INFO 6210/COMM6211: Information, Technology, Society
Cornell Tech - INFO 6210/COMM6211
Credits: 3 hours
Helen Nissenbaum, Information Science: Cornell Tech
About the course:
This research seminar is a core requirement of the doctoral program in Information Science. It explores key theoretical
and methodological approaches underlying the study of information, technology, and society. In this semester’s iteration,
the seminar will focus on ethical, political, policy, and quality of life issues taking, primarily, philosophical and
normative perspectives, also drawing from the social sciences, including disciplines such as sociology, communications,
history, science & technology studies, and others. The course is designed to be rigorous and to prepare students to make
their own analytically and theoretically sound contributions to scholarship and research.
Readings: Weekly reading assignments will be posted on Course Canvas.
Three Key Objectives of this Course:
We will explore and evaluate the social, political, economic, cultural, and ethical dynamics that accompany technology
"on the ground" (i.e. embedded and in use). We'll sample longstanding debates as well as newly emerging issues, both to gain a
historical perspective and to see how well we have learned lessons from the past (if at all!) Although the details of particular
cases and issues are important, more important is for you to develop the theoretical grounding to think rigorously not only about
the particular cases we study but to extrapolate to other, similar ones and ultimately those that inform your own research.
We will spend a good deal of time discussing methods, methodologies, and approaches not necessarily in their own right. However, in
the articles and cases that we study, we will allow time to extract and critically analyze the approaches taken in these works. In
some instances, this will mean confronting methodological difficulties and disagreements (and the ethical entanglements that can
accompany them) posed by digital and information technologies.
We will devote attention to the professional craft of being a researcher and a member of a research community. This means working on
the skills of reading analytically, critiquing readings and your colleagues' works-in-progress constructively, communicating your
ideas effectively in writing and orally, generating good research questions and collaborations, and related skills.
All activities, and assignments are mandatory for a passing grade.
* Please access the full syllabus
through the course Canvas page for detailed instructions and deadlines for the assignments and activities.
Level-setting description of you, your methodological and theoretical orientation, your research experience and trajectory, and
your particular aims for the course. The goal of this assignment is to give you a chance to reflect on how this course fits into
your own development as a researcher, and to give me a good sense of the skills and interests you're bringing to the class.
Particpation - Ongoing
Participation is a crucial component of a seminar-style class. I expect everyone to arrive to class having thoroughly read and
engaged with the course materials and being well prepared to discuss the material. Your contributions to the class can and should
occur in our in-person meetings; in addition, we'll operate an online Forum for interaction with your colleagues, to discuss
questions, and post additional items of interest.
Citiques - Twice over the course of the semester; due before class
You'll prepare a 2-page, double-spaced critique based on the
week's readings, which you will post to the Forum for others to read. This is not only a summary, although a brief overview of key
argument might be useful. In addition, however, you should use these as opportunities to mash up themes and texts against your own
research, ideas, perspective, analysis, interests, etc. This is a similar skillset to what you'll bring to critique of your colleagues'
work, and in due course, such exercises will make your own work better. Here is a non-exhaustive list of some possible approaches:
Focus on method: How do these researchers know what they know? Do they know what they think they know? What are some other ways
of knowing about the thing they're talking about? How do these researchers operationalize and measure the concepts they are
Focus on assumptions: What assumptions underlie the research and writing? What theory of the world are these authors working
with, and what are they trying to explain? What questions don't they ask? If there are assumptions that you think are faulty or
context-dependent, what are they, and how might recognition of them change the conclusions the authors reach?
Focus on design: How might you redesign a technology, a policy, a norm, or a social structure in light of the ideas/findings in
this research? How could you assess the effects of such a redesign? What new issues might it introduce?
Focus on ethics: What ethical issues are raised by the technology under discussion? What ethical issues are raised by the research
about the technology? How might either be addressed? What approaches do the authors take (if apparent) to thinking about ethics?
Do you find their approaches sufficient?
Focus on extensions (especially to your own work): How does the research make you reflect differently on your own academic research?
Can you "remix" it with work you're doing to come up with something new? Could you apply it in some other context or generalize it
in a different field? Try articulating a mini-proposal for a project you could pursue that relates in some way to the week's topics
Things to keep in mind for critiques
"Critique" doesn't necessarily mean "critical" in a negative sense; the point is to be analytic, creative, and reasoned,
regardless of whether you love or hate something.
Your critique doesn't have to involve all the readings for a given week. You can go deep on one paper if you want.
That said, synthesis is an important research skill, and you may get more out of the assignment if you try to draw together
several of the readings.
Class Facilitaiton - Once over the course of the semester
Drawing on one of your critiques, you will also be required to serve as a facilitator of our class discussion (possibly, with
another student depending on enrollment) once during the semester. This means that you will be responsible for leading class
discussion and prepare discussion questions for your colleagues in advance. I'll provide more detail about this component at
our first meeting.
You will produce a 15-20 page (double-spaced) paper, in lieu of a final exam, that draws out a key theme from the course. I
encourage you to use this requirement as a way to further some aspect of your research agenda (e.g., as a first draft of a paper
you could submit to a conference or journal, as a way to explore some facet of your dissertation project, as a means to collect
pilot data or test out a method that's new to you, etc.). We will discuss the paper in more detail as the course progresses, but
I encourage you to begin thinking of topics early in the semester, initially toward a proposal. The research paper should be
based on independent thinking and may draw on sources from outside as well as inside class.
A key component of academic life is learning how to give constructive, generative feedback to colleagues. This is just as important
a skill as developing your own research ideas (they often go hand-in-hand!) and the goal of this assignment is to practice that
skill. You will be asked to provide feedback for two of your colleagues' research proposals, in the style of conference- or
journal-style peer review, with the aim of helping to improve their work. We'll talk more specifically about how to provide
genuinely helpful peer review before the assignment.
In the final one or two weeks of class, you'll give a 10-15 minute oral presentation about your research-paper-in-progress, in the
style of a presentation you might give at an academic conference or workshop, to be followed by 5 minutes of class feedback. (Time
allotted will depend on enrollment.) The goals of this assignment are to practice communicating about your work clearly and
succinctly, to generate useful feedback from your colleagues, AND (as important) to generate useful feedback TO your colleagues.
Students should complete required readings prior to the scheduled date and be ready to particpate in class and online discussions.
All required readings are posted on the Class Canvas. Recommended readings (for students wishing to delve deeper into particular issues)
are clearly marked.
|No assigned readings for the first session|
|Sep 11||Politics, Ethics, Values|
|Langdon Winner. |
Do Artifacts have Politics? Daedalus (1980): 121-136.
|Neil Postman. |
Five Things We Need to Know About Technological Change. Talk delivered in Denver, CO (28 March 1998).
|Alvin M. Weinberg.|
Can Technology Replace Social Engineering? Bulletin of the Atomic Scientists 22, 10 (1966): 4-8.
Bruno Latour. |
Where Are the Missing Masses? The Sociology of a Few Mundane Artifacts. In Shaping Technology/Building Society:
Studies in Sociotechnical Change (W.E. Bijker and J. Law, eds). MIT Press (1992): 225-58.
Madeleine Akrich. |
The De-Scription of Technical Objects. In Shaping Technology/Building Society: Studies in Sociotechnical Change
(W.E. Bijker and J. Law, eds). MIT Press (1992): 205-224.
(Recommended) Bryan Pfaffenberger. |
Technological Dramas. Science, Technology, & Human Values 17, 3 (1992): 282-312.
|Sep 18||Rules and Regulations|
|Lawrence Lessig. Code 2.0. Basic Books (2006), Chapter 7.|
|Roger Brownsword. |
Code, Control, and Choice: Why East is East and West is West. Legal Studies 25, 1 (2005): 1-21.
Ian R. Kerr. |
Digital Locks and the Automation of Virtue. In From
Radical Extremism to
Balanced Copyright: Canadian Copyright and
the Digital Agenda (M. Geist, ed). Irwin Law (2010): 247.
Margaret Radin. |
Regulation By Contract, Regulation By Machine. Journal of Institutional and Theoretical Economics 160, 1 (2004): 142-56.
(Recommended) Michael L. Rich. |
Should We Make Crime Impossible? Harvard Journal of Law and Public Policy 36 (2013): 795-848.
|Sep 25||Quantification and Datafication|
Dan Bouk. How Our Days Became Numbered: Risk and the Rise of the Statistical Individual. University of Chicago Press (2015). Chapter 2
Espeland, Wendy Nelson, and Mitchell L. Stevens. |
A Sociology of Quantification. European Journal of Sociology 49.03 (2008): 401-436.
William Seltzer, and Margo Anderson. |
The Dark Side of Numbers: The Role of Population Data Systems in Human Rights Abuses. Social
Research 68, 2 (2001): 481-513.
|Lisa Gitelman. |
Raw Data is an Oxymoron. Cambridge: MIT Press, 2013. Introduction
Geoffrey C. Bowker and Susan Leigh Star. Sorting Things Out: Classification and its Consequences. MIT Press (2000). Introduction and
James C. Scott. Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed. Yale University Press (1998).
[Online version] Chapter 1
(Recommended) Theodore M Porter. Trust in Numbers: The Pursuit of Objectivity in Science and Public Life. Princeton University Press
(1996). Chapters 2.3.7
(Recommended) Eubanks, Virginia. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. St. Martin's Press (2018).
(Recommended) Shay David and Trevor Pinch. |
Six Degrees of Reputation: The Use and Abuse of Online Review and Recommendation Systems.
First Monday 11, 3 (2006). [link]
|Oct 2||Risk and Responsibility|
Brian Cantwell Smith. |
Limits of Correctness in Computers. In Program Verification (T.R. Colburn et al, eds).
Springer, Dordrecht (1993): 275-293.
|Helen Nissenbaum. |
Accountability in a Computerized Society. Science and Engineering Ethics 2, 1 (1996): 25-42.
Charles Perrow. Normal Accidents: Living With High-Risk Technologies. Princeton University Press (1984). Chapter 3.
(Recommended Chapters 1,2)
M.C. Elish |
Moral Crumple Zones: Cautionary Tales in Human-Robot Interaction. Engaging Science, Technology, and Society 5
Besmira Nushi, Ece Kamar, and Eric Horvitz. |
Toward Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure.
|Nicholas Diakopoulos. |
Accountability in Algorithmic Decision Making. Communications of the ACM 59, 2 (2016): 56-62.
(Recommended) Diane Vaughan. |
Autonomy, Interdependence, and Social Control: NASA and the Space Shuttle Challenger.
Administrative Science Quarterly 35 (1990): 225-257.
|Oct 9||No Class (Yom Kippur)|
Helen Nissenbaum. Privacy in Context: Technology, Policy, and the Integrity of Social Life. Stanford University Press (2009).
|Harry Surden. |
Structural Rights in Privacy. Southern Methodist University Law Review 60 (2007): 1605.
Shoshana Zuboff. |
Big Other: Surveillance Capitalism and the Prospects of an Information Civilization. Journal of Information
Technology 30, 1 (2015): 75-89.
Oscar Gandy. |
Coming to Terms with the Panoptic Sort. In, Computing, Surveillance and Privacy (eds.) David Lyon and Elia Zureik.
Minneapolis: University of Minnesota Press (1994)
(Recommended) Oscar Gandy. The Panoptic Sort: A Political Economy of Personal Information. Westview Press, Boulder, Colo. 1993
(Recommended) Julie E. Cohen. Configuring the Networked Self: Law, Code, and the Play of Everyday Practice. Yale University Press (2012).
(Recommended) Khiara Bridges. The Poverty of Privacy Rights. Stanford: Stanford University Press (2017).
|Oct 23||Accountability, Transparency, Autonomy|
|Danielle K Citron. |
Technological Due Process. Washington University Law Review 85 (2007): 1249.
Jenna Burrell. |
How the Machine ‘Thinks’: Understanding Opacity in Machine Learning Algorithms. Big Data & Society 3, 1 (2016):
|Zachary C. Lipton. |
The Mythos of Model Interpretability. ArXiv preprint (2016).
|Jamie Luguri and Lior Strahilevitz. |
Shining a Light on Dark Patterns. SSRN preprint (2019). [link]
|Arunesh Mathur et al. |
Dark Patterns at Scale: Findings from a Crawl of 11k Shopping Websites. ArXiv preprint (2019).
Karen Yeung. |
‘Hypernudge’: Big Data as a Mode of Regulation by Design. Information, Communication & Society 20, 1 (2017): 118-136.
Lucas D. Introna. |
Algorithms, Governance, and Governmentality: On Governing Academic Writing. Science, Technology, & Human Values 41,
1 (2016): 17-49.
(Recommended) Daniel Susser, Beate Roessler, Helen Nissenbaum. |
Online Manipulation: Hidden Influences in a Digital World.
[Draft under review. September 2019.]
|(Recommended) Jonathan Zittrain. The Future of the Internet and How to Stop It. Yale University Press (2008): Ch. 5.|
|Oct 30||Bias, Fairness, Discrimination, Justice|
|Cases: physical world, criminal justice, advertising, language, web search, housing|
Rachel N. Weber. |
anufacturing Gender in Commercial and Military Cockpit Design. Science, Technology, & Human Values 22, 2 (1997):
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner. |
Machine Bias: Risk Assessments in Criminal Sentencing. ProPublica
(23 May 2016). [link].
Jeff Larson, Surya Mattu, Lauren Kirchner, and Julia Angwin. |
How We Analyzed the COMPAS Recidivism Algorithm. ProPublica (23 May 2016).
Sam Corbett-Davies, Emma Pierson, Avi Feller, and Sharad Goel. |
A Computer Program Used for Bail and Sentencing Decisions
Was Labeled Biased Against Blacks. It’s Actually Not That Clear. Washington Post (17 October 2016). [link].
Latanya Sweeney. |
Discrimination in Online Ad Delivery. Communications of the ACM 56, 5 (2013): 44-54.
Joy Buolamini and Timnit Gebru. |
Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification.
Conference on Fairness, Accountability, and Transparency. Proceedings of Machine Learning Research, 81:1-15, 2018
Tolga Bolukbasi, Kai-Wei Chang, James Zou, Venkatesh Saligrama, and Adam Kalai. |
Man is to Computer Programmer as Woman is to Homemaker?
Debiasing Word Embeddings. ArXiv preprint (2016). [link]
|Safiya Umoja Noble. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press (2018). Chapter 2|
(Recommended) Lucas D. Introna and Helen Nissenbaum. |
Shaping the Web: Why the Politics of Search Engines Matters. The Information
Society 16, 3 (2000): 169-185.
(Recommended) Aylin Caliskan-Islam, Joanna J. Bryson, and Arvind Narayanan. |
Semantics Derived Automatically From Language Corpora
Necessarily Contain Human Biases. ArXiv preprint (2016). [link]
|Nov 6||Bias, Fairness, Discrimination, Justice: Analysis|
Batya Friedman and Helen Nissenbaum. |
Bias in Computer Systems. ACM Transactions on Information Systems (TOIS)
14, 3 (1996): 330-347.
|Solon Barocas and Andrew D. Selbst. |
Big Data’s Disparate Impact. California Law Review 104 (2016): 671.
Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan. |
Inherent Trade-Offs in the Fair Determination of Risk Scores.
ArXiv Preprint (2016). [link]
Christian Sandvig, Kevin Hamilton, Karrie Karahalios, and Cedric Langbort. |
Auditing Algorithms: Research Methods for Detecting
Discrimination on Internet Platforms. ICA Preconference on Data and Discrimination: Converting Critical Concerns into Productive
Inquiry, 2014 May 22.
|Nov 13||Digital Labor and Digital Workplace|
|Harry Braverman. Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century. Monthly Review Press (1974).|
Stephen Barley. |
Technology as an Occasion for Structuring: Evidence from Observations of CT Scanners and the Social Order of Radiology
Departments. Administrative Science Quarterly 31 (1986): 78-108.
|Shoshana Zuboff. In the Age of the Smart Machine: The Future of Work and Power. Basic Books (1988).|
|Ryan Calo and Alex Rosenblat. |
The Taking Economy: Uber, Information, and Power. Columbia Law Review 117 (2017): 1623.
|Karen E.C. Levy. |
The Contexts of Control: Information, Power, and Truck-Driving Work. The Information Society 31 (2015): 160-174.
|Trebor Scholz. |
Market Ideology and the Myths of Web 2.0. First Monday 13, 3 (2008).
|Jonathan Zittrain. |
Minds for Sale. YouTube video (29 November 2009). [link]
(Recommended) See other articles in First Monday 13, 3 (2008) Special Issue. https://journals.uic.edu/ojs/index.php/fm/issue/view/263/showToc
(Recommended) Yochai Benkler. The Wealth of Networks: How Social Production Transforms Markets and Freedom.
Yale University Press (2006).
Phil Agre. |
Towards a Critical Technical Practice: Lessons Learned in Trying to Transform AI. In Bridging the Great Divide: Social
Science, Technical Systems, and Cooperative Work (G. Bowker et al, eds). Erlbaum (1997).
|Nick Bostrom. Superintelligence: Paths, Dangers, Strategies. Oxford University Press (2014).|
Peter Stone et al. |
Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence:
Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016. [link]
Karen Yeung, Andrew Howes, and Ganna Pogrebna. |
AI Governance by Human Rights-Centred Design, Deliberation, and Oversight: An End to
Ethics Washing. In The Oxford Handbook of AI Ethics (M Dubber & F Pasquale, eds). Oxford University Press (2019).
|Nov 27||Thanksgiving break|
|Dec 4||Project Presentations|