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Public Computing Intellectuals in the Age of AI Crisis

Online AM: 04 November 2024 Publication History

Abstract

The belief that AI technology is on the cusp of causing a generalized social crisis became a popular one in 2023. While there was no doubt an element of hype and exaggeration to some of these accounts, they do reflect the fact that there are troubling ramifications to this technology stack. This conjunction of shared concerns about social, political, and personal futures presaged by current developments in artificial intelligence presents the academic discipline of computing with a renewed opportunity for self-examination and reconfiguration. This position paper endeavors to do so in four sections. The first explores what is at stake for computing in the narrative of an AI crisis. The second articulates possible educational responses to this crisis and advocates for a broader analytic focus on power relations. The third section presents a novel characterization of academic computing’s field of practice, one which includes not only the discipline’s usual instrumental forms of practice but reflexive practice as well. This reflexive dimension integrates both the critical and public functions of the discipline as equal intellectual partners and a necessary component of any contemporary academic field. The final section will advocate for a conceptual archetype–the Public Computer Intellectual and its less conspicuous but still essential cousin, the Almost-Public Computer Intellectual–as a way of practically imagining the expanded possibilities of academic practice in our discipline, one that provides both self-critique and an outward-facing orientation towards the public good. It will argue that the computer education research community can play a vital role in this regard. Recommendations for pedagogical change within computing to develop more reflexive capabilities are also provided.

References

[1]
Rediet Abebe, et al. 2020. Roles for computing in social change. In Proceedings of the 2020 conference on fairness, accountability, and transparency, 252-260.
[2]
Daron Acemoglu and Pascual Restrepo. 2020. The wrong kind of AI? Artificial intelligence and the future of labour demand. Cambridge Journal of Regions, Economy and Society, 13, 1, 25-35.
[3]
Daron Acemoglu and Pascual Restrepo. 2022. Tasks, automation, and the rise in us wage inequality. Econometrica 90, 5, 1973-2016.
[4]
ACM. 2018. ACM Code of Ethics and Professional Conduct. https://www.acm.org/code-of-ethics.
[5]
Barbara Adam, et al. Handbook of public sociology. Rowman & Littlefield Publishers, 2009.
[6]
David H Autor. 2015. Why are there still so many jobs? The history and future of workplace automation. Journal of economic perspectives 29, 3, 3-30. https://doi.org/10.1257/jep.29.3.3
[7]
David H Autor. 2022. The labor market impacts of technological change: From unbridled enthusiasm to qualified optimism to vast uncertainty (No. w30074). National Bureau of Economic Research.
[8]
David H Autor, et al. 2020. The fall of the labor share and the rise of superstar firms. The Quarterly Journal of Economics 135, 2, 645-709.
[9]
Alain Badiou. 2017. The True Life. Polity Press.
[10]
Chelsea Barabas, Colin Doyle, J. B. Rubinovitz, and Karthik Dinakar. 2020. Studying up: reorienting the study of algorithmic fairness around issues of power. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAT* '20). Association for Computing Machinery, New York, NY, USA, 167–176.
[11]
Richard Barbrook. 2007. Imaginary Futures: From Thinking Machines to the Global Village. Pluto Press.
[12]
Richard Barbrook and Andy Cameron. 1996. The californian ideology. Science as culture, 6, 1, 44-72.
[13]
Ulrich Beck. 1986. Risk Society: Towards a New Modernity. Trans. Mark Ritter. Sage, London.
[14]
Ruha Benjamin. 2019. Race after technology: Abolitionist tools for the new Jim code. John Wiley & Sons.
[15]
Elettra Bietti. 2022. From Ethics Washing to Ethics Bashing: A Moral Philosophy View on Tech Ethics. Journal of Social Computing, 2, 3, 266–283. https://doi.org/10.23919/JSC.2021.0031
[16]
Abeba Birhane. 2021. Algorithmic injustice: a relational ethics approach. Patterns, 2(2).
[17]
Abeba Birhane, et al. 2022. The values encoded in machine learning research. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, 173-184.
[18]
Abeba Birhane, et al. 2022. The forgotten margins of AI ethics. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, 948-958.
[19]
Su Lin Blodgett, et al, 2020. Language (technology) is power: A critical survey of "bias" in nlp. arXiv preprint arXiv:2005.14050.
[20]
Emile Bojesen and Judith Suissa. 2019. Minimal utopianism in the classroom. Educational Philosophy and Theory, 51, 3, 286-297.
[21]
Pierre Bourdieu. 2000. For a scholarship with commitment. Profession, 40-45.
[22]
Benedetta Brevini. 2020. Black boxes, not green: Mythologizing artificial intelligence and omitting the environment. Big Data & Society, 7, 2, 2053951720935141.
[23]
Craig Browne. 2017. Critical Social Theory. Sage Publications.
[24]
Erik Brynjolfsson and Andrew McAfee. 2014. The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & Company.
[25]
Joy Buolamwini and Timnit Gebru. 2018. Gender shades: Intersectional accuracy disparities in commercial gender classification. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 77-91. PMLR.
[26]
Joy Buolamwini. 2023. Unmasking AI: my mission to protect what is human in a world of machines. Random House.
[27]
Michael Burawoy. 2005. For public sociology. American sociological review, 70, 1, 4-28.
[28]
Judith Butler. 2022. The Public Futures of the Humanities. Daedalus, 151, 3, 40-53.
[29]
David E. Campbell. 2019. What social scientists have learned about civic education: A review of the literature. Peabody Journal of Education, 94, 1, pp.32-47.
[30]
Government of Canada. 2023. The Artificial Intelligence and Data Act (AIDA). https://ised-isde.canada.ca/site/innovation-better-canada/en/artificial-intelligence-and-data-act-aida-companion-document
[31]
Center for AI Safety. 2023. Statement of AI Risk. https://www.safe.ai/statement-on-ai-risk
[32]
Dubravka Cecez-Kecmanovic. 2011. Doing critical information systems research–arguments for a critical research methodology. European Journal of Information Systems, 20, 4, 440-455.
[33]
Paul Ceruzzi. 2003. A history of modern computing. MIT Press.
[34]
Wai Fong Chua. 1986. Radical developments in accounting thought. Accounting review, 61, 4, 601-632.
[35]
Wolfie Christl. 2023. Surveillance and the Algorithmic Control in the Call Center. Cracked Labs. https://crackedlabs.org/en/data-work
[36]
Maria Christoforaki and Oya Beyan. 2022. AI ethics—a bird’s eye view. Applied Sciences 12, 9, 4130.
[37]
Dan Clawson, ed. 2007.  Public sociology: Fifteen eminent sociologists debate politics and the profession in the twenty-first century. Univ of California Press.
[38]
Mark Coeckelbergh. 2022. The political philosophy of AI: an introduction. John Wiley & Sons.
[39]
Randy Connolly. 2011. Beyond good and evil impacts: rethinking the social issues components in our computing curricula. In Proceedings of the 16th annual joint conference on Innovation and technology in computer science education, 228-232. https://doi.org/10.1145/1999747.1999812
[40]
Randy Connolly. 2020. Why computing belongs within the social sciences.” Communications of the ACM, 63, 8, 54-59. https://doi.org/10.1145/3383444.
[41]
Randy Connolly. 2023. From ethics to politics: changing approaches to AI education. Handbook of Critical Studies of Artificial Intelligence. Ed. Simon Lindgren. Edward Elgar Publishing.
[42]
Randy Connolly. Submitted. Ethical Principles, the Social Good, or Citizenship? Educating for Responsible Computing. ACM Journal on Responsible Computing.
[43]
Rodrigo Cordero. 2017. Crisis and critique: On the fragile foundations of social life. London: Routledge.
[44]
Carmen Correa and Carlos Larrinaga. 2015. Engagement research in social and environmental accounting. Sustainability Accounting, Management and Policy Journal, 6, 1, pp.5-28.
[45]
Kate Crawford. 2021. The atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.
[46]
Daniel Crevier. 1993. AI: The Tumultuous History of the Search for Artificial Intelligence. Basic Books.
[47]
John Danaher. 2019. Automation and utopia: Human flourishing in a world without work. Harvard University Press.
[48]
Cécile Deer. 2008. Doxa. Pierre Bourdieu: key concepts. Michael Grenfell, Ed. Routledge.
[49]
Patrick J. Deneen. 2016. The Public Intellectual as Teacher and Students as Public. Public Intellectuals in the Global Arena: Professors or Pundits? Ed. Michael C. Desch. University of Notre Dame Press.
[50]
Jean-Phillippe Deranty and Thomas Corbin. 2022. Artificial intelligence and work: a critical review of recent research from the social sciences. AI & SOCIETY, 29, pp.1-17.
[51]
Advait Deshpande, et al. 2021. Improving Working Conditions Using Artificial Intelligence: Study Requested by the AIDA Committee. European Parliament.
[52]
Virginia Dignum. 2020. AI is multidisciplinary. AI Matters, 5, 4, 18-21.
[53]
Carl DiSalvo, et al. 2010. HCI, communities and politics. In CHI'10 Extended Abstracts on Human Factors in Computing Systems, 3151-3154.
[54]
Cory Doctorow. 2023. The Internet Con: How To Seize the Means of Computation. Verso Books.
[55]
Devdatt Dubhashi. 2022. Can universities combat the 'wrong kind of AI'? Communications of the ACM, 65, 12, 24-26.
[56]
Charles Dunlop and Rob Kling, ed. 1991. Computerization and controversy: Value conflicts and social choices. Academic Press, Inc.
[57]
Josh Dzieza, 2020. How hard will the robots make us work? The Verge. https://www.theverge.com/2020/2/27/21155254/automation-robots-unemployment-jobs-vs-human-google-amazon
[58]
Ron Eglash, et al. 2021. Counter-hegemonic Computing: Toward Computer Science Education for Value Generation and Emancipation. ACM Transactions on Computing Education, 21, 4. https://doi.org/10.1145/3449024
[59]
Anthony Elliot. 2009. Contemporary Social Theory: An Introduction. Routledge.
[60]
M. David Ermann et al, eds., 1990. Computers, Ethics, & Society. Oxford University Press, Inc.
[61]
Ekkehard Ernst. 2022. The AI trilemma: Saving the planet without ruining our jobs. Frontiers in Artificial Intelligence, 5, 886561.
[62]
Virginia Eubanks. 2018. Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin's Press.
[63]
European Parliament. 2024. EU AI Act. https://artificialintelligenceact.eu/the-act/.
[64]
Andrew Feenberg. 1991. Critical Theory of Technology. Oxford University Press.
[65]
José Vida Fernández. 2023. The Risk of Digitalization: Transforming Government into a Digital Leviathan. Indiana Journal of Global Legal Studies, 30, 1, 3-13.
[66]
Casey Fiesler, Natalie Garrett, and Nathan Beard. 2020. What Do We Teach When We Teach Tech Ethics? A Syllabi Analysis. Proceedings of the 51st ACM Technical Symposium on Computer Science Education. Association for Computing Machinery, New York, NY, USA, 289–295.
[67]
Luciano Floridi. 2019. Translating principles into practices of digital ethics: Five risks of being unethical. Philosophy & Technology, 32, 2, 185-193.
[68]
Morgan Frank, et al. 2019. Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences, 116, 14, 6531-6539.
[69]
Nancy Fraser and Rahel Jaeggi. 2018. Capitalism: A conversation in critical theory. John Wiley & Sons.
[70]
Carl Benedikt Frey and Michael A. Osborne. 2017. The future of employment: How susceptible are jobs to computerisation?. Technological forecasting and social change 114, 254-280.
[71]
Christian Fuchs. 2021. Foundations of Critical Theory. Routledge.
[72]
Eugene Gan. 2023. The looming artificial intelligence crisis. Crisismagazine.com (Jan 24, 2023). https://crisismagazine.com/opinion/the-looming-artificial-intelligence-crisis
[73]
Seeta Peña Gangadharan and Jędrzej Niklas Gangadharan. 2019. Decentering technology in discourse on discrimination. Information, Communication & Society, 22, 7, 882–899. https://doi.org/10.1080/1369118X.2019.1593484
[74]
Timnit Gebru. 2022. Effective Altruism Is Pushing a Dangerous Brand of ‘AI Safety’. Wired. https://www.wired.com/story/effective-altruism-artificial-intelligence-sam-bankman-fried/
[75]
Katrina Geddes. 2019. Meet your new overlords: How digital platforms develop and sustain technofeudalism. Columbia Journal of Law & the Arts, 43, p.455.
[76]
Anthony Giddens. 1990. The Consequences of Modernity. Stanford University Press.
[77]
Henry Armand Giroux. 2019. Public Scholarship, Public Intellectuals, and the Role of Higher Education in a Time of Crisis. The Oxford Handbook of Methods for Public Scholarship, Oxford University Press.
[78]
Henry Armand Giroux. 2004. Cultural studies, public pedagogy, and the responsibility of intellectuals. Communication and critical/cultural studies, 1, 1, 59-79.
[79]
Ben Green. 2020. Data Science as Political Action: Grounding Data Science in a Politics of Justice. Journal of Social Computing, 2, 3, 249–265. https://doi.org/10.23919/jsc.2021.0029
[80]
Egon G. Guba and Yvonna S. Lincoln. 1994. Competing paradigms in qualitative research. Handbook of qualitative research, 2, 163-194, 105-117.
[81]
Mark Guzdial. 2020. Talking about race in CS education. Communications of the ACM 64, 1, 10–11. https://doi.org/10.1145/3433921
[82]
Robert Hassan. 2020. The Condition of Digitality: A Post-Modern Marxism for the Practice of Digital Life. Pp. 1–11. London: University of Westminster Press.
[83]
Karen Hao and Nadine Freischlad. 2022. The gig workers fighting back against the algorithms. MIT Technology Review. https://www.technologyreview.com/2022/04/21/1050381/the-gig-workers-fighting-back-against-the-algorithms/.
[84]
Karen Hao and Andrea Paola Hernández. 2022. How the AI industry profits from catastrophe. MIT Technology Review. https://www.technologyreview.com/2022/04/20/1050392/ai-industry-appen-scale-data-labels/.
[85]
Jan-Christoph Heilinger. 2022. The ethics of AI ethics. A constructive critique. Philosophy & Technology, 35, 3, 61.
[86]
Eckhard Hein. 2012. The macroeconomics of finance-dominated capitalism and its crisis. Edward Elgar Publishing.
[87]
Natali Helberger. 2020. The Political Power of Platforms: How Current Attempts to Regulate Misinformation Amplify Opinion Power. Digital Journalism, 8, 6, 842–854. https://doi.org/10.1080/21670811.2020.1773888.
[88]
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey Gritsenko, Diederik P. Kingma et al. 2023. Imagen video: High definition video generation with diffusion models. arXiv preprint arXiv:2210.02303.
[89]
Qingqing Huang, Daniel S. Park, Tao Wang, Timo I. Denk, Andy Ly, Nanxin Chen, Zhengdong Zhang et al. 2023. Nois58music: Text-conditioned music generation with diffusion models. arXiv preprint arXiv:2302.03917.
[90]
Leah Hunt-Hendrix and Astra Taylor. 2024. Solidarity: The Past, Present, and Future of a World-Changing Idea. Pantheon.
[91]
Marco Iansiti and Karim R. Lakhani. 2020. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Harvard Business Review Press
[92]
Malte Frøslee Ibsen. 2019. The populist conjuncture: Legitimation crisis in the age of globalized capitalism. Political Studies, 67, 3, 795-811.
[93]
Ole Sejer Iversen, Rachel Charlotte Smith, and Christian Dindler. 2018. From computational thinking to computational empowerment: a 21st century PD agenda. In Proceedings of the 15th Participatory Design Conference: Full Papers - Volume 1 (PDC '18). 1–11. https://doi.org/10.1145/3210586.3210592
[94]
Russell Jacoby. 1987. The last intellectuals: American culture in the age of academe. Basic Books.
[95]
Anna Jobin, Marcello Ienca, and Effy Vayena. 2019. The global landscape of AI ethics guidelines. Nature machine intelligence, 1, 9, 389-399.
[96]
Johnson, D.G. 1985. Computer Ethics. Englewood Cliffs, New Jersey.
[97]
Stephanie Jones and Natalie Araujo Melo. 2021. We tell these stories to survive: Towards abolition in computer science education. Canadian Journal of Science, Mathematics and Technology Education, 21, 2, 290-308.
[98]
Natascha Just and Michael Latzer. 2017. Governance by algorithms: reality construction by algorithmic selection on the Internet. Media, culture & society 39, 2, 238-258. https://doi.org/10.1177/0163443716643157.
[99]
Pratyusha Kalluri, 2020. Don’t ask if artificial intelligence is good or fair, ask how it shifts power. Nature 583.7815: 169-169.
[100]
Sayash Kapoor and Arvind Narayanan. 2023. A misleading open letter about sci-fi AI dangers ignores the real risks. (Mar 23, 2023). https://www.aisnakeoil.com/p/a-misleading-open-letter-about-sci
[101]
Christian Katzenbach and Lena Ulbricht. 2019. Algorithmic governance. Internet Policy Review, 8, 4, 1-18.
[102]
Davinder Kaur, Suleyman Uslu, Kaley J. Rittichier, and Arjan Durresi. 2022. Trustworthy artificial intelligence: a review. ACM Computing Surveys (CSUR) 55, 2, 1-38. https://doi.org/10.1145/3491209.
[103]
Avril Keating. 2009. Educating Europe's citizens: moving from national to post-national models of educating for European citizenship. Citizenship Studies, 13, 2, 135-151.
[104]
Os Keyes, et al. 2019. Human-computer insurrection: Notes on an anarchist HCI. In Proceedings of the 2019 CHI conference on human factors in computing systems, 1-13.
[105]
Jennifer J. Kish-Gephart, David A. Harrison, and Linda Klebe Treviño. 2010. Bad apples, bad cases, and bad barrels: meta-analytic evidence about sources of unethical decisions at work. Journal of applied psychology 95, 1.
[106]
Amy J. Ko, et al, 2024. Critically Conscious Computing: Methods for Secondary Education. https://criticallyconsciouscomputing.org/.
[107]
Nima Kordzadeh & Maryam Ghasemaghaei. 2022. Algorithmic bias: review, synthesis, and future research directions, European Journal of Information Systems, 31, 3, 388-409.
[108]
Micahel Lachney and Aman Yadav. 2023. From endpoints to trading zones: Multi-directional exchange for computational empowerment in computer science education. International Journal of Child-Computer Interaction, 37, p.100591.
[109]
Michael Lachney, Jean Ryoo, and Rafi Santo. 2021. Introduction to the Special Section on Justice-Centered Computing Education, Part 1. ACM Transactions on Computer Education 21, 4 (December 2021), 15 pages.
[110]
Stefan Larsson. 2019. The socio-legal relevance of artificial intelligence. Droit et société, 103, 573-593. https://doi.org/10.3917/drs1.103.0573
[111]
Ashlin Lee, et al. 2023. Barriers to regulating AI: critical observations from a fractured field. Handbook of Critical Studies of Artificial Intelligence. Ed. Simon Lindgren. Edward Elgar Publishing.
[112]
Clifford H. Lee and Elisabeth Soep. 2016. None But Ourselves Can Free Our Minds: Critical Computational Literacy as a Pedagogy of Resistance. Equity & Excellence in Education, 49, 4, 480–492. https://doi.org/10.1080/10665684.2016.1227157.
[113]
Bruno Lepri, et al. 2017. Fair, Transparent, and Accountable Algorithmic Decision-making Processes. Philosophy & Technology, 31, 4, 611–627. https://doi.org/10.1007/S13347-017-0279-X
[114]
Alex Lin. 2015. Citizenship education in American schools and its role in developing civic engagement: a review of the research. Educational Review, 67, 1, 35–63. https://doi.org/10.1080/00131911.2013.813440.
[115]
Simon Lindgren. 2024. Critical Theory of AI. Polity Press.
[116]
Wesley Longhofer and Daniel Winchester. 2016. Social theory re-wired: New connections to classical and contemporary perspectives. Routledge.
[117]
Tia C. Madkins, Nicol Howard, and Natalie Freed. 2020. Engaging Equity Pedagogies in Computer Science Learning Environments. Journal of Computer Science Integration, 3, 1–27.
[118]
Dianne C. Martin. 1995. ENIAC: press conference that shook the world. IEEE Technology and Society Magazine, 14, 4, 3-10.
[119]
Gary Marcus. 2023. Why are we letting the AI Crisis just happen? atlantic.com (Mar. 13, 2023). https://www.theatlantic.com/technology/archive/2023/03/ai-chatbots-large-language-model-misinformation/673376/
[120]
Karl Maton. 2008. Habitus. Pierre Bourdieu: key concepts. Michael Grenfell, Ed. Routledge.
[121]
Andrew McNamara, Justin Smith, and Emerson Murphy-Hill. 2018. Does ACM’s code of ethics change ethical decision making in software development?. In Proceedings of the 2018 26th ACM joint meeting on european software engineering conference and symposium on the foundations of software engineering (pp. 729-733).
[122]
Dan McQuillan. 2022. Resisting AI: an anti-fascist approach to artificial intelligence. Policy Press.
[123]
Ulises A. Mejias and Nick Couldry. 2024. Data Grab: The New Colonialism of Big Tech and How to Fight Back. University of Chicago Press.
[124]
Miceli Miceli, et al. 2022. Studying up machine learning data: Why talk about bias when we mean power?. Proceedings of the ACM on Human-Computer Interaction, 6, 1-14.
[125]
Paul Mihailidis. 2018. Civic media literacies: re-Imagining engagement for civic intentionality. Learning, Media Technology, 43, 2, 152–164. https://doi.org/10.1080/17439884.2018.1428623.
[126]
Brian Milstein. 2014. Thinking politically about crisis: A pragmatist perspective. European Journal of Political Theory, 14, 2, 141–160. https://doi.org/10.1177/1474885114546138
[127]
Brent Mittelstadt. 2019. Principles alone cannot guarantee ethical AI. Nature machine intelligence, 1, 11, 501-507.
[128]
Brent Mittelstadt, et al. 2016. The ethics of algorithms: Mapping the debate. Big Data & Society 3, 2, 2053951716679679. https://doi.org/10.1177/2053951716679679
[129]
Jared Moore, 2019. AI for not bad. Frontiers in Big Data, 2, p.32.
[130]
Jared Moore. 2020. Towards a more representative politics in the ethics of computer science. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAT* '20). Association for Computing Machinery, New York, NY, USA, 414–424.
[131]
Evgeny Morozov. 2022. Critique of techno-feudal reason. New Left Review, 133, 89-126.
[132]
Luke Munn. 2023. The uselessness of AI ethics. AI and Ethics, 3, 3, 869-877.
[133]
Mariana Mazzucato. 2015. The Entrepreneurial State. Public Affairs.
[134]
Luis Felipe R.Murillo, Caitlin Wylie, and Phil Bourne, 2023. Critical data ethics pedagogies: Three (non-rival) approaches. Big Data & Society, 10, 2: 20539517231203666.
[135]
Michael D. Myers and Heinz K. Klein. 2011. A set of principles for conducting critical research in information systems. MIS quarterly, 17-36.
[136]
Safiya Umoja Noble. 2018. Algorithms of oppression. New York University Press.
[137]
Cathy O'Neil. 2017. Weapons of math destruction: How big data increases inequality and threatens democracy. Crown.
[138]
Guy Paltieli. 2023. Re-imagining democracy: AI’s challenge to political theory. Handbook of Critical Studies of Artificial Intelligence. Ed. Simon Lindgren. Edward Elgar Publishing.
[139]
Elise Paradis et al. 2020. Critical theory: broadening our thinking to explore the structural factors at play in health professions education. Academic Medicine, 95, 6, 842-845.
[140]
Billy Perrigo. 2023. OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic. Time Magazine. https://time.com/6247678/openai-chatgpt-kenya-workers/
[141]
Whitney Phillips and Ryan M. Milner. 2021. You are here: A field guide for navigating polarized speech, conspiracy theories, and our polluted media landscape. MIT Press.
[142]
Frances Fox Piven. 2007. From public sociology to politicized sociologist. Public sociology: Fifteen eminent sociologists debate politics and the profession in the twenty-first century. Dan Clawson et al, Eds. University of California Press. 158-166.
[143]
Gianfranco Polizzi. 2020. Information literacy in the digital age: why critical digital literacy matters for democracy. Informed Societies, Stephane Goldstein (Ed). Facet Publishing.
[144]
Richard A. Posner. 2001. Public intellectuals: A study of decline. Harvard University Press.
[145]
Veronica Rivera and Norman Su. 2024. Teaching Ethics & Activism in a Human-Computer Interaction Professional Master's Program. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1, 1140-1146.
[146]
Emily Robinson. 2023. The Politics of Unpolitics. The Political Quarterly, 94, 2, 306-313.
[147]
Monique S. Ross. 2023. Let’s have that Conversation: How Limited Epistemological Beliefs Exacerbates Inequities and will Continue to be a Barrier to Broadening Participation. ACM Transactions on Computing Education, 23, 2. https://doi.org/10.1145/3578270
[148]
Edward W. Said. 2004. The Return to Philology. Humanism and democratic criticism. Columbia University Press.
[149]
Edward W. Said. 2012. Representations of the Intellectual. Vintage.
[150]
Jeffrey Saltz, et al. 2019. Integrating ethics within machine learning courses. ACM Transactions on Computing Education (TOCE) 19, 4, 1-26.
[151]
Sebastin Santy, Anku Rani and Monojit Choudhury. 2021. Use of formal ethical reviews in NLP literature: Historical trends and current practices. arXiv preprint arXiv:2106.01105.
[152]
Faridun Sattarov. 2019. Power and technology: A philosophical and ethical analysis. Rowman & Littlefield.
[153]
Kimberly A. Scott, Kimberly Sheridan, and Kevin Clark. 2014. Culturally responsive computing: A theory revisited. Learning, Media and Technology, 40, 412–436.
[154]
Tony Schirato. and Mary Roberts. 2020. Bourdieu: A critical introduction. Routledge.
[155]
John Schwarzmantel. 2014. The Routledge guidebook to Gramsci's prison notebooks. Routledge.
[156]
Andrew D. Selbst, et al. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68.
[157]
Niral Shah and Aman Yadav. 2023. Racial justice amidst the dangers of computing creep: A dialogue. TechTrends, 67, 3, 467-474.
[158]
Judith Simon, Pak Hang Wong, and Gernot Rieder. 2020. Algorithmic bias and the Value Sensitive Design approach. Internet Policy Review, 9, 4. https://doi.org/10.14763/2020.4.1534
[159]
Josh Simons. 2023. Algorithms for the People: Democracy in the Age of AI. Princeton University Press.
[160]
Nathalie A. Smuha. 2019. The EU approach to ethics guidelines for trustworthy artificial intelligence. Computer Law Review International, 20, 4, 97-106.
[161]
Thomas Sowell. 2012. Intellectuals and society. Hachette UK.
[162]
Bernd Carsten Stahl, Job Timmermans, and Brent Daniel Mittelstadt. 2016. The Ethics of Computing: A Survey of the Computing-Oriented Literature. ACM Computer Survey, 48, 4, 1-38.
[163]
Miriam Sturdee, et al. 2021. Consequences, schmonsequences! Considering the future as part of publication and peer review in computing research. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, 1-4.
[164]
Mustafa Suleyman and Michael Bhaskar. 2023. The Coming Wave: Technology, Power, and the Twenty-first Century's Greatest Dilemma. Crown Publishing.
[165]
Cass R. Sunstein. 2001. Republic. com. Princeton University Press.
[166]
Richard Susskind and Daniel Susskind. 2015. The future of the professions: How technology will transform the work of human experts. Oxford University Press, USA.
[167]
Mike Tissenbaum, Josh Sheldon, and Hal Abelson. 2019. Viewpoint from computational thinking to computational action. Communications of the ACM, 62, 3, 34–36. https://doi.org/10.1145/3265747.
[168]
Émile P. Torres. 2021. The Dangerous Ideas of “Longtermism” and “Existential Risk”. Current Affairs. https://www.currentaffairs.org/news/2021/07/the-dangerous-ideas-of-longtermism-and-existential-risk
[169]
Alberto Toscano. 2023. Late Fascism: Race, Capitalism and the Politics of Crisis. Verso Books.
[170]
Laura D. Tyson and John Zysman. 2022. Automation, AI & Work. Daedalus, 151, 2, 256-271.
[171]
Sepehr Vakil. 2018. Ethics, identity, and political vision: Toward a justice-centered approach to equity in computer science education. Harvard Educational Review, 88, 1, 26-52.
[172]
Ville Vakkuri, et al, 2020. "This is just a prototype": How ethics are ignored in software startup-like environments. International Conference on Agile Software Development. Cham: Springer International Publishing, 2020.
[173]
Chris Vallance. 2023. Elon Musk among experts urging a halt to AI training. bbc.com. (Mar. 30, 2023). https://www.bbc.com/news/technology-65110030
[174]
Yaris Varoufakis. 2024. Technofeudalism: What killed capitalism. Melville House.
[175]
Pieter Verdegem. 2023. Critical AI studies meets critical political economy. Handbook of Critical Studies of Artificial Intelligence. Ed. Simon Lindgren. Edward Elgar Publishing.
[176]
James Vincent. 2023. Top AI researchers and CEOs warn against ‘risk of extinction’ in 22-word statement. theverge.com. (May 30, 2023). https://www.theverge.com/2023/5/30/23742005/ai-risk-warning-22-word-statement-google-deepmind-openai
[177]
Rosalie Waelen. 2022. Why AI ethics is a critical theory. Philosophy & Technology, 35, 1, 9.
[178]
Walker, R., Sherif, E. and Breazeal, C., 2022, May. Liberatory computing education for african american students. In 2022 Conference on Research in Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT), pp. 95-99.
[179]
Jen Webb, Tony Schirato, and Geoff Danaher. 2002. Understanding Bourdieu. Sage Publications.
[180]
Anne L. Washington and Rachel Kuo. 2020. Whose side are ethics codes on? power, responsibility and the social good. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAT* '20). Association for Computing Machinery, New York, NY, USA, 230–240.
[181]
White House. 2023. Biden-⁠Harris Administration Secures Voluntary Commitments from Leading Artificial Intelligence Companies to Manage the Risks Posed by AI. July 21 2023. https://www.whitehouse.gov/briefing-room/statements-releases/2023/07/21/fact-sheet-biden-harris-administration-secures-voluntary-commitments-from-leading-artificial-intelligence-companies-to-manage-the-risks-posed-by-ai/
[182]
Lindsay Weinberg. 2022. Rethinking fairness: An interdisciplinary survey of critiques of hegemonic ML fairness approaches. Journal of Artificial Intelligence Research, 74, pp.75-109.
[183]
David Gray Widder, et al, 2023. It’s about power: What ethical concerns do software engineers have, and what do they (feel they can) do about them?. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 467-479.
[184]
Langdon Winner. 1980. Do Artifacts Have Politics? Daedalus, 109, 1, 121–36, http://www.jstor.org/stable/20024652.
[185]
Erik Olin Wright. 2013. Transforming capitalism through real utopias. American sociological review, 78, 1, 1-25.
[186]
Peter Wright and John McCarthy. 2015. The politics and aesthetics of participatory HCI. Interactions, 22, 6, 26-31.
[187]
Karen Yeung. 2018. Five fears about mass predictive personalization in an age of surveillance capitalism. International Data Privacy Law, 8, 3 (2018): 258-269.
[188]
Mike Zajko, 2022. Artificial intelligence, algorithms, and social inequality: Sociological contributions to contemporary debates. Sociology Compass, 16,3: e12962.
[189]
Monika Zalnieriute, 2021. "Transparency Washing" in the Digital Age: A Corporate Agenda of Procedural Fetishism. Critical Analysis of Law, 8, 139.
[190]
Michalinos Zembylas, Mark Baildon, and Dennis Kwek. 2022. Responsive education in times of crisis. Asia Pacific Journal of Education 42, sup1, 1-5.
[191]
Londi Ziko. 2024. AI and the Instrumentalization of Fear. Blue Labyrinths. https://bluelabyrinths.com/2023/08/14/ai-and-the-instrumentalization-of-fear/
[192]
Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Public Affairs.

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      cover image ACM Transactions on Computing Education
      ACM Transactions on Computing Education Just Accepted
      EISSN:1946-6226
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      Online AM: 04 November 2024
      Accepted: 10 October 2024
      Revised: 20 June 2024
      Received: 31 August 2023

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      Author Tags

      1. AI
      2. ethics
      3. social issues
      4. crisis
      5. intellectuals
      6. critique
      7. public good
      8. critical theory
      9. social theory

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