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What’s queer about the internet now?

February 28, 2017

This past month, I organized the Queer Internet Studies Workshop with my longtime friend and collaborator, Jack Gieseking, and Anne Esacove at the Alice Paul Center at UPenn.  This was the second QIS (the first was in 2014 at Columbia), and our plan was to organize a day long series of conversations, brainstorming sessions, panels, and chats dedicated to broaden thinking about the internet.  Rather than a formal conference of people presenting their research, QIS is intended (1) to identify what a queer internet might look like (2) to give a sense of research that’s being done in this area, and (3) to collaborate on artistic, activist and academic projects.We’ve been lucky to have folks post some terrific blog posts about the event, but here’s a quick recap.  After opening the day with group discussions about what queer internet studies might be and how (or whether) we could study it, a carefully curated group of researchers and activists shared their expertise in a facet of queerness and media.

  • Mia Fischer talked about intersections between trans people and surveillance studies.
  • Oliver Haimson described his work on trans identity and social media.
  • Carmen Rios spoke about online communities and feminist politics.
  • Adrienne Shaw  shared her work about building an LGBT games archive.
  • Mitali Thakor shared her work on digital vigilante-ism against sex trafficking.

Artist and academic TL Cowan led a participatory workshop called “Internet of Bodies/Internet of Bawdies.” Part theoretical inquiry, part brainstorming session, and rapid prototyping exercise, the workshop offered an embodied means of working through sexuality, performativity, and technological change.

Rather than a traditional keynote dialogue, we asked Katherine Sender to act as an interlocutor for Shaka McGlotten. Their dialogue ranged from racism and desire to sped up and slowed down experiences of intimacy, from surveillance and performativity to social media platform politics. As a freeform conversation, Sender and McGlotten both addressed and reworked themes that had surfaced throughout the day around queerness, technology, and desire.

We closed the day with breaking into groups to talk about outcomes, which included pooling resources to develop syllabuses and course materials, collaborating on a special issue, and developing best practices around respecting privacy and ownership of online content.  I’m excited to see where these plans and provocations end up in the coming months.  A huge thanks to my co-organizers, the attendees and speakers, and our sponsors.  In 2017, it’s clear that we need spaces for queerness and media provocation more than ever, it’s my hope that QIS can continue to be a space for those connections and creativity, both as a physical meetup and as a chance to build enduring social ties.

Learn It, Buy It, Work It! Performing Pregnancy on Instagram

January 20, 2017

Katrin Tiidenberg (Aarhus University, Denmark and Tallinn University, Estonia) and SMC Principal Researcher Nancy Baym (Microsoft Research, New England) have recently published an article in Social Media + Society that analyzes how pregnancy is performed on Instagram. According to Tiidenberg and Baym,

‘Pregnancy today is highly visible, intensely surveilled, marketed as a consumer identity, and feverishly stalked in its celebrity manifestations. This propagates narrow visions of what a “normal” pregnancy or “normal” pregnant woman should be like.’

Drawing on Tiidenberg’s work during her Ph.D. internship with the SMC (2014), the article asks:

‘[W]hether they [women] rely on and reproduce pre-existing discourses aimed at morally regulating pregnancy, or reject them and construct their own alternatives.’

You can read their findings here.

“Just how artificial is Artificial Intelligence?”

January 9, 2017

SMC member Mary L. Gray (Microsoft Research, New England; Berkman Kein Center for Internet and Society) and colleague Siddharth Suri (Microsoft Research, New York) have published an article for the Harvard Business Review asking, “just how artificial is Artificial Intelligence?”

Whether it is Facebook’s trending topics; Amazon’s delivery of Prime orders via Alexa; or the many instant responses of bots we now receive in response to consumer activity or complaint, tasks advertised as AI-driven involve humans, working at computer screens, paid to respond to queries and requests sent to them through application programming interfaces (APIs) of crowdwork systems. The truth is, AI is as “fully-automated” as the Great and Powerful Oz was in that famous scene from the classic film, where Dorothy and friends realize that the great wizard is simply a man manically pulling levers from behind a curtain.

For Gray and Suri, the mythos of “full-automation” is akin the Great and Powerful Oz, famously depicted as a man “manically pulling levers from behind a curtain” in the classic American film.

This blend of AI and humans, who follow through when the AI falls short, isn’t going away anytime soon. Indeed, the creation of human tasks in the wake of technological advancement has been a part of automation’s history since the invention of the machine lathe.

Full text of the article is available here.

Amplifying the Presence of Women in STEM

December 8, 2016

December 7-13th is Computer Science Education Week!

Recently, feminist media scholars have demanded we take seriously seriously the dearth of women and people of color in computing fields. This week presents the opportunity to broadcast professional role models to inspire young minority techies in pursuit of their STEM dreams, both in industry and in academia.


Source: Microsoft Corporate Blogs

Mary L. Gray, senior researcher at the Social Media Collective, was recently featured in Microsoft’s “17 for ’17: Microsoft researchers on what to expect in 2017 and 2027,” which sought to work against this gap by highlighting 17 women from within their global research organization.

Mary offers insights on the digital world we should anticipate over the next decade and where to position ourselves as scholars.

Reminder, the application deadline for 2017 SMC internships is fast approaching…

December 8, 2016

Just a reminder, January 1 is the deadline for applications for the summer 2017 internship program with the Social Media Collective, at Microsoft Research New England. All the information you need, about the internship, the necessary qualifications, and how to apply, can be found here. During their twelve-week stay, SMC interns devise and execute their own research project, distinct from the focus of their dissertation. The expected outcome is a draft of a publishable scholarly paper for an academic journal or conference. Our goal is to help interns advance their own careers.

The Social Media Collective (in New England, we are Nancy Baym, Tarleton Gillespie, and Mary Gray, with current postdocs Dan Greene and Dylan Mulvin) bring together empirical and critical perspectives to understand the political and cultural dynamics that underpin social media technologies. Primary mentors for this year will be Nancy Baym and Tarleton Gillespie, with additional guidance offered by other members of SMC.


“These Days, Everyone Needs a Side Hustle”

November 23, 2016

Uber has TV ads now. The one I see most often is called “Get Your Side Hustle On”. It opens with a thirty-something black male Uber driver telling us, somewhat wearily, “These days, everyone needs a side hustle.” Then the upbeat horns pick up, he and his passenger start dancing, and he tells us how Uber helps drivers move “from earning, to working, to chilling at the push of a button.” He’s earning in his car, working when he’s teaching middle-school chemistry, and chilling when he’s passed out on the couch in the middle of the day, his daughter reading beside him. The side hustle is what helps you make ends meet. Uber, now valued at around $62.5 billion, helps you get your side hustle on whenever you have spare time to slip between your full-time job, your childcare responsibilities, your social life, and your sleep schedule.

There’s some romance to this story, of course; Americans love a hustler. But all credit to Uber, because this ad seems to be an accurate representation of their business model and the reason why they, founded in 2009 and officially launched in 2011, and the rest of the gig economy have grown so rapidly in the wake of the 2008 financial crisis.  New data from Pew show that folks on the fringes of the formal labor market, those without secure jobs or the sort of wealth that provides a cushion in tough times, are seeking out gig economy work to make ends meet.

This a sizable group: 8% of Americans earned money from technology-enabled gig work last year. Pew calls these tools for soliciting drivers, handymen, shoppers, and data-enterers ‘labor platforms’, distinct from the ‘capital platforms’ used to rent your home or sell your bespoke wares. Another 18% of Americans made money from the latter in the last year. It is no coincidence that the growth and success of gig platforms has taken place during a period of stagnant wages and labor market bifurcation (i.e., the jobs generated in the wake of the crisis have been concentrated in high-wage knowledge sectors and low-wage service sectors, with the middle increasingly disappearing). It is precisely because so many Americans have needed to find a little work on the side that these gig platforms are thriving. These days, everyone needs a side hustle.

This is not an altogether new phenomenon. The so-called ‘informal economy’ often grows during recessions. When good jobs are hard to find, people seek out other, less-regulated means to put food on the table: selling food out of a cooler at the bus stop, taking in neighbors’ laundry, offering handyman services to other members of your church, or driving an unlicensed taxi for a few spare bucks. In previous eras, these would have been largely off-the-books, cash-only exchanges, because individual hustlers don’t want to get the health department, the taxicab commission, or the taxman involved. But the genius of Uber, TaskRabbit, and the like is that they formalize these previously informal exchanges by making them accessible to any consumer with a credit card and a smartphone, while simultaneously retaining the informality that frees the company from the obligations employers typically owe employees or regulators. And of course, gig platforms create many new opportunities for this work just by providing extensive logistical support for it, support that justifies their extraction of rent from this newly formalized work conducted on their platforms.

What was the macroeconomic soil in which these business models took root? According to the Economic Policy Institute, while US workers’ productivity has grown by leaps and bounds since 1979, their real wages have barely budged—and low-wage workers’ pay has actually fallen. The exception is the top 5% of earners, whose wages have grown 41% since 1979. So most of our wages haven’t grown in a few decades, while the cost of expensive, essential outlays like housing, healthcare, and college have soared.

More recently, the 2008 financial crash destroyed many Americans’ financial safety nets by wiping out their main sources of wealth—their investment in their homes and their retirement accounts, typically 401Ks—and put serious strain on other savings and investments, if they had them. There has always been a massive wealth gap between white Americans and people of color, which severely restricts the social mobility of the latter, since inherited wealth is a crucial ingredient in affording big things like housing and college and smaller things like unpaid internships This gap widened a great deal in the wake of the housing crash, with black and Latino households losing three and four times more wealth respectively than white households between 2007 and 2010. And while the unemployment rate has finally fallen back to pre-recession levels, the jobs that we have regained since the recession have not been good ones. The National Employment Law Project found that while employment losses during the recession were concentrated in mid-wage and higher-wage industries, the employment gains during the recovery have been concentrated in low-wage industries.  We’ve had an uneven recovery, especially for people of color.

How does Pew’s new data on gig economy workers fit into these trends? Well, the data only provide a snapshot. To confirm my speculation that gig platforms capture precarious Americans’ informal work and extend the opportunity for a side hustle to others, we’d need to know more about trends in gig economy work across time and geography (e.g., whether tighter local labor markets discouraged gig work or not), and what sort of other work gig workers are doing. But this snapshot seems to support my suspicions:

  • 56% of labor platform users say the money they earn through those platforms is either ‘essential’ or ‘important’ to meeting their basic needs, as opposed to being ‘nice to have’ (42%). They’re more likely to have a household income below $30,000 (57%), be nonwhite (64%), and lack a college degree (52%).
  • Recalling our black male middle-school teacher going from chilling to working at the push of a button, labor platform users for whom those earnings are essential or important are more likely to say they use the platform because it gives them control over their own schedule (45%) and because there are few jobs in their area (25%). Those who say the money is nice to have are more often (62%) motivated by the work being fun, or just something to do.
  • 14% of black Americans and 11% of Latinos earned money from online gig work in the past year, compared to 5% of whites. Black Americans are more likely to have done physical gigs like driving or taking in laundry (5%) than white Americans (1%)
  • Fewer than half (44%) of technology-enabled gig workers are employed full-time. 32% are unemployed.
  • Americans making less than $30,000 per year are more than twice as likely (10%) to do gig work than Americans making more than $75,000 per year (4%).
  • Compared to Americans overall, technology-enabled gig workers are less likely to have health insurance (10% lower than the national average), a credit card (15% lower), or a retirement account (13% lower).

Importantly, Pew finds large differences between labor and capital platforms; users of the latter are older, whiter, wealthier, more highly educated, and less reliant on these earnings than gig workers. Who, then, is most likely to be a gig worker who needs that side hustle? A working-class person of color without a college degree who is fitting that hustle in between other life tasks because they’re making less than $30,000 a year, lack a financial safety net, and struggle to afford healthcare. So, that Uber ad wasn’t 100% correct: Some people need a side hustle more than others these days.

The language of the ‘sharing economy’ positions all of us equally in the same community of app users. Indeed, the main advocacy group for the industry, now packaging portable benefits for gig workers, is simply called Peers. But if we read the latest data alongside earlier data on consumers of gig platform labor, it becomes clear that we are not all on the same page. An earlier Pew report found that super-users who purchase services from six or more of these platforms are generally digitally literate, college-educated urbanites making $75,000 or more. The gulf between frequent suppliers of labor to these platforms and frequent purchasers of that labor mirrors the gulf in the labor market that has been growing for decades but which ballooned after the recession: Low-wage service jobs with unpredictable schedules and no benefits on one side, and high-wage knowledge economy jobs concentrated in urban areas on the other.

That so many are desperate to supply their labor for these platforms must surely be a major factor in their growth. They were the right model for the right moment. With good jobs drying up and people looking for extra, flexible, informal work, these digital platforms were ready to welcome them. In precarious times, the side hustle is a growth industry.

Dan is a postdoctoral researcher with the Social Media Collective at Microsoft Research New England.  He studies the institutions and technologies that teach us how, where, and why to work in the information economy. You can learn more about him and his research at

Spike in Online Gig Work: Flash in the Pan or Future of Employment?

November 17, 2016

Most conventional jobs involve hierarchy. A boss divvies up work to the office’s full-time employees awaiting direction and a green light. While still true for the majority of American workers, a growing number of people are picking up work online — accepting jobs with companies that assign, schedule, route, and pay for work through websites or mobile apps. This on-demand “gig work” is unraveling the typical job. Yet none of our current workplace statistics or labor laws reckon with the new employment reality turning APIs into shift managers. Our research team spent the past two years conducting one of the largest, most comprehensive studies of its kind to learn about the lives of on-demand gig workers. One of our greatest challenges was that we didn’t have a representative sample of American workers that could validate and enrich our findings. That is…until now.

We shared our survey questions and preliminary findings with the Pew Research Center for Internet, Science and Tech as they designed their survey, “Gig Work, Online Selling and Home Sharing.” Pew wanted to develop a better way to gauge how many people, from a representative sample of the U.S. population, participate in gig work, ridesharing (think apps like Uber and Lyft) and homesharing (via sites like Airbnb and VRBO). It is hard to get a good headcount of those earning an income in the gig economy because the words to describe these jobs change with the launch of a new on-demand service or court case challenging what it means to “work” for a mobile app. Ridesharing and homesharing are more visible in the media. But a variety of jobs are quietly shifting online to become on-demand gig work, too. TaskRabbit and Thumbtack, for example, connect consumers with trade workers available to do the task. Crowdflower and Amazon Mechanical Turk are two of the more popular “crowdsourcing” platforms. They offer companies a way to post tasks online to a pool of people who have signed up to sift through the platform’s online listings of work opportunities. These public crowdsourcing platforms are the tip of the spear. Today, nearly every large tech company developing artificial intelligence uses proprietary services like these. The on-demand labor that AI-fueled jobs create is hard to measure, let alone see. The typical jobs performed on these platforms are white-collar office gigs, like transcribing audio, labeling images, and reviewing social media material flagged as “adult content” or “not safe for work.”

Before Pew’s report, scholars and policymakers had only the Contingent and Alternative Employment Arrangements survey, last run in 2005, to estimate the size and growth rate of this workforce. A lot has changed since then but worker surveys never caught up with the technology trends radically altering the workplace.

The Pew’s findings confirmed everything we learned. It is the perfect complement to our roughly 200 in-person interviews, tens of thousands of survey responses, dozens of behavioral experiments and big data analyses of gig work platforms. It also spotlights how quickly temp and contract work have changed for U.S. workers since the Great Recession.

According to the Pew report, about 5% of the U.S. population, or 1-in-20 people, does some form of online gig work. To put that in perspective, online gig work was a far more common source of income than homesharing (at about 2%) or ridesharing (around 1%).

How important is earning money from gig work to those who do it? Are we talking about college students earning beer money or people trying to put food on the table? According to Pew:

· Only 8% of those surveyed said the money they earned from selling goods online is “essential for meeting my basic needs.”

· Eighteen percent said the same of money earned from homesharing.

· But roughly one quarter of those doing gig work reported that the money they earned was essential for meeting their basic needs.

· Another one quarter said the money was important.

According to the Pew analysis, “workers who describe the income they earn from these platforms as ‘essential’ or ‘important’ are more likely to come from low-income households, more likely to be non-white and more likely to have not attended college.”

The reliance on gig work income reported in the Pew survey is echoed in our own survey of over 2,000 gig workers, collected across 4 different platforms. Over half of our study’s respondents reported that they had a minimum amount of money that they needed to make that month from gig work.

Part of gig work’s appeal is a chance to manage one’s own workflows. Of the people who said doing gig work was “essential” or “important” in the Pew survey:

· Just under half reported that they do this work because they have a “need to control their own schedule.”

· Another quarter said there was a “lack of other jobs where they live.”

In fact, according to one of our study’s experiments, gig workers were willing to take somewhere between a $0.40/hour and $0.80/hour pay cut to work on tasks that allowed them some degree of control over when they complete the task. And almost every one of our interview participants described balancing care for a loved one or completing a school program as the kind of constraint that pushed them to seek online work. Clearly, people do this kind of work because they need the job, they need to control their schedules and/or they don’t have a lot of employment options in their hometowns.

Pay attention to online gig work because it is dramatically reshaping our society. Labor economists Lawrence Katz and Al Krueger estimate that conventional temp and alternative contract-driven work rose from 10 to 16%, accounting for all net employment growth in the US economy in the past decade. Assuming Pew’s trends continue at the current rate, by the year 2027, nearly 1 in 3 American adults will transition to online platforms to support themselves with on-demand gig work. This is only bad news if we do nothing to change the outdated laws and structures in place to support working people. Ignoring corporate and consumer dependency on an on-demand gig workforce is not a sustainable strategy.

Pew’s study is robust proof that the world of work — what we spend most of our time doing — is quickly moving online. Platform start-ups are cropping up every day to connect people directly with employers for short-term gig work. There is no evidence that this trend will reverse and every indication that the move to on-demand gig work is well underway. The future of work will look more like the apps and web-based platforms that we have been studying the past two years than the “traditional” employment around (some of us) today. These workers may be difficult to see but they are vital to the future of our economy. Our country cannot afford to leave them behind.

Siddharth Suri (@ssuri) is a Senior Researcher at Microsoft Research, New York City. Mary L. Gray (@maryLgray) is a Senior Researcher at Microsoft Research, Associate Professor at Indiana University and Fellow at the Harvard University Berkman Klein Center for Internet & Society. They are writing a book about workers’ experiences of the on-demand economy. You can read more about their research at