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Syllabus The "big data revolution" : a critical approach - 54232

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Last update 01-08-2017
HU Credits: 2

Degree/Cycle: 2nd degree (Master)

Responsible Department: cultural studies-individual graduate prog.

Semester: 2nd Semester

Teaching Languages: Hebrew

Campus: Mt. Scopus

Course/Module Coordinator: Dr. Laurence Barry

Coordinator Email:

Coordinator Office Hours:

Teaching Staff:
Dr. Laurence Barry

Course/Module description:
Big data has become in the last decade the trendiest tool in a wide range of domains: with the growing capacity to store large amounts of data, came also the algorithmic technologies to analyze them. Following Foucault's claim that power and knowledge come always as entangled, this course will attempt to grasp genealogically the social and political implications of the emergence of these technologies.
Using Foucaults conceptual toolbox, we will thus examine the power mechanisms propelled by the algorithms and the kind of social norms they imply. At the individual level, what can be said of the algorithms' effects on the contemporary self? If the process of subjectivation occurs in the relation of the self to truth, what is truth in the big data era, that some have coined the post-truth era? Finally, if the individual remains the provider of data, is there a way to resist this new order, and how?

Course/Module aims:
The course aims at granting a critical understanding of contemporary social and political processes that accompany the big data revolution, together with a greater familiarity with some of Foucault's writings.

Learning outcomes - On successful completion of this module, students should be able to:
Assess the political and sociological changes that affect contemporary societies with the generalization of the use of big data technologies.
Develop a consciousness of the way we are "conducted" and "subjected" as a result of these technologies.
Master some of Foucault's texts on the one hand and current critical literature on the algorithmic culture and society on the other.

Attendance requirements(%):

Teaching arrangement and method of instruction: Short frontal lectures in order to allow debate and discussion in class

Course/Module Content:
(not final)
The knowledge of big data
From neoliberal to algorithmic governmentality
New forms of control and profiling
Big data in election processes
The algorithmic self
The private/public divide
Post truth, fake news in genealogy
Imagined virtual communities
Artificial Intelligence
Legal issues and the possibility of resistance

Required Reading:
The reading list will include three sources:
- Foucault's texts as relevant to our subject;
- General literature to situate genealogically the matters at stake;
- Specific critical literature on the algorithmic culture and society.

The list will be available in the syllabus as distributed at the beginning of the course and as much as possible through Moodle

Additional Reading Material:

Course/Module evaluation:
End of year written/oral examination 0 %
Presentation 0 %
Participation in Tutorials 10 %
Project work 60 %
Assignments 0 %
Reports 30 %
Research project 0 %
Quizzes 0 %
Other 0 %

Additional information:
Students needing academic accommodations based on a disability should contact the Center for Diagnosis and Support of Students with Learning Disabilities, or the Office for Students with Disabilities, as early as possible, to discuss and coordinate accommodations, based on relevant documentation.
For further information, please visit the site of the Dean of Students Office.