Machine Agencies and the Algorithmic Media Observatory are pleased to announce its new research program on the Politics of Open Models. The SSHRC Insight Funded grant, The Politics of Open Models, explores the contradictions of open models as a defining AI governance question.
Could open models – “open-source technologies that are free to use…safe and secure” – be “a Made-in-Canada approach to generative AI” (Canadian Chamber of Commerce, 2024)? The Canadian Chamber of Commerce floated the idea in an article amidst debates about Canada’s AI regulation. But the article was anything but “made-in-Canada.” International platform giant Meta wrote the piece. Why would a firm—notorious for commercializing the Internet—advocate for a technology free-to-use? How might the rhetoric of openness mask new corporate expansion into AI?
These models can often be proxies for corporate control of AI. Meta, in 2024, quietly changed the use policy of its open-source model, Llama, to allow “national security applications” effectively permitting the model to support military applications (Roth, 2024). Meta’s ability to unilaterally change policies runs counter to foundational theories of openness as a means for shared governance and public accountability (Lessig, 2004; Schrock, 2016). How can an “open” model be under such tight corporate control? Why do open models receive regulatory protection given that most open models “will not on its own lead to a more diverse, accountable or democratized ecosystem, even though it may have other benefits” (Widder et al., 2024, p. 831).
What is an open models is at the nexus of AI’s global governance and governmentality (Amoore et al., 2024; Roberge et al., 2020; Veale et al., 2023). Increasingly, AI is understood as a political project especially given the extreme views of many key figures in the field (Gebru & Torres, 2024). Controversies, or the lack thereof, about what is AI and what are its social impacts shaped AI’s early political project, legitimating large AI firms to become empires of the “new” economy (Dandurand et al., 2023; Gourlet et al., 2024; Suchman, 2023). These AI empires has prompted a global crisis: a need to legitimate AI as foundational to future without legitimating anti-democratic consolidations of power prompting a turn to open models as a solution that relies on the importance and ambiguity of openness.
Research blends critical AI studies and political economy of international communication with research-creation and commons theory to explore the contentious politics of open models as both a solution and threat for democratic accountability of AI technologies. Taking up this challenge, the five-year project analyzes emerging, governance of open AI models, collaborates in the development of new forms of model governance, and enhances democratic oversight of AI through commons-based governance theory. These research themes will make national and international contributions. The team will establish Montreal as a critical hub on open-source models in the emerging field of Critical AI Studies, advise national and international AI regulation, and contribute new governance models for community-based models.
The project will be lead at the Milieux Institute at Concordia University and the Chaire de recherche du Québec sur l’intelligence artificielle et le numérique francophones (IANF) with partners including MUTEK, Canadian Centre for Policy Alternatives, and the Société des arts technologiques. Researchers include Jonathan Roberge, Bart Simon, ME Luka, Jennifer Pybus, Florence Millerand, and Patrick McCurdy.
References
Amoore, L., Campolo, A., Jacobsen, B., & Rella, L. (2024). A world model: On the political logics of generative AI. Political Geography, 113, 103134. https://doi.org/10.1016/j.polgeo.2024.103134
Canadian Chamber of Commerce. (2024, October 28). Open-Sourced AI: A Made-in-Canada Approach to Generative AI. Canadian Chamber of Commerce. https://chamber.ca/open-sourced-ai-a-made-in-canada-approach-to-generative-ai/
Dandurand, G., McKelvey, F., & Roberge, J. (2023). Freezing out: Legacy media’s shaping of AI as a cold controversy. Big Data & Society, 10(2), 20539517231219242. https://doi.org/10.1177/20539517231219242
Gebru, T., & Torres, É. P. (2024). The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence. First Monday. https://doi.org/10.5210/fm.v29i4.13636
Gourlet, P., Ricci, D., & Crépel, M. (2024). Reclaiming artificial intelligence accounts: A plea for a participatory turn in artificial intelligence inquiries. Big Data & Society, 11(2), 20539517241248093. https://doi.org/10.1177/20539517241248093
Lessig, L. (2004). Free Culture: How Big Media uses Technology and the Law to Lock Down Culture and Control Creativity. Penguin Press.
Roberge, J., Morin, K., & Senneville, M. (2020). Deep Learning’s Governmentality: The Other Black Box. In A. Sudmann (Ed.), The Democratization of Artificial Intelligence (pp. 123–142). transcript Verlag. https://doi.org/10.1515/9783839447192-008
Roth, E. (2024, November 4). Meta AI is ready for war. The Verge. https://www.theverge.com/2024/11/4/24287951/meta-ai-llama-war-us-government-national-security
Schrock, A. R. (2016). Civic hacking as data activism and advocacy: A history from publicity to open government data. New Media & Society, 18(4), 581–599. https://doi.org/10.1177/1461444816629469
Suchman, L. (2023). The uncontroversial ‘thingness’ of AI. Big Data & Society, 10(2), 20539517231206794. https://doi.org/10.1177/20539517231206794
Veale, M., Matus, K., & Gorwa, R. (2023). AI and Global Governance: Modalities, Rationales, Tensions. Annual Review of Law and Social Science, 19(Volume 19, 2023), 255–275. https://doi.org/10.1146/annurev-lawsocsci-020223-040749
Widder, D. G., Whittaker, M., & West, S. M. (2024). Why ‘open’ AI systems are actually closed, and why this matters. Nature, 635(8040), 827–833. https://doi.org/10.1038/s41586-024-08141-1
