Fenwick McKelvey’s research while affiliated with Concordia University and other places

As two researchers faced with the prospect of still more knowledge mobilisation, and still more consultation, our manuscript critically reflects on strategies for engaging with consultations as critical questions in critical AI studies. Our intervention reflects on the often-ambivalent roles of researchers and ‘experts’ in the production, contestation, and transformation of consultations and the publicities therein concerning AI. Although ‘AI’ is increasingly becoming a marketing term, there are still substantive strategic efforts toward developing AI industries. These policy consultations do open opportunities for experts like the authors to contribute to public discourse and policy practice on AI. Regardless, in the process of negotiating and developing around these initiatives, a range of dominant publicities emerge, including inevitability and hype. We draw on our experiences contributing to AI policy-making processes in two Global North countries. Resurfacing long-standing critical questions about participation in policymaking, our manuscript reflects on the possibilities of critical scholarship faced with the uncertainty in the rhetoric of democracy and public engagement.

Generative AI is a uniquely public technology. The large language models behind ChatGPT and other tools that generate text and images is a major develop in publicity as much as technology. Without public data and public participation, these large models could not be trained. Without the attention, hype, and hope around these technologies, the big AI firms probably could not afford the computational costs to train these models. Our special issue questions how Critical AI Studies can attend to the publics, publicities, and publicizations of generative AI. We situate AI’s publicity as mode of publicity – hype, scandals, silences, and inevitability – as well as a mode of participation seen in the grown importance of technology demonstrations. Within this situation our contributions offer four different research paths: (1) situating the legacy media as an enduring process of legitimation; (2) looking at the ways that AI has a private life in public; (3) questioning the post-democratic future of public participation; and, (4) developing new prototypes of public participation through research creation.

Political parties have gone digital. Political scientists in countries around the world have diagnosed the rise of the digital party and traced parties’ adoption of digital technology. Existing attempts to understand parties’ digital practices have focused on the adoption of different tools, with scholars empirically studying and theorizing how and why digital technology is used. What has received less attention is the technical architecture and origins of these tools, questions that have been more directly examined by political communication scholarship. In this paper we entwine insights from these two disciplines, interrogating the idea of ‘platformization’ in the context of political technology. Presenting a unique, longitudinal dataset that captures the technological development of political party websites in 66 parties in 16 countries, we provide unprecedented insight into the evolution of party websites and show evidence of increasing platform dependency. Our findings have important implications for our understanding of parties’ relationship with technology, showing how technological developments and monopolies can lead to increasingly homogenized practice internationally.

On February 13, 2020, the Toronto Police Services (TPS) issued a statement admitting that its members had used Clearview AI’s controversial facial recognition technology (FRT). The controversy sparked widespread outcry by the media, civil society, and community groups, and put pressure on policy-makers to address FRTs. Public consultations presented a key tool to contain the scandal in Toronto and across Canada. Drawing on media reports, policy documents, and expert interviews, we investigate four consultations held by the Toronto Police Services Board (TPSB), the Office of the Privacy Commissioner (OPC), and the parliamentary Standing Committee on Access to Information, Privacy and Ethics (ETHI) to understand how public opinion and outrage translate into policy. We find that public consultations became a powerful closure mechanism in the policy-making toolbox, inhibiting rather than furthering democratic debate. Our findings show that consultations do not advance public literacy; that opportunities for public input are narrow; that timeframes are short; and that mechanisms for inclusion are limited. Even in the best-case circumstances, consultations are merely one of many factors in AI governance and seldom impact concrete policy outcomes in the cases studied here.

Mainstream coverage of artificial intelligence often appears to emphasise the technologies’ benefit and economic potential over its growing downsides. How does a technology poised to be so disruptive become so uncritically embraced? Why is it, simply put, that artificial intelligence's representations in legacy media do not normally convey the controversialities otherwise found in research or policy debates? We introduce the concept of ‘freezing out’ to describe processes of translation that cool down debates over the merits of technology. Freezing out looks at the other side of controversy studies to study the production of uncontroversies or cold controversies rather than hot topics and debates. We use the coverage of artificial intelligence in Canadian national news outlets to analyse how controversiality becomes ‘frozen out’. Since Canadian academics won the prestigious ImageNet prize in 2012 introducing the modern turn toward machine learning approaches, Canada has promoted itself as a global leader. Using in-depth interviews with Francophone and Anglophone journalists as well as topic modelling on data collected from five major newspapers, we find that routine news making processes between journalists, experts, entrepreneurs, and governments build, maintain, and promote Canada's artificial intelligence ecosystem. Freezing out contributes to a broader interest in how heterogeneous actors traverse their domain of expertise across policy, media, and research circles to cool down artificial intelligence controversies.

Background: In 2021, the Canadian Parliamentary Standing Committee on Access to Information, Privacy and Ethics (ETHI) conducted an inquiry around Pornhub, following allegations that parent company MindGeek profits from non-consensual content. Analysis: This article offers a discourse analysis of the ETHI’s process, testimony, and report on Pornhub using Carol Bacchi’s policy analysis method, “What is the problem represented to be?” Conclusions and implications: This study reveals a policy process blatantly influenced by anti-porn sentiments, resulting in hearings that framed porn as sexual violence rather than sex industry labour. It exposes how ETHI’s approach failed to constructively engage existing regulations, precarious labour conditions, or platform operations. The result is ineffective policy recommendations that procedurally exclude relevant stakeholders and do not adequately protect platform users from harm.

Our article analyses partisan, user-generated Facebook pages and groups to understand the articulation of political identity and party identification. Adapting the concept of scenes usually found in music studies, these Facebook pages and groups act as partisan scenes that maintain identities and sentiments through participatory practices, principally by making and sharing memes. Using a mixed methods approach that combines social media data and interviews during the 2019 Canadian federal election, we find that these partisan scenes are an active part of elections and the overall political information cycle in Canada but endure beyond election cycles. Rather than trying to sway voters of different political affiliation and influence the election outcome, Facebook users employ memes to hang-out and build community, thereby reinforcing partisanship.