Visualizing the Sociological Field

By Sharon Cornelissen and Joel Mittleman

All sociologists amongst us have probably faced this question at some point of their life, whether it is at a holiday dinner amongst family, on a first date with a non-academic (?!) or when striking up a casual conversation with a stranger: “So.. what is Sociology? What do sociologists actually study?” 

While I have occasionally stumbled my way through these questions unprepared, with incomprehensible inventions such as ‘the psychology of society’ or ‘the anthropology of the United States,’ Joel Mittleman, a classmate of mine – anticipating the same question in his SOC101 discussion session – came up with a more creative answer.

He word clouded the entire American Sociological Association 2014 Conference Program.

Joel, ASA word cloud

I think it is quite interesting and informative. For instance, the concepts of gender and race feature more prominently in the program than ‘class’ (if you check out Google NFrequency here you can see the steady decline in the use of ‘class’ since the early 1970s up to 2008 – it remains open whether we would observe a temporary increase again in recent years since 2008 due to the great Recession).  Even more interesting, of course, would be to see the changes over time; What would a word cloud of the ASA program in the 1950s have looked like? Or in the 1970s?

I, sociologist: Artificial Intelligence and the future of Sociology

By  Andrew Ledford

A long time ago, in a Galaxy far, far away and 2 B.K. (2 years before kids), my wife and I were weekly movie-goers.  We would pretty much go to see just about anything.  These days, 10 P.K. (10 years post-kids), the opportunity doesn’t come that often so we are pretty selective with what movie is “baby-sitter worthy.”  The most recent movie we saw was Spike Jonze’s “Her” starring Joaquin Phoenix in the not-so-distant future as a lonely writer who falls in love with his Operating System (OS). 

Her It is a quirky movie that has great appeal in how natural the relationship is portrayed.  For those who have not seen it yet, it is    absolutely “baby-sitter worthy.” 

In seeing “Her” and considering my newly found field of Sociology, I began to wonder if we are truly in the dawn of a new age for our discipline.  The type of AI as depicted in Her is different from the current program that “learns” your preferences on the Internet (which is slightly sinister), but rather true AI that can independently think, communicate, and most importantly reason without human influence.   This is considerably more advanced than what has been discussed in previous sociology conferences such as the one hosted by the National Science Foundation in May 1993. This conference looked at AI only in terms of “intelligently searching and analyzing data.”One of my colleagues upon reading the first draft of this post suggested that I not get too “sci-fi” with my concept of social interaction with machines but I believe that is exactly the point of this concept and the necessity it entails.

         Once the technology is there for AI to exist (as described earlier), the time it will take to surpass human capabilities will most likely be short considering the incredible capacity for simultaneous calculations and an extensive database of knowledge.  This is not just my opinion either but a consensus of an eclectic group at the Future of Humanity Institute at Oxford University.  As fantastical as the name implies, the Future of Humanity Institute has been deliberating over the existential risk facing mankind once AI “comes online.”  Scientists, mathematicians and philosophers come together to work through what happens when we aren’t the smartest beings on the planet anymore. In November, I attended a lecture by Oxford University Philosophy Professor, Nick Bostrom, whom is also the founding Director of the Institute. The lecture was truly awe-inspiring when considering the term  “the fate of humankind” was being tossed around like we were on the ground floor of the Manhattan Project.

As the Institute would argue, when, not if, AI surpasses human capability and becomes a “being” that can reason and interact with humans, it will be critically important to examine the interaction between the human race (now for the first time as a member of the “rational being” unit of analysis) and AI machines.   To do this, an AI sociologist will have to be a stellar programmer (e.g., Python is the first language they learn and then English), and the real dilemma will then be whether it would even be possible to study machines that are vastly superior in intellect. Will they let us?  One can conclude that studying a superior “being” might be similar to playing chess with a vastly superior player and wondering what their next move might be.  The challenges for human sociologists in understanding the reasoning of a machine might be even more difficult.   Assuming that the superior intelligence of AI will allow us to examine and study it, is it also possible that AI will begin to examine us?  It is not hard to imagine that there is the potential for AI to become sociologists of the human race as well in a desire to work alongside their creators.

They will be smarter, more efficient, and most likely have an ability to eliminate bias altogether, which their human counterparts cannot do.  Its quite possible that a machine would not have to disassociate itself from its own SES, country of origin or education.  Would it necessarily have the characteristics of the programmer that created it?  Would it be possible for the AI, assuming it does surpass human capability to then remove this characteristic altogether?  There are more questions than answers with this concept as the technology still doesn’t exist but it can become quickly unnerving.    It is not hard to imagine that an AI sociologist (the machine version) will be able to study human-to-human interaction better than a human sociologist will.

        Back to current day— it is an exceptional time to be a sociologist with the modern tools that are already bringing down many barriers to better sociological study than was possible even 10-15 years ago.   The advent of true AI likewise poses exciting new opportunities for this field.  Whether we are the examinees or the examined however, AI sociology requires serious contemplation and most importantly,  involvement from the sociological community in  discussions on the advent of this technology,  lest we find ourselves in the position of trying to play catch up with a more intelligent being.   At that point, even John Connor won’t be able to save us.


 

Caring as Invisible Work

By Samantha Jaroszewski

Feeding the Family

Over winter break, I read Marjorie Devault’s Feeding the Family: The Social Organization of Caring as Gendered Work, a book Devault argues that those responsible for the caring work of the family, usually women, deploy a vast store of tacit knowledge to perform their work, specifically feeding the family. Devault discusses this work as “feeding” work rather than merely food preparation because of the processual ways in which caregivers are constantly considering, calculating, negotiating, and preparing for the nourishment of their families. Feeding work constitutes part of reproductive labor, the daily or oft repeated tasks that reproduce the ability of household members to contribute to society. This usually includes feeding work, childreading, home economics, and other domestic sphere tasks without clear boundaries or definitive ends, summed up in the idiom, “A woman’s work is never done.”

I liken this work to a computer running with a high powered program running in the background. Writing this post, I had R Studio running on my desktop, a handful of annotated pdfs and eight Half.com tabs open in Chrome. The mental space my computer dedicated to these background tasks cannot be allocated to running whatever foreground program I needed at the moment. Similarly, Devault argues, women engaged in housework, work without clear boundaries and no actual “end,” impinges on their capacity to dedicate their mental CPU to other tasks.

In our roles as students, too, we have this constant background noise of the “reproductive labor”  of our schoolwork. There is always more to read, more to write, more to do. There are always four talks a week that we wish we could have gone to, but couldn’t spare the time that would be better spent getting our own stuff done. There are the paper and conference deadlines that loom above our heads, making it difficult to ever take a full break from work. These tasks garner us no positive reinforcement, no awards or praise. Its just part of the job. Similarly, there is much work and constant effort exerted towards feeding the family that just gets noticed when it doesn’t get done. We develop systems of tacit knowledge and routinize the tasks at hand in ways that perhaps we can’t articulate. Many of Devault’s interlocuters had trouble putting their routines to words, the ways that they made the decisions about food based on the preferences, schedules, tastes, and resources of each member of the family unit.

Devault’s book and her theoretical framing of mundane reproductive labor as gendered and inseparable from emotion-work for the women who perform it, has helped me reflect on my own practices and behaviors. It also reminds me to be thankful for the caring work that my husband does — not least listening attentively to my mundane stories about the lecture in my theory class — and the devalued caring work of many traditionally gendered occupations: mothers and child-rearers, teachers, nurses, cooks, housekeepers and secretaries. When I think of the women in any of those roles, I recall their warmth, their care. As people who care — not just gendered persons — Devault offers us a useful map of the caring landscape: the work that goes into feeding a family and organizing the care of a household.

  • What ethnographies, studies, or theories made you reflect on your own everyday practices?
  • What are other examples of invisible labor?