Reflections on SoCS

I apologize for not blogging last week. I was at the SoCS PI conference in Seattle as the student representative of my research group’s grant, learning a lot about different areas of social computing and the larger paradigm of academia. I’ll use this blog post to briefly review what I learned at the conference, and then post again about things more immediately relevant to my internship.

SoCS stands for Social Computing, and is pronounced like the counterpart to “shoes”. According to Wikipedia, Social Computing can be considered “a general term for an area of computer science that is concerned with the intersection of social behavior and computational systems” (brief, awesome tangent: while compiling the first draft of the practitioner guide for PPSR data policy, I spent some time looking at different court rulings a) specifically about clickwrap v. browsewrap agreements, and b) generally pertaining to crowdsourcing. One of the rulings I found in the later category was Bates v. State, a case heard in the Alaska Court of appeals that used the Wikipedia definition of “dating” as a best representation of the “zeitgeist,” hence affirming the legal validity of some types of crowdsourced content.  In a complementary ruling, Bates, Rainey v. Grand Casinos, Inc. noted that crowdsourced content should not be relied upon for “bright-line, verifiable” facts).

From my perspective as an HCI researcher, this definition is a bit strange. Given that computers exist qua tools that serve the needs of human beings, shouldn’t all areas of computer science be concerned with at least some aspects of social behavior?  I believe this perspective is shared by colleagues at the conferences I usually attend, such as CHI (Computer-Human Interaction) and CSCW (Computer-Supported Cooperative Work). So SoCS was notable because, when I looked around the room during the closing remarks, I noticed about 50% of attendees that (based on the research they presented) cared about machines— singly, and passionately, the way some teenage girls care about Justin Bieber—and about 50% who cared about people as well.

The machines people aren’t bad people, of course; they’re not apathetic about the human race as a whole. But they’re also probably not the types of people that would join me in geeking out over the temporal arcs of motivation or the ways that user experiences change over time due to the evolution of how a computational artifact is perceived.  SoCS (which is now dead as a source of funding; as our program officer said, “Try HCC instead”) was a good call because it required, as a condition of receiving money, the collaboration of researchers in different fields.

Our project funded through SoCS, Biotracker, draws on the expertise of “computer” and “social” scientists in order to combine “computer vision, state-of-the-art mobile phone technologies, and the Internet to encourage science enthusiasts to gather biological data.”  Other projects funded under SoCS include a study of how online social networks can facilitate real-life relationships, a project that uses technological interventions to increase political consciousness at the community level, and a study examining how human and computer intelligence can be combined to avoid misclassifications of different types of birds. Achieving the goals of these projects—or even making substantial progress toward achieving them—would be impossible without a) the technical intelligence of people who care about computers, and b) the social understanding of people who care about people more.

Outliers are interesting because they are not the status quo. Unfortunately, the level of collaboration and integration involved is SoCS projects is not typical of academic research. I know this through my experience as a student, and also through a lit review conducted for my DataONE internship about the history of scientific funding in the USA and the norms that this history engendered.  People who study citizen science as a phenomenon find it interesting in part because it blends hobby-level interest with some level of scholarly expertise. But citizen science also crosses disciplines more frequently than other crowdsourcing projects do; at the very least, most projects have a “biology person” and a “technology person” working in tandem (although at certain times the “technology person” is in actuality a “biology person” who converted out of necessity).

My mentor, Andrea Wiggins, wrote a paper entitled “Free as puppies: Compensating for ICT constraints in citizen science” cautioning against the use of suboptimal ICT by citizen science campaigns.  When I first read the paper, I was in the process of transforming a piece of “suboptimal ICT” into a more optimal mobile application. During this time, I listened to the director of the project that I was working with express embarrassment that she didn’t have a good mobile app functioning despite having access to a larger budget and a larger staff than similar campaigns.  What I read and what I experienced played off each other, and encouraged me to think deeply about the role of technology in citizen science or PPSR.

What I realized was this: as projects progress, they will require more than just a “biology person” and a “technology person” with a high level of expertise.  For example, many projects are starting to consider the importance of education or political outreach, both at the community level and on larger scales.  How long will it be before citizen science projects will need at least a “biology person,” a “technology person,” and an “education/ outreach person” to operate at their full potential? Two years?  Three? And how long before finding an “education/ outreach person” becomes a realistic goal?  The answer to this second question depends, in part, on the ability of projects to secure funding that will be increasingly cross- disciplinary and inter-disciplinary.  In this respect, citizen science shares some parallels with the really good social computing research that I witnessed at SoCS.

The big question that comes out of this blog post is, “what can we, as researchers, do to secure cross-disciplinary funding?”  A big question is essentially a question that needs to be broken down into smaller pieces before it can be adequately addressed.  Funding is closely connected to institutional support.  One access point into addressing this question could simply be acting—speaking, reading, researching—in ways that demonstrate the value of cross-cultural work in different institutional settings. This is less a solution and more a best practice to be integrated into everyday life.  As such, it’s something that I have the agency to accomplish—a starting point, for supporting future work.