Module ANTH40A15: Critical Perspectives in Data Science

Department: Anthropology

ANTH40A15: Critical Perspectives in Data Science

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To develop an understanding of the production, analysis and use of quantified data as a combination of human and non-human practices, and to analyse these practices anthropologically.
• To introduce students to wider debates in the anthropology and sociology of quantification, including situating contemporary data practices within larger trends in the history and philosophy of science and knowledge production.
• To provide students with the tools to think ethically and contextually about the production, analysis, and use of quantified data, and to apply these tools to practically problems in Data Science and in particular to their own proposed projects.
• To interrogate the role of quantified data in governance and relationality at multiple levels – at the level of the global, the national, the interpersonal, and the self.
• To provide data scientists an opportunity to practice engaging with various stakeholders of their research, as well as how work collaboratively and to think through complex issues.

Content

• The module takes an interdisciplinary approach – which will include resources from critical medical anthropology, social and cultural anthropology, sociology, history, and science and technology studies (STS) – to analysing data practices and infrastructures.
• Topics may include: the production and use of data in constituting health problems and solutions, the ethics of imputation and estimation when representing people and problems, the rise of Big Data in global governance, situating contemporary structural data inequalities (e.g., statistical capacity) in larger histories of unequal flows of capital, algorithms as culture, and the Quantified Self and tracking devices.

Learning Outcomes

• At the end of the module, students will be able to:
• Identify and make use of relevant literature.
• Be competent in accessing and assimilating specialised research literature of an advanced nature.

• At the end of the module, students will be able to:
• Demonstrate advanced knowledge and understanding of anthropological and interdisciplinary approaches to the politics and culture of quantified data.
• Deploy analytical skills specific to the anthropology of data.
• Demonstrate in depth knowledge of data practices and infrastructures, the structural forces that shape them, and the contribution anthropology can make to deepen our understanding.
• Think clearly and independently about the intersection of statistics and society.

• At the end of the module, students will be able to:
• Communicate complex theoretical ideas and their relationship with empirical research material through written work.
• Show initiative to find resources on their chosen assessment topics and to apply those resources in the evaluation of theory and apply it to practical examples.
• Pursue interdisciplinary research.
• Write an essay which answers a question in an appropriately focused manner, with a clear and concise discussion of the topic area and a structured argument.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• This module will be delivered by the Department of Anthropology with input from Computer Science.
• Most of the teaching will take the form of two-hour plenary sessions, which include lecture, tutorial, and practical components, in order to allow presentation, discussion, and use of the subject of the lecture components. In these plenary sessions, we will address questions that are central to contextualizing data practices and apply anthropological and ethical thinking to real life cases. Students will have the opportunity to ask questions and debate the topics outlined in the lecture and will be encouraged to develop their own opinions and defend their own points of view with the help of concepts from anthropology and STS. They will be guided through the material and have a chance to develop both their analytic and argumentative skills.
• The tutorials will enable smaller groups of students to target a specific research area (based on the essay topic they have chosen) and participate in in-depth discussions of this particular topic. They will have a chance to examine the wider ramifications of their research area and reflect on its practical relevance in Data Science. These tutorials will also enable students to work on their essay-writing techniques, receiving individual guidance where appropriate.
• Student preparation and reading time will allow engagement with specific references in advance of classes and will introduce general and particular reading related to the assessment, which will be an essay related to students’ final project for the MDS course.
• Towards the end of the module the students will attend a workshop focusing on specific applications of the theories they have studied. During this workshop students will present a team-based case study. They will defend their arguments by responding to questions. This will help students to develop their skills for collaborative anthropological and ethical decision making.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

One formative preliminary draft of a component of the summative essay (1000 words). A team-based presentation on a separate topic from the summative assessment.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University