SOCI 395: Special Topics in Sociology

SOCI 395-004: Big Data, Tchnolgies & Society
(Spring 2018)

12:00 PM to 01:15 PM MW

Section Information for Spring 2018

We are living amidst a data revolution. Data, traditionally viewed as a scarce commodity, jealously guarded and expensively traded, now – in part due to radical technological developments and political lobbying – flows as a deep and wide torrent at relatively low-cost, supported by robust infrastructures. Much of it is increasingly open and accessible. Beyond and through the ubiquitous smartphone and “internet of things” that allow for the networking of the self within a planetary mesh of perception and response, radical technological developments are redesigning everyday life. Whether we are conscious of it or not, networked digital technology has become the dominant mode through which we experience the everyday. Witness augmented reality (providing an interactive overlay of the world);  digital fabrication (forging a new political economy of matter); cryptocurrency like Bitcoin and, likely more enduring, the blockchain (or the “programmable trust infrastructure” beyond it that has spawned such tools as “distributed applications,” “smart contracts,” and “autonomous organizations”); automation (and the annihilation of work and vast increase in precarious labor);  machine learning (the algorithmic production of knowledge); and artificial intelligence (in some cases, eclipsing human discretion). Increasingly, these data-laden technologies, and the data they collect and produce, shape the rhythms of our (“networked”) communities, (“smart”) cities, education, work, play, and knowledge of the world, as well as our sense of time, place, and self within it. In fact, they are changing the way we think – and the ways we now attempt to make sense of the world.

Managing flows of “Big Data” – a buzzword that simply denotes the extremely high volume, velocity, and variety (and, increasingly, veracity) of contemporary data production – has stressed conventional techniques (of applying structure to it by storing it in the linked cells of a relational database) to the breaking point. The new way of handling such massive amount of data is to look for patterns in previously unstructured data (say, from large bodies of text to real-time video feeds). Here, the patterns themselves begin to suggest the questions that might be asked of them. Big Data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted in widely varying contexts. While the main hype has focused on tracking and targeting consumers, a new crop of social entrepreneurs and activists see opportunities to improve the state of the world by making sense of the current-day data deluge. And while they may employ similar tools on the backend, their motivation stems from a desire to help alleviate some of the world's most pressing problems; poverty, inequality; disease, ecological harm, war and famine. Practitioners in fields such as public health and humanitarian relief view big data as a critical driver of empirically based problem-solving.

In this course, we not only explore the new technologies, relations, and practices emerging in the course of this data revolution, but also examine how the availability of Big Data, coupled with new data analytics, challenges established epistemologies (or theories of knowledge, especially with regard to its methods, validity, and scope, that distinguish justified belief from opinion) across the sciences, social sciences and humanities. We assess the extent to which they are engendering paradigm shifts across multiple disciplines. We explore new forms of empiricism that declare “the end of theory,” the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, history, economy and society.  Students will critically engage the epistemological implications of this unfolding data revolution, and survey the rapid changes in research practices presently taking place. We review emerging epistemological positions, including social science research approaches that emphasize a more situated, reflexive and contextually nuanced epistemology. In addition to highly engaging and accessible readings, students also will meet guest lecturers throughout the course who are working with Big Data in innovative ways across a variety of applied settings to shape our futures. Learn how to meaningfully participate in this process – enroll now!

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Course Information from the University Catalog

Credits: 3

Introduces the research interests of the faculty, offering new courses that reflect current issues not yet incorporated into the curriculum. Offers, in addition, advanced study into topics covered in the standing curriculum. Topics change by semester. May be repeated within the term for a maximum 18 credits.
Specialized Designation: Topic Varies
Recommended Prerequisite: SOCI 101
Schedule Type: Lec/Sem #1, Lec/Sem #2, Lec/Sem #3, Lec/Sem #4, Lec/Sem #5, Lec/Sem #6, Lec/Sem #7, Lec/Sem #8, Lec/Sem #9, Lecture, Sem/Lec #10, Sem/Lec #11, Sem/Lec #12, Sem/Lec #13, Sem/Lec #14, Sem/Lec #15, Sem/Lec #16, Sem/Lec #17, Sem/Lec #18
Grading:
This course is graded on the Undergraduate Regular scale.

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