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Deep Tech Ethics: An Approach to Teaching Social Justice in Computer Science

Published:05 March 2021Publication History

ABSTRACT

As ethical questions around the development of contemporary computer technologies have become an increasing point of public and political concern, computer science departments in universities around the world have placed renewed emphasis on tech ethics undergraduate classes as a means to educate students on the large-scale social implications of their actions. Committed to the idea that tech ethics is an essential part of the undergraduate computer science educational curriculum, at Rice University this year we piloted a redesigned version of our Ethics and Accountability in Computer Science class. This effort represents our first attempt at implementing a "deep" tech ethics approach to the course. Incorporating elements from philosophy of technology, critical media theory, and science and technology studies, we encouraged students to learn not only ethics in a "shallow" sense, examining abstract principles or values to determine right and wrong, but rather looking at a series of "deeper" questions more closely related to present issues of social justice and relying on a structural understanding of these problems to develop potential sociotechnical solutions. In this article, we report on our implementation of this redesigned approach. We describe in detail the rationale and strategy for implementing this approach, present key elements of the redesigned syllabus, and discuss final student reflections and course evaluations. To conclude, we examine course achievements, limitations, and lessons learned toward the future, particularly in regard to the number escalating social protests and issues involving Covid-19.

References

  1. Louis Althusser. 2008. On Ideology. Verso, London?; New York.Google ScholarGoogle Scholar
  2. Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016. Machine Bias. ProPublica (May 2016). Retrieved November 2, 2020 from https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing?token=H5XUYhBoyN_v2qMTsiJRtLcjOEweQC5eGoogle ScholarGoogle Scholar
  3. Richard H. Austing, Bruce H. Barnes, Della T. Bonnette, Gerald L. Engel, and Gordon Stokes. 1979. Curriculum '78: recommendations for the undergraduate program in computer science. Commun. ACM 22, 3 (March 1979), 147--166. DOI:https://doi.org/10.1145/359080.359083Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Cameron Barbrook. 1995. The Californian Ideology. Mute. Retrieved August 11, 2020 from https://www.metamute.org/editorial/articles/californian-ideologyGoogle ScholarGoogle Scholar
  5. W Lance Bennett and Steven Livingston. 2018. The disinformation order: Disruptive communication and the decline of democratic institutions. Eur. J. Commun. 33, 2 (April 2018), 122--139. DOI:https://doi.org/10.1177/0267323118760317Google ScholarGoogle Scholar
  6. Luc Boltanski and Eve Chiapello. 2005. The New Spirit of Capitalism. Verso.Google ScholarGoogle Scholar
  7. Joel Breakstone, Mark Smith, Sam Wineburg, Amie Rapaport, Jill Carle, Marshall Garland, Anna Saavedra, and Gibson Consulting. 2019. Students? Civic Online Reasoning: A National Portrait. Stanford History Education Group. Retrieved from https://stacks.stanford.edu/file/gf151tb4868/Civic%20Online%20Reasoning%20National%20Portrait.pdfGoogle ScholarGoogle Scholar
  8. danah boyd. 2017. Google and Facebook Can't Just Make Fake News Disappear. Wired. Retrieved August 6, 2020 from https://www.wired.com/2017/03/google-and-facebook-cant-just-make-fake-news-disappear/Google ScholarGoogle Scholar
  9. Gilles Deleuze. 1992. Postscript on the Societies of Control. October 59, (1992), 3--7. Retrieved March 13, 2020 from https://www.jstor.org/stable/778828Google ScholarGoogle Scholar
  10. Nicholas Diakopoulos. 2019. Automating the News: How Algorithms Are Rewriting the Media. Harvard University Press, Cambridge, Massachusetts.Google ScholarGoogle Scholar
  11. Stacy A. Doore, Casey Fiesler, Michael S. Kirkpatrick, Evan Peck, and Mehran Sahami. 2020. Assignments that Blend Ethics and Technology. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE '20), Association for Computing Machinery, New York, NY, USA, 475--476. DOI:https://doi.org/10.1145/3328778.3366994Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Casey Fiesler. 2019. Tech Ethics Curricula: A Collection of Syllabi. Medium. Retrieved August 11, 2020 from https://medium.com/@cfiesler/tech-ethics-curricula-a-collection-of-syllabi-3eedfb76be18Google ScholarGoogle Scholar
  13. Casey Fiesler, Natalie Garrett, and Nathan Beard. 2020. What Do We Teach When We Teach Tech Ethics?: A Syllabi Analysis. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, ACM, Portland OR USA, 289--295. DOI:https://doi.org/10.1145/3328778.3366825Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Rana Foroohar. 2018. Year in a Word: Techlash. Financial Times. Retrieved August 11, 2020 from https://www.ft.com/content/76578fba-fca1--11e8-ac00--57a2a826423eGoogle ScholarGoogle Scholar
  15. Michel Foucault. 1995. Discipline & Punish: The Birth of the Prison. Vintage Books, New York.Google ScholarGoogle Scholar
  16. Christian Fuchs. 2017. AirBnB and Uber: The Political Economy of Online Sharing Platforms. In Social Media: A Critical Introduction (2 edition). SAGE Publications Ltd, Thousand Oaks, CA.Google ScholarGoogle Scholar
  17. Mayo Fuster Morell. 2011. The Unethics of Sharing: Wikiwashing. Social Science Research Network, Rochester, NY. Retrieved May 13, 2019 from https://papers.ssrn.com/abstract=2842693Google ScholarGoogle Scholar
  18. Alexander R. Galloway. 2014. The Reticular Fallacy. Culture and Communication. Retrieved August 6, 2020 from http://cultureandcommunication.org/galloway/the-reticular-fallacyGoogle ScholarGoogle Scholar
  19. Will Douglas Heaven. 2020. Predictive policing algorithms are racist. They need to be dismantled. MIT Technology Review. Retrieved November 2, 2020 from https://www.technologyreview.com/2020/07/17/1005396/predictive-policing-algorithms-racist-dismantled-machine-learning-bias-criminal-justice/Google ScholarGoogle Scholar
  20. Johannes Himmelreich. 2019. Ethics of technology needs more political philosophy. Commun. ACM 63, 1 (December 2019), 33--35. DOI:https://doi.org/10.1145/3339905Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Thomas Hobbes. 2017. Leviathan (First Edition edition ed.). Penguin Classics, Harmondsworth, Meddlesex.Google ScholarGoogle Scholar
  22. Chuck Huff and C. Dianne Martin. 1995. Computing consequences: a framework for teaching ethical computing. Commun. ACM 38, 12 (December 1995), 75--84. DOI:https://doi.org/10.1145/219663.219687Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Dianne C. Martin and David H. Martin. 1990. Professional codes of conduct and computer ethics education. ACM SIGCAS Comput. Soc. 20, 2 (July 1990), 18--29. DOI:https://doi.org/10.1145/95554.95560Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Dianne Martin, Chuck Huff, Donald Gotterbarn, and Keith Miller. 1996. Curriculum guidelines for teaching the consequences of computing. In Proceedings of the symposium on Computers and the quality of life (CQL '96), Association for Computing Machinery, New York, NY, USA, 73--85. DOI:https://doi.org/10.1145/238339.238376Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Eliot Michaelson, Rachel Sterken, and Jessica Pepp. 2019. What's New About Fake News? J. Ethics Soc. Philos. 16, 2 (July 2019). DOI:https://doi.org/10.26556/jesp.v16i2.629Google ScholarGoogle Scholar
  26. Evgeny Morozov. 2014. To Save Everything, Click Here: The Folly of Technological Solutionism. PublicAffairs, New York, NY.Google ScholarGoogle Scholar
  27. Norman R. Nielsen. 1972. Social responsibility and computer education. In Proceedings of the second SIGCSE technical symposium on Education in computer science (SIGCSE '72), Association for Computing Machinery, New York, NY, USA, 90--96. DOI:https://doi.org/10.1145/800155.805011Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Cathy O'Neil. 2017. Opinion | The Ivory Tower Can't Keep Ignoring Tech. The New York Times. Retrieved July 15, 2020 from https://www.nytimes.com/2017/11/14/opinion/academia-tech-algorithms.htmlGoogle ScholarGoogle Scholar
  29. John Rawls. 1999. A Theory of Justice (Second ed.). Belknap Press: An Imprint of Harvard University Press, Cambridge, Mass.Google ScholarGoogle Scholar
  30. Rob Reich, Mehran Sahami, Jeremy M. Weinstein, and Hilary Cohen. 2020. Teaching Computer Ethics: A Deeply Multidisciplinary Approach. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE '20), Association for Computing Machinery, New York, NY, USA, 296--302. DOI:https://doi.org/10.1145/3328778.3366951Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Rashida Richardson, Jason Schultz, and Kate Crawford. 2019. Dirty Data, Bad Predictions: How Civil Rights Violations Impact Police Data, Predictive Policing Systems, and Justice. Social Science Research Network, Rochester, NY. Retrieved November 2, 2020 from https://papers.ssrn.com/abstract=3333423Google ScholarGoogle Scholar
  32. Alex Rosenblat and Luke Stark. 2016. Algorithmic Labor and Information Asymmetries: A Case Study of Uber's Drivers. Int. J. Commun. 10, (2016), 3758--3784.Google ScholarGoogle Scholar
  33. Trebor Scholz. 2015. Platform Cooperativism vs. the Sharing Economy. Medium. Retrieved August 6, 2020 from https://medium.com/@trebors/platform-cooperativism-vs-the-sharing-economy-2ea737f1b5adGoogle ScholarGoogle Scholar
  34. Trebor Scholz. 2016. Uberworked and Underpaid: How Workers Are Disrupting the Digital Economy (1 edition ed.). Polity, Cambridge, UK'; Malden, MA.Google ScholarGoogle Scholar
  35. Michael Skirpan, Nathan Beard, Srinjita Bhaduri, Casey Fiesler, and Tom Yeh. 2018. Ethics Education in Context: A Case Study of Novel Ethics Activities for the CS Classroom. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE '18), Association for Computing Machinery, New York, NY, USA, 940--945. DOI:https://doi.org/10.1145/3159450.3159573Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Alex S. Vitale. 2017. The End of Policing. Verso, London?; New York.Google ScholarGoogle Scholar
  37. Ben Wagner. 2019. Ethics As An Escape From Regulation. From "Ethics-Washing" To Ethics-Shopping? In Being Profiled. 84--89. DOI:https://doi.org/10.1515/9789048550180-016Google ScholarGoogle Scholar
  38. Jackie Wang. 2017. "This Is a Story About Nerds and Cops": PredPol and Algorithmic Policing. E-Flux 87, (December 2017). Retrieved August 6, 2020 from https://www.e-flux.com/journal/87/169043/this-is-a-story-about-nerds-and-cops-predpol-and-algorithmic-policing/Google ScholarGoogle Scholar
  39. Jackie Wang. 2018. Carceral Capitalism. Semiotext, South Pasadena, CA.Google ScholarGoogle Scholar
  40. Stephanie Wykstra. 2019. Fixing Tech's Ethics Problem Starts in the Classroom. Retrieved August 6, 2020 from https://www.thenation.com/article/archive/teaching-technology-ethics-big-data-algorithms-artificial-intelligence/Google ScholarGoogle Scholar
  41. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power (1 edition ed.). Public Affairs, New York.Google ScholarGoogle Scholar
  42. 2017 Edelman Trust Barometer. Edelman. Retrieved August 6, 2020 from https://www.edelman.com/research/2017-edelman-trust-barometerGoogle ScholarGoogle Scholar

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      cover image ACM Conferences
      SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education
      March 2021
      1454 pages
      ISBN:9781450380621
      DOI:10.1145/3408877

      Copyright © 2021 ACM

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      • Published: 5 March 2021

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