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Culture Digitally // Examining Contemporary Cultural Production

  • With the generous support of the National Science Foundation we have developed Culture Digitally. The blog is meant to be a gathering point for scholars and others who study cultural production and information technologies. Welcome and please join our conversation.

     

    • Matrix algebra: how to be human in a digital economy Apr 1, 2014


      Ray and Charles Working on a Conceptual Model for the Exhibition Mathematica, 1960, photograph. Prints & Photographs Division, Library of Congress (A-22a). Click here to see original image.

       

      “Certainly the cost of living has increased, but the cost of everything else has likewise increased,”[1] H.G. Burt, the President of the Union Pacific Railroad, asserted to railroad company machinists and boilermakers.  For Burt, the “cost of everything else” included the cost of labor. His remedy: place “each workman on his [own] merit.”  In 1902, “workman merit” to a tycoon like H.G. Burt squarely meant equating the value of labor, or the worth of a person, to the amount of output each individual produced.  Union Pacific Railroad eventually made use of this logic by replacing the hourly wages of workers with a piece rate system.  Employers switched to piecework systems around the turn of the 19th century largely to reduce labor costs by weeding out lower skilled workers, and cutting the wages of workers unable to keep apace with the “speeding up” of factory production.

      Employers historically leveraged piecework as a managerial tool, reconfiguring labor markets to the employers’ advantage by allowing production rates, rather than time on the job, to measure productivity.  Whatever a person produced that was not quantifiable as a commodity, in other words, did not constitute work.  We’ve seen other examples of discounted labor in spaces outside the factory.  Feminist economists fight to this day, for example, for the work of caregivers and housewives, largely ignored by mainstream economic theory, to gain recognition as “real” forms of labor.  Real benefits and income are lost to those whose work goes unaccounted.

      As the historical record shows, workers do not typically accept arbitrary changes to their terms of employment handed down by management.  In fact, the Union Pacific Railroad machinists protested Burt’s decision to set their wages through a piecework system.  H.G. Burt met their resistance with this question: is it “right for any man to ask for more money than he is actually worth or can earn?”

      But what is a person truly worth in terms of earning power?  And what societal, cultural, and economic factors limit a person from earning more?

      In 2014, the question of a person’s worth in relation to their work, or the value of labor itself, is no less prescient.  The rhetoric surrounding workers’ rights compared to those of business differs little whether one browses the archives of a twentieth century newspaper or scrolls Facebook posts.  Ironically enough though, in the age of social media and citizen reporting, the utter lack of visibility and adequate representation of today’s workers stands in stark contrast to the piece rate workers of H.G. Burt’s day.  Few soundbites or talking points, let alone byline articles, focus on the invisible labor foundational to today’s information economies.  Nowhere is this more clearly illustrated than with crowdwork.

      Legal scholar Alek L. Felstiner defines crowdworking as, “the process of taking tasks that would normally be delegated to an employee and distributing them to a large pool of online workers, the ‘crowd’” (2011).  Hundreds of thousands of people regularly do piecework tasks online for commercial, crowdsourcing sites like Amazon.com’s Mechanical Turk (“AMT”).

      Over the last year, we’ve worked with Dr. Siddharth Suri and an international team of researchers, to uncover the invisible forms of labor online, and people who rely upon digital piecework for a significant portion of their income.  Crowdwork is, arguably, the most economically valuable, yet invisible, form of labor that the Internet has ever produced.  Take Google’s search engine for instance.  Each time you search for an image online (to create the next most hilarious meme, or find a infograph for a conference presentation) you’re benefitting from the labor of thousands of crowdworkers who have identified or ranked the image your search populates. While this service may be valuable to you, the workers doing it, only receive a few cents for their contributions to your meme or slideshow presentation.  Additionally, a typical crowdworker living in the United States makes, on average, 2 to 3 dollars an hour.  We need to ask ourselves: what is fair compensation for the value that workers bring to our lives?  How would you feel if tomorrow, all your favorite, seemingly free, online services that depend on these digital pieceworkers, disappeared?

      Last fall, we spent four months in South India talking with crowdworkers and learning about their motivations for doing this type of work.  In the process we met people with far ranging life experiences, but a common story to tell – perhaps familiar to all of us who’ve earned a wage for our keep: work is not all we are, but most of what we do is work.  And increasingly, the capacity to maintain a living above the poverty line is elusive, and complicated by what “being poor” means in a global economy. Our hopes for finding more satisfying work, a life valued for what it is rather than what it is not — is no less, even as we confront the realities of today.

      Moshe Marvit spoke to the complexities of crowdwork as a form of viable employment in a compelling account of U.S. workers’ experience with Amazon Mechanical Turk. He describes this popular crowdsourcing platform as “one of the most exploited workforces no one has ever seen.” Marvit emphasizes how crowdwork remains a thing universally unacknowledged, in that more and more tasks, from researchers’ web-based surveys and to Twitter’s real-time deciphering of trending topics, depend on crowdwork.  However, most people still don’t know that behind their screen is an army of click workers.  Anyone, who has ever browsed an online catalogue or searched the web for a restaurant’s physical address, has benefited from a person completing small, crowdworked task online.  Pointedly, our web experience is better because of the thousands of unknown workers who labor to optimize the online spaces we employ.

      As Marvit points out, and our research also notes, people only earn pennies at a time for doing the small crowd tasks not yet fully automatable by computer algorithms. These crowd tasks, however, add up to global systems whose monetary worth sometimes trumps that of small nations.  Yet, when we ask our peers and colleagues, “do you know who the thousands of low income workers are behind your web browser?”  We receive mystified stares, and many reply “I don’t know.”

      The hundreds of thousands of people who regularly work in your web browser are not the youth of Silicon Valley’s tech industry.  They likely cannot afford Google glass, or ride to work in corporate buses.  Some are college educated, but, like people today – they are stuck in careers that undervalue their real worth, in addition to discounting the investments they’ve already made in their education, skills, and the unique set of values they’ve gained from their own life experiences.

      Yet, the more our research team learns about crowdworkers’ lives, the more we realized how little we know about the economic value of crowdwork and the makeup of the crowdworking labor force. And as Marvit notes, we still don’t have a good grasp of what someone is doing, legally speaking, when they do crowdwork. Should we categorize crowdwork as freelance work? Contract labor? Temporary or part-time work?

      In the absence of answers to these questions, some have called for policy solutions to mitigate the noted and sometimes glaring inequities in power distributed between those posting tasks (or, jobs) to crowdwork platforms, and those seeking to do crowdwork online.  But, we argue, good labor policy that makes sense of crowdwork, from a legal or technical point of view, can’t be adequately drafted until we understand what people expect and experience doing task-based work online. Who does crowdwork? Where, how, and why do they do it? And how does crowdworking fit into the rest of their lives, not to mention our global workflows? When we can answer these questions, we’ll be ready to talk about how to define crowdwork in more meaningful ways. Until then, we resist dubbing crowdwork “exploitative” or “ideal,” because doing so is meaningless to the millions of people who crowdwork, and ignores the builders and programmers out there trying to improve these technologies.

      We are all implicated in the environments we rely on and utilize in our daily lives, including the Internet.  Those who mindlessly request and outsource tasks to the crowd without regard to crowdworkers’ rights, are perhaps, no more at fault than the rest of us who expect instant, high quality web services every time we search or do other activities online.  An important lesson from Union Pacific Railroad still holds true: workers are not expendable.

      This is cross-posted from the Social Media Collective Blog at Microsoft Research, New England and the Center for Popular Economics at the University of Massachusetts, Amherst.


      [1]Omaha daily bee. (Omaha [Neb.]), 01 July 1902. Chronicling America: Historic American Newspapers. Lib. of Congress. <http://chroniclingamerica.loc.gov/lccn/sn99021999/1902-07-01/ed-1/seq-1/>

      -Contributed by ,  University of Massachusetts, Amherst; and ,  Microsoft Research New England / Associate Professor of Communication and Culture with affiliations in American Studies, Anthropology, and the Gender Studies Department at Indiana University-

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      A “pay it back tax” on data brokers: a modest (and also politically untenable and impossibly naïve) policy proposal Mar 18, 2014

      I’ve just returned from the “Social, Cultural, and Ethical Dimensions of Big Data” event, held by the Data & Society Initiative (led by danah boyd), and spurred by the efforts of the White House Office of Technology and Policy to develop a comprehensive report on issues of privacy, discrimination, and rights around big data. And my head is buzzing. (Oh boy. Here he goes.) There must be something about ma and workshops aimed at policy issues. Even though this event was designed to be wide-ranging and academic, I always get this sense of urgency or pressure that we should be working towards concrete policy recommendations. It’s something I rarely do in my scholarly work (to its detriment, I’d say, wouldn’t you?) But I don’t tend to come up with reasonable, incremental, or politically viable policy recommendations anyway. I get frustrated that the range of possible interventions feels so narrow, so many players that must be untouched, so many underlying presumptions left unchallenged. I don’t want to suggest some progressive but narrow intervention, and in the process confirm and reify the way things are – though believe me, I admire the people who can do this. I long for there to be a robust vocabulary for saying what we want as a society and what we’re willing to change, reject, regulate, or transform to get it. (But at some point, if it’s too pie in the sky, it ceases being a policy recommendation, doesn’t it?) And this is especially true when it comes to daring to restrain commercial actors who are doing something that can be seen as publicly detrimental, but somehow have this presumed right to engage in this activity because they have the right to profit. I want to be able to say, in some instances, “sorry, no, this simply isn’t a thing you get to profit on.”

      All that said, I’m going to propose a policy recommendation. (It’s going to be a politically unreasonable one, you watch.)

      I find myself concerned about this hazy category of stakeholders that, at our event, were generally called “data brokers.” There are probably different kinds of data brokers that we might think about: companies that buy up and combine data about consumers; companies that scrape public data from wherever it is available and create troves of consumer profiles. I’m particularly troubled by the kind of companies that Kate Crawford discussed in her excellent editorial for Scientific American a few weeks ago — like Turnstyle, a company that has set up dummy wifi transponders in major cities to pick up all those little pings your smartphone gives off when its looking for networks. Turnstyle coordinates those pings into a profile of how you navigated the city (i.e. you and your phone walked down Broadway, spent twenty minutes in the bakery, then drove to the south side), then aggregates those navigation profiles into data about consumers and their movements through the city and sells them to marketers. (OK, that is particularly infuriating.) What defines this category for me is that data brokers do not gather data as part of a direct service they provide to those individuals. Instead they gather at a point once removed from the data subjects: such as purchasing the data gathered by others, scraping our public utterances or traces, or tracking the evidence of our activity we give off. I don’t know that I can be much more specific than that, or that I’ve captured all the flavors, in part because I’ve only begun to think about them (oh good, then this is certain to be a well-informed suggestion!) and because they are a shadowy part of the data industry, relatively far with consumers, with little need to advertise or maintain a particularly public profile.

      I think these stakeholders are in a special category, in terms of policy, for a number of reasons. First, they are important to questions of privacy and discrimination in data, as they help to move data beyond the settings in which we authorized its collection and use. Second, they are outside of traditional regulations that are framed around specific industries and their data use (like HIPAA provisions that regulate hospitals and medical record keepers, but not data brokers who might nevertheless traffic in health data). Third, they’re a newly emergent part of the data ecosystem, so they have not been thought about in the development of older legislation. But most importantly, they are a business that offers no social value to the individual or society whose data is being gathered. (Uh oh.) In all of the more traditional instances in which data is collected about individuals, there is some social benefit or service presumed to be offered in exchange. The government conducts a census, but we authorized that, because it is essential to the provision of government services: proportional representation of elected officials, fair imposition of taxation, etc. Verizon collects data on us, but they do so as a fundamental element of the provision of telephone service. Facebook collect all of our traces, and while that data is immensely valuable in its own right and to advertisers it is also an important component in providing their social media platform. I am by no means saying that there are no possible harms in such data arrangements (I should hope not) but at the very least, the collection of data comes with the provision of service, and there is a relationship (citizen, customer) that provides a legally structured and sanctioned space for challenging the use and misuse of that data — class action lawsuit, regulatory oversight, protest, or just switching to another phone company. (Have you tried switching phone companies lately?) Some services that collect data have even voluntarily sought to do additional, socially progressive things with that data: Google looking for signs of flu outbreaks, Facebook partnering with researchers looking to encourage voting behavior, even OK Cupid giving us curious insights about the aggregate dating habits of their customers. (You just love infographics, don’t you.) But the third party data broker who buys data from an e-commerce site I frequent, or scrapes my publicly available hospital discharge record, or grabs up the pings my phone emits as I walk through town, they are building commercial value on my data, but offer me no value to me, my community, or society in exchange.

      So what I propose is a “pay it back tax” on data brokers. (Huh?! Does such a thing exist, anywhere?) If a company collects, aggregates, or scrapes data on people, and does so not as part of a service back to those people (but is that distinction even a tenable one? who would decide and patrol which companies are subject to this requirement?), then they must grant access to their data and access 10% of their revenue to non-profit, socially progressive uses of that data. This could mean they could partner with a non-profit, provide them funds and access to data, to conduct research. Or, they could make the data and dollars available as a research fund that non-profits and researchers could apply for. Or, as a nuclear option, they could avoid the financial requirement by providing an open API to their data. (I thought your concern about these brokers is that they aggravate the privacy problems of big data, but you’re making them spread that collected data further?) I think there could be valuable partnerships: Turnstyle’s data might be particularly useful for community organizations concerned about neighborhood flow or access for the disabled; health data could be used by researchers or activists concerned with discrimination in health insurance. There would need to be parameters for how that data was used and protected by the non-profits who received it, and perhaps an open access requirement for any published research or reports.

      This may seem extreme. (I should say so. Does this mean any commercial entity in any industry that doesn’t provide a service to customers should get a similar tax?) Or, from another vantage point, it could be seen as quite reasonable: companies that collect data on their own have to spend an overwhelming amount of their revenue providing whatever service they do that justifies this data collection: governments that collect data on us are in our service, and make no profit. This is merely 10% and sharing their valuable resource. (No, it still seems extreme.) And, if I were aiming more squarely at the concerns about privacy, I’d be tempted to say that data aggregation and scraping could simply be outlawed. (Somebody stop him!) In my mind, it at the very least levels back the idea that collecting data on individuals and using that as a primary resource upon which to make profit must, on balance, provide some service in return, be it customer service, social service, or public benefit.

      This is cross-posted from the Social Media Collective blog at Microsoft Research, New England.

      -Contributed by ,  Cornell University Department of Communication-

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      Twitch Plays Pokemon: Questioning Intellectual Property, Creativity and the Public Performance of Play Mar 17, 2014

      As a bookend to the podcast that T.L. Taylor and Greg Lastowka were kind enough to participate in, I’m posting this bit of thinking on the legal issues that continue to plague those of us thinking about cultural production in the digital age.   It’s also a bit of an emerging dialogue.   See Greg Lastowka’s thoughts below.

      Hector Postigo: Recently Greg Lastowka linked the article, “This Guy Makes Millions Playing Video Games,” from the Atlantic Monthly via his FB page.  Because I’m trying to finish writing my next book on YouTube and Video Gameplay, I was happy to see that recording gameplay and posting it on YouTube as an entrepreneurial venture for video gamers was getting some media attention.  Greg’s post started a related discussion about how digital copyright might map onto the practices in digital culture that converge a number of technologies, media and laws.  It made me think of Twitch Plays Pokemon.

       

      Screen Shot 2014-03-17 at 1.11.56 PM

       

      I found this case thanks to one of my students in my video game studies class. When I was at Virginia Tech for the Intellectual Property in the Digital Age Forum, where we discussed digital copyright and its impact on creativity, we talked a little bit about Twitch Plays Pokemon over dinner.  Some of us couldn’t decide where copyright infringement liability may lie in the case of Twitch, or even if there was an infringement claim to be made.   In Twitch Plays Pokemon, a user has modified the chat interface to work with his inputs of his Pokemon game.  Viewers on his Twitch channel can control the gameplay via chat.  What has emerged is a massively played, live webcast of, at times, 50 thousand or so viewers playing the game through chat commands.

      I think the questions in the Pokemon example that get to the copyright problem are:

      1.  Did that streamer on twitch circumvent access or copy protection encryption algorithms to afford the chat mediated play?  2. Does a modification to browser chat and input/output interfaces on the game or game console or PC constitute circumvention? 3. Is the stream of an unauthorized public performance an infringing broadcast? 4.  Could a reasonable argument be made that 50 thousand people playing the game is transformative, making public performance and derivative works claims weak?

      The convergence question is also at play (pun intended) in this case.  A number of media and technologies are orbiting the practice of broadcasting gameplay.  The game consoles, the web, and the games themselves.  A host of techno-practices and life worlds converge through the synergies afforded by a chat interface hack that lets thousands play a game they don’t necessarily own: web surfing, video gameplay, online chat, broadcast and digital media entrepreneurship.   The reality that all these converge on proprietary platforms leave us with the political economy questions that have been orbiting our research for sometime.  How is value generated, captured and extracted?  Where does hobby end and work begin?  How should the value and profit generated across media platforms and genres be properly distributed so that incentives and creativity continue to be fostered?  Questions that I’m still sorting out in my writing but thankful to have our community to share with. Thanks go to Elizabeth Stark, Saul Halfon, Greg Lastoka (linked above), Alex Leavitt, TL Taylor (also linked above), Bruce Boyden, Ren Reynolds and Sal Humphreys for having these discussions over social media or over a meal.  Nothing beats a good dose of collaborative thinking about collaborative play.

      Greg Lastowka: In response to #1 & #2, I’m figuring there *had* to be some TPM on there sufficient to create a 1201 violation, right? (Haven’t looked into the architecture.)
      On #3 & #4, I was thinking about the fair use question — my first instinct was that Twitch isn’t radically different than Taito but, after a second of thinking, I realized it probably is a very different question. It’s all about how the use is carried out and toward what end. Twitch is a strange form of use. By analogy, what if Twitch sang the songs from Disney’s The Little Mermaid or performed Death of a Salesman? That’s not the same as a “standard” performance of either work — so I think the case for fair use is stronger when the Twitchers all play.

      The derivative work claim seems pretty strong in the absence of fair use.

      Other Qs: potentially severable copyright in the Pokemon characters? TM
      concerns about them too? and what about copies of the software code to
      create the thing in the first place? There is certainly a lot going on here.

      -Contributed by ,  Temple Dept. of Department of Media Studies & Production-

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      Podcast: TL Taylor and Greg Lastowka on Video Games, User Generated Content and Regulatory Regimes Feb 24, 2014

      TLbwsmall

      gregIn this episode of Culture Digitally the Podcast, MIT’s TL Taylor and Rutgers Law School’a Greg Lastowka share their insights into emergent video game culture practices that may run aground on copyright law.  Greg talks about his recent NSF  funded work surveying user generated content (UGC) in video games and TL discusses emergent video gameplay live-streaming practices on Twitch TV.   Their conversation took place at the School of Media and Communication at Temple University with the school’s and Culture Digitally’s support.

      Editor’s Note:  This Episode of Culture Digitally the Podcast was recorded in the Spring of 2013.  Since then, some of the details on the data presented in the conversation may have changed given that some platforms discussed adjust terms of service agreements and content policies often.

      Greg Lastowka’s Book:  Virtual Justice

      TL’s Book : Raising the Stakes

       

      -Contributed by ,  Temple Dept. of Department of Media Studies & Production-

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      Announcement: Hector Postigo at Virginia Tech – Plenary Panel on Intellectual Property and the Digital Age Feb 24, 2014

      Screen Shot 2014-02-24 at 11.23.29 AMThis week Culture Digitally’s Hector Postigo will speak as part of the Plenary Panel for the Choices and Challenges Forum on Intellectual Property in the Digital Age hosted at Virginia Tech on February 27th.  He’ll discuss copyright law, cultural production and digital technology with Karin Temple Claggett, Associate Register of Copyrights and Director of Policy and International Affairs; Paul Brigner, Regional Director of the North American Bureau at the Internet Society; Adrian Johns, Allan Grant Maclear Professor of History at the University of Chicago; and Elizabeth Stark, Entrepreneur-in-Residence at StartX at Stanford University.

      -Contributed by ,  With the generous support from the National Science Foundation-

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