, and helped give dense, well-bounded cities a hub-and-spokes shape, with the spokes made up of rail lines. This was made possible by new technology.
Early in the 20th century, another new technology became widely available: the automobile. The car made suburbanization, in the American sense involving sprawl and highways and a turn away from center cities, possible.
But the car alone was not enough to suburbanize the United States. Jackson’s real contribution was to show how technological developments intersected with 1) cultural responses to the crowded, dirty realities of urban life, and 2) government policies that encouraged both white homeownership and white flight, to create the diffuse, car-dependent American suburbs we know and love. The two evolve together: technological possibilities and social decisions about how to use the technologies. As they lock in, both become harder to change — until the next disruptive technology (((ducking))) comes along.
So what does all this have to do with OKCupid?
The lesson here is that technologies and their uses can evolve in multiple ways. European cities developed very differently from American cities, even though both had access to the same transportation technologies. But there are particular moments, periods of transition, when we start to lock in a set of institutions — normative, legal, organizational — around a developing new technology.
We’re never going to be able to predict all the effects that a particular social decision will have on how we use some technology. Government support of racist red-lining practices is one reason for the white flight that encouraged suburbanization. But even if the 1930s U.S. mortgage policy hadn’t been racist, other aspects of it — for example, making the globally uncommon fixed-rate mortgage the U.S. norm — still would have promoted decentralization and encouraged the car-based suburbs. Some of that was probably unforeseeable.*
But some of it wasn’t. And I can’t help but think that more loud and timely conversation about the decisions and nondecisions the U.S. was making in the early decades of the 20th century might have led the country down a less car-dependent path. Once the decisions are made, though, they become very difficult to change.
Right now, it is 1910. We have the technology to know more about individuals than it has ever been possible to know, and maybe to change their behavior. We don’t know how we’re going to govern that technology. We don’t really know what its effects will be. But this is the time to talk about the possibilities, loudly and repeatedly if necessary. Maybe the effects on online experimentation will turn out to be to be harmless. Maybe just trusting that Facebook and OKCupid aren’t setting us on the wrong path will work out. But I’d hate to think that we unintentionally create a new set of freedom-restricting, inequality-reproducing institutions that look pretty lousy in a few decades just because we didn’t talk enough about what might — or might not — be at stake.
* There is a story that GM drove the streetcars out of business by buying up streetcar companies and then dismantling the streetcars. There are a number of accounts purporting to debunk this story. This version, which splits the difference (GM tried, but it wasn’t a conspiracy, and it was only one of several causes) seems knowledgeable, but I’d love a pointer to an authoritative source on GM’s role.