Postgraduate

Module Content:

Data and algorithmic practices are increasingly shaping and informing social life - from the meta-data harvested as we use social media and used to target us politically, to the biometric data extracted when we enter securitised spaces that is used to profile and racialise, to the rise of self-tracking and mhealth as means of self-care. What can the anthropological study of these practices tell us about emergent forms of sociality? This course will equip students to engage critically with a range of social, cultural and political issues that surround the increasingly pervasive production and circulation of digital data and algorithmic practices.

Drawing on a number of major theoretical debates in anthropology, we will analyse different ethnographic studies of data practices drawn from anthropology, science and technology studies and other disciplines, in order to explore questions such as: Can a person be their data? Is the relationship between state and citizen changing because of big data and algorithms? What is happening to the body in data-driven biomedicine? Are notion of ownership and property transforming in a digital knowledge economy? How are data practices such as the Quantified Self movement re-shaping notions of selfhood and identity? Are algorithmic practices reproducing or deconstructing racialising categories? How can we study such algorithmic practices ethnographically, and should we critique, resist, or co-opt them?

The course will simultaneously engage students in current theoretical debates in anthropology, teach students how to use these theoretical debates to interrogate the claims and promises of digital data and algorithmic practices, and ask how these theoretical debates might be taken in new directions by engaging with data and algorithms as ethnographic subjects. There will be a particular focus on the methodological challenges that such a new areas of study pose for anthropology.

Indicative Topics

Is data new? Anthropological approaches to data, algorithms and computation
	What are data and algorithms? Materiality, immateriality, relationality
	Do we own ‘our’ data? Exchange and property
	Data nature? The digital Anthropocene
	Data bodies? The social and the biological
	Data selves? Self-tracking and personalisation
	Data citizens? The state
	Algorithmic justice? Society and the individual
	Big Data Hype: critique and resistance
	Ethnography, data and algorithms: new collaborative methods?
Teaching Delivery:

This course is seminar-based. There is a weekly two-hour seminar which is compulsory. The seminars will be a combination of a short lecture, close analysis of the texts in groups, and class discussion and debate. You may also attend the weekly undergraduate lectures if you can.

 

Learning Outcomes: Postgraduate Level 7

Knowledge -

You will develop a fluency in and excellent working knowledge of several major theoretical debates in anthropology and science and technology studies, as well as emerging contemporary debates around data and algorithmic practices from across a selection of disciplines including anthropology, science and technology studies, media studies, sociology, and information studies.
	You will be able to discuss both the merits and the limits of these approaches, and locate the areas that require further research within the anthropological study of data and algorithms.
 

Understanding -

You will be able to apply your knowledge of anthropological theory to new settings and contexts relevant to the study of data and algorithms.
	You will be able to develop an original argument that allows you to compare the limitations of different scholarly approaches to data and algorithmic practices, and to critically engage in current events around data and algorithmic practices.
	You will be able to define a field site that will allow you to test this argument, and be able to debate the different methodological obstacles and opportunities that the field site poses for classical anthropological field methods.
	You will be able to evaluate the ethical issues at stake in the study of your chosen field site.
 

Skills - 

You will learn how to write a convincing research proposal.
	You will become conversant with a number of different methodological possibilities for the qualitative study of data and algorithmic practices.
 

Additional Information:

This course is theoretically orientated, and challenging. It is designed on the basis that students will be complete all the readings and engage in the discussions and activities. It is an opportunity for students to be actively involved in an emerging sub-field in anthropology, and as a result the course does require that students come ready to engage fully in the themes and material.

The final assessment is a research proposal, in which the student is expected to use the material from the course to find a relevant field site, propose a methodology, and discuss the theoretical importance and implications of the study of such a site. The course co-ordinator will explain exactly what is expected of the final assessment in the first lecture and last lectures, including the marking criteria. To support the development of your research proposal, there will be a formative assessment (peer reviewed, unmarked) in the first reading week.

 

Please note the assessment titles may be subject to change.