The Pacific Standard magazine has been running a series where academics, business leaders, technologists and labor leaders have contributed to the discussion on the most consequential changes in labor and the future of work. We invite you to read the contributions from members of our SMC family.
“Caring for the Crowdworker going at it alone” –>Mary L. Gray, one of our senior researchers at the SMC. She is writing a book, with computer scientist Siddharth Suri, on platform economies, digital labor, and the future of work.
In many ways, the assumption that workers no longer need a supportive or collaborative work environment and can act as self-directed actors is a fair one. Plenty of workers figure out how to find a good gig, develop routines for getting work done quickly, even find water-cooler chatter on worker-centered forums. A significant percentage of crowdworkers string together 30 to 50 hours of work, and rely on networks of peer support to maintain this level of productivity. Workers share information about how to sign up for platforms, what jobs to consider, employers to avoid, even how to do certain tasks when the task instructions leave out key details. Indeed, my time with workers shows that the API silently shifts the burden of finding, training, and retaining talent to workers’ shoulders.
“Working for the machine” –> Michael Bernstein, assistant professor of computer science at Stanford University, where he co-directs the Human-Computer Interaction group and is a Robert N. Noyce Family Faculty Scholar. His research focuses on the design of crowdsourcing and social computing systems.
The computer no longer is just our tool for doing work: it is becoming an instrument that gives us work. Online, networked societies have embarked on a massive shift to take work online, and that means an algorithm may be your next boss, or at least be your task matchmaker. Ask an Uber driver, who is told where to be and when by software. Or ask workers on Amazon’s Mechanical Turk marketplace, who execute information tasks for hours a day at piecework rates.
For Uber Drivers, Data is the Boss –> Alex Rosenblat, researcher and technical writer at Data & Society, a New York organization focused on social, cultural, and ethical issues arising from data-centric technological development.
From Uber’s perspective, drivers are a stopgap solution until autonomous vehicles can replace them. The more permanent Uber employees—the data scientists—algorithmically scrutinize the drivers’ movements to determine where they should be positioned to meet passenger demand. At Uber, drivers are also data points on a screen. The data they generate as they do their work feeds Uber’s surge pricing algorithm, can help determine how long it should take a driver to complete a trip, or could be used to move into markets beyond passenger delivery.
What isn’t counted, counts –> Karen Levy, postdoctoral fellow at New York University School of Law and the Data and Society Research Institute.
Consider long-haul truckers. Most are paid according to the number of miles they drive, which are increasingly tracked by their employers via GPS-enabled “fleet management systems.” What these systems don’t track (and what drivers aren’t paid for) is the time they spend on other essentials—like safety inspections, paperwork, and waiting for hours while their freight is loaded or unloaded at crowded terminals. But because their work is measured by miles driven instead of by some other metric (say, by number of hours worked), truckers have incentives to cut corners—hurrying their safety checks, speeding, ignoring the legally mandated rest breaks meant to keep the highways safe.
The Social Media Collective is showing up in force at Internet Research 16 in Phoenix, Arizona starting next week. Along with many friends of the SMC, there will be some of our permanent researchers (Nancy Baym, Tarleton Gillespie), postdocs current and past (Kevin Driscoll, Lana Swartz, Mike Ananny), past & present interns (Stacy Blasiola, Brittany Fiore-Gartland, Germaine Halegoua, Tero Karppi, J. Nathan Matias, Kat Tiidenberg, Shawn Walker, Nick Seaver), past and future Visiting Researchers (Jean Burgess, Annette Markham, Susanna Paasonen, Hector Postigo, TL Taylor), and our past Research Assistants (Kate Miltner and Alex Leavitt). Hope to see you there!
Below is a list of papers and panels they will be presenting:
WEDNESDAY, 21 OCT
THURSDAY, 22 OCT
11:00 am – 12:20 pm
1:30 pm – 2:50 pm
1:30 pm, -2:50 pm
3:10 pm- 4:30 pm
***The Nancy Baym Book Award will be presented to Robert Gehl for Reverse Engineering Social Media at the banquet on Thursday night
FRIDAY, 23, OCT
9:00 am – 10:20 am
9:00 am – 10:20 am
10:40 am – 12:00 pm
10:40 am – 12:00 pm
Tarleton Gillespie, Mike Ananny, Christian Sandvig & J. Nathan Matias
10:40 am- 12:00 pm
10:40 am – 12:00 pm
Jing Zeng, Jean Burgess, Axel Bruns
1:00 pm – 2:20 pm
Sharif Mowlabocus, Nancy Baym, Susanna Paasonen, Dylan Wittkower, Kylie Jarrett
2:40 pm – 4:00 pm
2:40 pm – 4:00 pm
4:20 pm- 5:40 pm
Greg Elmer, Ganaele Langlois, Joanna Redden, Axel Bruns, Jean Burgess, Robert Gehl
4:20 pm – 5:40 pm
SATURDAY 24, OCT
9:00 am – 10:20 am
Lee Humphreys, Jean Burgess, Joseph Turow
9:00 am- 10: 20 am
1:30 pm – 2:50 pm
3:10 pm – 4:30 pm
SMC is excited to welcome Tom Streeter, who will be soon making occasional visits to our New England lab, beginning later this month. To mark his arrival, we wanted to highlight the essay he has just published in the International Journal of Communication: “Steve Jobs, Romantic Individualism, and the Desire for Good Capitalism.” (Borrowing from the summary provided by IJOC here:)
The essay explains how that story and its repetition tell us more about the culture than the man. Building on previous work about the rise of “romantic individualism” as an organizing mechanism for high-tech capitalism, this essay focuses on the latest outpouring of discourse about Jobs since his death in 2011, analyzing both its continuities with past cultural forms and what it is about the present moment that has intensified the discourse—especially the post-2008 crisis of confidence in financial capitalism. Among other things, the tale offers the appealing, if ultimately unrealistic, hope of a capitalism with integrity, of a one-percenter who deserves it.
The Social Media Collective at Microsoft Research New England (MSRNE) is looking for two social media postdoctoral researchers (start date: 5 July, 2016). This position is an ideal opportunity for a scholar whose work draws on anthropology, communication, media studies, sociology, and/or science and technology studies to bring empirical and critical perspectives to complex socio-technical issues. Application deadline: Friday 6 November, 2015.
Microsoft Research provides a vibrant multidisciplinary research environment, with an open publications policy and close links to top academic institutions around the world. Postdoctoral researcher positions provide emerging scholars (PhDs received late 2015 or to be conferred by July 2016) an opportunity to develop their research career and to interact with some of the top minds in the research community. Postdoctoral researchers define their own research agenda. Successful candidates will have a well-established research track record as demonstrated by journal publications and conference papers, as well as participation on program committees, editorial boards, and advisory panels.
While each of the Microsoft Research labs has openings in a variety of different disciplines, this position with the Social Media Collective at Microsoft Research New England specifically seeks social science/humanities candidates with critical approaches to their topics. Qualifications include a strong academic record in anthropology, communication, media studies, sociology, science and technology studies, or a related field. The ideal candidate may be trained in any number of disciplines, but should have a strong social scientific or humanistic methodological, analytical, and theoretical foundation, be interested in questions related to technology or the internet and society or culture, and be interested in working in a highly interdisciplinary environment that includes computer scientists, mathematicians, and economists.
The Social Media Collective is comprised of full-time researchers, postdocs, visiting faculty, Ph.D. interns, and research assistants. Current projects in New England include:
– How does the use of social media affect relationships between artists and audiences in creative industries, and what does that tell us about the future of work? (Nancy Baym)
– How are social media platforms, through algorithmic design and user policies, adopting the role of intermediaries for public discourse? (Tarleton Gillespie)
– What are the cultural, political, and economic implications of crowdsourcing as a new form of semi-automated, globally-distributed digital labor? (Mary L. Gray)
– How are predictive analytics used by law enforcement and what are the implications of new data-driven surveillance practices? (Sarah Brayne)
– What are the social and political consequences of popular computing folklore? (Kevin Driscoll)
– How are the technologies of money changing and what are the social implications of those changes? (Lana Swartz)
SMC postdocs may have the opportunity to visit and collaborate with our sister Social Media Collective members in New York City. Related projects in New York City include:
– What are the politics, ethics, and policy implications of big data science? (Kate Crawford, MSR-NYC)
– What are the social and cultural issues arising from data-centric technological development? (danah boyd, Data & Society Research Institute)
Postdoctoral researchers receive a competitive salary and benefits package, and are eligible for relocation expenses. Postdoctoral researchers are hired for a two-year term appointment following the academic calendar, starting in July 2016. Applicants must have completed the requirements for a PhD, including submission of their dissertation, prior to joining Microsoft Research. We encourage those with tenure-track job offers from other institutions to apply, so long as they can defer their start date to accept our position.
To apply for a postdoc position at MSRNE:
Submit an online application here.
– On the application website, indicate that your research area of interest is “Anthropology, Communication, Media Studies, and Sociology” and that your location preference is “New England, MA, U.S.” in the pull down menus. IF YOU DO NOT MARK THESE PREFERENCES WE WILL NOT RECEIVE YOUR APPLICATION.
– In addition to your CV and names of three referees (including your dissertation advisor) that the online application requires, upload the following 3 attachments with your online application:
- two journal articles, book chapters, or equivalent writing samples (uploaded as two separate attachments);
- a single research statement (four page maximum length) that does the following: outlines the questions and methodologies central to your research agenda (~two page); provides an abstract and chapter outline of your dissertation (~one page); offers a description of how your research agenda relates to research conducted by the Social Media Collective (~one page)
After you submit your application, a request for letters will be sent to your list of referees on your behalf. NOTE: THE APPLICATION SYSTEM WILL NOT REQUEST REFERENCE LETTERS UNTIL AFTER YOU HAVE SUBMITTED YOUR APPLICATION! Please warn your letter writers in advance so that they will be ready to submit them when they receive the prompt. The email they receive will automatically tell them they have two weeks to respond but that an individual call for applicants may have an earlier deadline. Please ensure that they expect this and are prepared to submit your letter by our application deadline of Friday 6 November, 2015. Please make sure to check back with your referees if you have any questions about the status of your requested letters of recommendation. You can check the progress on individual reference requests at any time by clicking the status tab within your application page. Note that a complete application must include three submitted letters of reference.
For more information, see here.
Feel free to ask questions about the position in the comments below.
The latest issue of Media, Culture, and Society features an open-access discussion section responding to SMC all-stars danah boyd and Kate Crawford‘s “Critical Questions for Big Data.” Though the article is only a few years old, it’s been very influential and a lot has happened since it came out, so editors Aswin Punathambekar and Anastasia Kavada commissioned a few responses from scholars to delve deeper into danah and Kate’s original provocations.
The section features pieces by Anita Chan on big data and inclusion, André Brock on “deeper data,” Jack Qiu on access and ethics, Zizi Papacharissi on digital orality, and one by me, Nick Seaver, on varying understandings of “context” among critics and practitioners of big data. All of those, plus an introduction from the editors, are open-access, so download away!
My piece, titled “The nice thing about context is that everyone has it,” draws on my research into the development of algorithmic music recommenders, which I’m building on during my time with the Social Media Collective this fall. Here’s the abstract:
In their ‘Critical Questions for Big Data’, danah boyd and Kate Crawford warn: ‘Taken out of context, Big Data loses its meaning’. In this short commentary, I contextualize this claim about context. The idea that context is crucial to meaning is shared across a wide range of disciplines, including the field of ‘context-aware’ recommender systems. These personalization systems attempt to take a user’s context into account in order to make better, more useful, more meaningful recommendations. How are we to square boyd and Crawford’s warning with the growth of big data applications that are centrally concerned with something they call ‘context’? I suggest that the importance of context is uncontroversial; the controversy lies in determining what context is. Drawing on the work of cultural and linguistic anthropologists, I argue that context is constructed by the methods used to apprehend it. For the developers of ‘context-aware’ recommender systems, context is typically operationalized as a set of sensor readings associated with a user’s activity. For critics like boyd and Crawford, context is that unquantified remainder that haunts mathematical models, making numbers that appear to be identical actually different from each other. These understandings of context seem to be incompatible, and their variability points to the importance of identifying and studying ‘context cultures’–ways of producing context that vary in goals and techniques, but which agree that context is key to data’s significance. To do otherwise would be to take these contextualizations out of context.
We all have preferences for how we work. Maybe you’re the kind of person who likes to work in complete isolation, in which case this blog post is not for you. But if you’re like me, there’s something appealing about being deeply engaged in your own work in proximity to people who are also being productive. This is why I have long struggled to work at home and instead tend to write in coffee shops and libraries. I’ve also experimented with more intentional forms of co-working. For many years, my most successful attempt was with my friend Stephen. As a DJ, Stephen would work on mixes and set lists, while I would typically revise papers – beyond the fact that we’ve been friends for years and enjoy hanging out, I think we both got a lot out of the gentle pressure/quite support of collocated work. In the last few years, I’ve made several other efforts at co-working, spanning in-person, online and inter-species collaborations (#noclickbait – it’s not as exciting as it sounds), which I thought I’d share below. If you have other ideas for coworking, feel free to share them in the comments!