Data Subjects 2021 @ ddinf Aarhus

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🤖 General information

click for Covid19-related information*

Instructor: Pablo Velasco // pvelasco@cc.au.dk // https://pablov.me/
Office: 5347 (Wiener building) room 117

LECTURE
Time: Tuesdays 12.00-14.00
Location: ~~5520-112~~ online

WORKSHOPS (hold)
Time: Fridays 13.00-15.00
Location: ~~5008-127~~ online

Public course catalogue: english / danish
Curriculum information (see 2nd Semester “Data Subjects” Exam details/Prøvedetaljer): english / danish

What is this course about?

The course focuses on the individual as a user and producer of data, but also as shaped by data. The course focuses on the various practices and technologies by which we as individual persons produce data and how data shapes our understanding of ourselves and our subjectivity and affects how we live.

By focusing on the use practices of devices and technologies such as social media, mobile devices, apps, geolocation, sensors, state governed and private information systems etc., the students will learn to investigate and analyse these practices and their consequences for the subjectivity of the user. The students will explore phenomena and technologies such as filter bubbles, echo chambers, recommender systems, quantified self, tracking, data doubles, surveillance and dataveillance.

🛠️ Assignments

ø Uncharted Data

🔥 LINKS FOR THE COURSE

Course home: https://hackmd.io/@dsub21/syllabus
Readings folder: here (please let me know if files are missing)
Groups pad: here

No materials are strictly required for the course, however it is recommended:

A HackMD account (Markdown Syntax guide: https://www.markdownguide.org/basic-syntax)
A Gitlab account (or Github, if you already have it)

💯 Exam

Exam page here

📚 Bibliography

Bibliography page here

📅 Calendar

Calendar may be subject to changes, including readings. Remember to double check.

W	DATE	SESSION/TOPICS	READINGS/ACTIVITIES
05	02 feb	1. Introductory session	☛ Iliadis, A., & Russo, F. (2016). Critical data studies: An introduction. Big Data & Society, 3(2). ☛ Goriunova, O. (2019). The Digital Subject: People as Data as Persons. Theory, Culture & Society, 36(6), 125–145. ☛ Suggested: Radiolab 'Who Am I' (podcast)
	05 feb	Workshop: Testing Mozilla hubs
06	09 feb	2. The modern subject	☛ Foucault, M. (1982). The Subject and Power. Critical Inquiry, 8(4), 777–795. (20 p.) ☛ Krasmann, S. (2017). Imagining Foucault. On the digital subject and “visual citizenship.” Foucault Studies, 10–26. (17 p.)
	12 feb	Workshop: What remains of…
07	16 feb	3. Digital identities	☛ Smith, S., & Watson, J. (2014). Virtually Me: A Toolbox about Online Self-Presentation. In A. Poletti & J. Rak (Eds.), Identity technologies: Constructing the self online. The University of Wisconsin Press. ☛ Bruns, A. (2006). Towards Produsage: Futures for User-Led Content Production. In C. Ess, F. Sudweeks, & H. Hrachovec (Eds.), Proceeding of the 5th International Conference on Cultural Attitudes towards Technology and Communication (pp. 275–284). School of Information Technology. https://eprints.qut.edu.au/4863/ ☛ Bruns, A. (2009). From Prosumer to Produser: Understanding User-Led Content Creation. Transforming Audiences 2009, London. (Slides here)
	19 feb	Workshop: Testing GIT + gitlab server	☛ Suggested: Borges. Funes, the memorious (short story)
08	23 feb	4. The quantified self	☛ Lupton, D. (2016). The quantified self. John Wiley & Sons. (~~Introduction~~ Chapter 1: Know Thyself) ☛ Hynnä, K., Lehto, M., & Paasonen, S. (2019). Affective Body Politics of Social Media. Social Media + Society, 5(4)
	26 feb	Workshop: Data (re)quest Guest: Rasmus Raspel	☛ Watch the Quantified Life (Ajana 2017) short film, if you haven't
09	02 mar	5. Biopolitical subject	☛ Cheney-Lippold, J. (2017). We Are Data: Algorithms and The Making of Our Digital Selves. New York: NYU Press. [Intro — 36 pages] ☛ Pasquinelli, M. (2015). Italian Operaismo and the Information Machine. Theory, Culture & Society, 32(3), 49–68
	05 mar	Workshop
10	09 mar	6. The digital citizen	☛ Ruppert, E. (2013). Not Just Another Database: The Transactions that Enact Young Offenders. Computational Culture, 1–13. ☛ Currie, M., Paris, B. S., Pasquetto, I., & Pierre, J. (2016). The conundrum of police officer-involved homicides: Counter-data in Los Angeles County. Big Data & Society, 3(2). ☛ Zhang, Ch. (2020, September 30). The Epistemic Production of “Non-Western Immigrants” in Denmark. The Disorder Of Things
	12 mar	Workshop: Using p5.js
11	16 mar	7. Situated subjects I: the south Guest: Gabriel Pereira	☛ Pereira, G., Bojczuk, I., & Parks, L. (2020) WhatsApp Disruptions in Brazil: A content analysis of user and news media responses, 2015-2018. Global Media and Communication. ☛ Kotliar, D. M. (2020). Data orientalism: On the algorithmic construction of the non-Western other. Theory and Society. ☛ Lewis, K. (2015). Three fallacies of digital footprints. Big Data & Society, 2(2).
	19 mar	Workshop
12	23 mar	8. The subject of surveillance capitalism	☛ Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs. (CH. 3 “The Discovery of Behavioral Surplus”) ☛ Keller, F. B., Schoch, D., Stier, S., & Yang, J. (n.d.). Political astroturﬁng across the world. 11. ☛ Clarke, R. (2019). Risks inherent in the digital surveillance economy: A research agenda. Journal of Information Technology, 34(1), 59–80.
	26 mar	Workshop
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14	06 apr	9. Situated subjects II: the alt	☛ Tuters, M. & Hagen, S. (2018). Who are (((they)))?: On Online Hate, Tasteless Transgression, and Memetic Versatility. [17 min read] ☛ [Essay] Machine Politics by Fred Turner. (2019, January 1). Harper’s Magazine. https://harpers.org/archive/2019/01/machine-politics-facebook-political-polarization/ ☛ Bechmann, A., & Nielbo, K. L. (2018). Are We Exposed to the Same “News” in the News Feed?: An empirical analysis of filter bubbles as information similarity for Danish Facebook users. Digital Journalism, 6(8), 990–1002.
	09 apr	Workshop: Feels good man
15	13 apr	10. Unruly & narrated subjects	☛ Lynch, C. R. (2020). Unruly digital subjects: Social entanglements, identity, and the politics of technological expertise. Digital Geography and Society, 1, 100001. ☛ Jacobsen, B. N. (2020). Algorithms and the narration of past selves. Information, Communication & Society, 1–16. ☛ Dourish, P., & Gómez Cruz, E. (2018). Datafication and data fiction: Narrating data and narrating with data. Big Data & Society, 5(2).
	16 apr	Workshop
16	20 apr	11. The posthuman	☛ Lury, C., & Day, S. (2019). Algorithmic Personalization as a Mode of Individuation. Theory, Culture & Society, 36(2), 17–37. ☛ Wark, S. (2019). The subject of circulation: On the digital subject’s technical individuations. Subjectivity, 12(1), 65–81. ☛ Hacking, I. (1986). Making up people.
	23 apr	Workshop: Making up people
17	27 apr	12. Situated subjects III: the organic other(s) Guest: Research Institute of Botanical Linguistics	☛ Tavares, Paulo. 2018. ‘In the Forest Ruins’. In Superhumanity: Design of the Self, edited by Nick Axel, Beatriz Colomina, Nikolaus Hirsch, Anton Vidokle, and Mark Wigley, 1st edition. New York, NY: e-flux. ☛ Shaw, Debra Benita. 2011. ‘Technonature/Culture’. In Technoculture: The Key Concepts. Oxford ; New York: Routledge. ☛ Coccia, Emanuele. 2018. ‘Prologue’. In The Life of Plants: A Metaphysics of Mixture, 1st edition. Medford, MA: Polity.
	30 apr		(no workshop)
18	04 may	13. Situated subjects IV: the technical other(s)	☛ Hayles, N. K. (2017). Unthought: The power of the cognitive nonconscious. The University of Chicago Press. (CHAPTER 1 : Nonconscious cognitions: humans and other) ☛ Parisi, Luciana. 2015. ‘Instrumental Reason, Algorithmic Capitalism’. In Alleys of Your Mind, edited by Matteo Pasquinelli. Lüneburg: meson press. ☛ Watch Karl Friston's Embodied Cognition (full paper here, if you're curious).
	07 may	Workshop	Presentations of Uncharted Data I (groups 1-5)
19	11 may	14. Final session	Presentations of Uncharted Data II (groups 6-8)

	28 May	Exam hand out	Exam dates subject to change
	04 Jun	Exam submission	Exam dates subject to change

📃 Academic regulation

Key excerpts from academic regulation:

Academic objectives

In the evaluation of the student’s performance, emphasis is placed on the extent to which the student is able to:

Knowledge:

describe and discuss theories, concepts and methods for investigating the role of data in relation to the formation of the subject
critically reflect on the relation between data and subjectivity.

Skills:

analyse and discuss the relation between data and subjectivity in general and in specific cases
communicate about the relation between data and subjectivity in general and in specific cases.

Competences:

independently plan and execute studies of data and subjectivity in specific cases.