We introduce the Bias Network Approach (BNA) as a sociotechnical method for AI developers to identify, map, and relate biases across the AI development process. This approach addresses the limitations of what we call the "isolationist approach to AI bias," a trend in AI literature where biases are seen as separate occurrences linked to specific stages in an AI pipeline. Dealing with these multiple biases can trigger a sense of excessive overload in managing each potential bias individually or promote the adoption of an uncritical approach to understanding the influence of biases in developers’ decision-making. The BNA fosters dialogue and a critical stance among developers, guided by external experts, using graphical representations to depict biased connections. To test the BNA, we conducted a pilot case study on the "waiting list” project, involving a small AI developer team creating a healthcare waiting list NPL model in Chile. The analysis showed promising findings: (i) the BNA aids in visualizing interconnected biases and their impacts, facilitating ethical reflection in a more accessible way; (ii) it promotes transparency in decision-making throughout AI development; and (iii) more focus is necessary on professional biases and material limitations as sources of bias in AI development.

According to social studies of artificial intelligence (AI), public AI controversies tend to dissipate relatively quickly despite well-documented risks and harms. The reasons for this lack of controversiality are beginning to be studied. Drawing on the framework of sociotechnical controversies, we analyze the de-escalation of contentious discussions observed in the AI legislative process by Chile's National Congress. Utilizing a qualitative approach, we tracked the deliberations hosted by the Chamber of Deputies and the Senate of Chile across 51 sessions between 2023 and 2024. We describe three processes of cooling down in the AI debates: (1) deflection of technology liability, (2) instrumentalization of technology policy, and (3) moralization of technology use. However, constructive exchanges appear in some circumstances, which allow us to foresee some favorable conditions for participation in the debates on AI regulation. This paper contributes to AI controversy studies by outlining cooling-down processes and conditions that foster dialogue and providing a critical perspective on the formation of AI regulation.

This year, CSCW is coming to Latin America for the first time. In this workshop, we aim to position the region as a common context that brings together students, academics, as well as industry researchers and practitioners interested in studying, designing, developing, deploying, and/or evaluating CSCW and social computing technology, addressing challenges either emerging from or impacting Latin America. Previous initiatives have explored or highlighted the potential of Latin America for CSCW research, and this one-day workshop seeks to build on that foundation. Our objectives are to: (1) Bring together researchers, practitioners, and students interested in engaging with Latin America through their research and practice; (2) Discuss the opportunities and challenges of conducting CSCW research centered on Latin America; (3) Collaboratively mentor emerging projects focused on Latin America; (4) Advance 5-year collaborative research agendas among existing CSCW Latin America research groups; and (5) Increase the visibility of Latin American research projects within the broader international CSCW community. We will invite senior CSCW researchers from Latin America and other regions to discuss the work presented at the event. This workshop seeks to enrich the global conversation on CSCW and highlight and strengthen Latin America's unique contributions to this field.

AI has become (again) a matter of public interest, and it is crucial to investigate how the news media intervenes in the hype and publicity around AI in different countries. At the intersection between Media Studies and Science and Technology Studies (STS), this article examines portrayals of AI and related technologies in the Chilean news media. We curated a corpus of nearly 7000 AI-related news articles from 2008 to 2023 from four Chilean newspapers. We combined an LDA topic modelling with an analysis with dictionaries of the key actors and critical issues discussed around AI. The analysis shows the explosive growth of the media coverage of AI in recent years, as well as the diversity of topics associated with AI in Chile. We found a high prominence of topics related to industry and technology, a high visibility of international actors, mostly U.S. tech companies, and a low level of mentions of critical issues around AI. Moreover, we also discuss the low coverage of the State’s AI use, the emergent use of generative AI in tech journalism, and the prominence of topics such as the arts and humanities that appear as emerging spaces for the problematisation of AI in Chile.

Public funding plays a pivotal yet often overlooked role in shaping AI development, especially in Latin America. Drawing on sociological theories of performativity, we analyze 205 AI projects funded by Chile’s key public agencies, related to research, entrepreneurship, and creation, over the past decade. Through content analysis combined with a qualitative, heuristic procedure, we characterize five dominant narratives across state-funded AI projects, seeking to interpret the social meanings embedded within their descriptions considering their situated context. This method informs the articulation of five narratives: AI for productivity gains, as a transformative force, as a literacy need, for smart surveillance, and as situated and creative inquiry. Our findings reveal that AI for productivity gains has strongly dominated over the last decade. We argue that this narrative functions as a strategic mechanism for aligning legacy institutional interests with those of the actors seeking funding. By framing public funding as performative, this paper contributes to debates on how state-led narratives help shape technological development’s trajectory. It also emphasizes the interconnectedness of actors, political economy, and socio-technical dynamics concerning AI’s future.

AI technologies are rapidly transforming societies, yet dominant narratives about AI development and governance often emerge from the Global North, overlooking perspectives from Latin America. This study explores how stakeholders in Chile—end-users, developers, and decision-makers—understand and engage with AI, focusing on transparency and governance. We uncover how local narratives shape AI perceptions, understandings, and demands for governance approaches by drawing from qualitative research projects, including interviews, focus groups, and a digital ethnography of AI regulation discussions in the Congress. A key finding is the widespread perception of Chile as a "test subject" or "sandbox nation" for AI across the different stakeholders, reflecting broader power asymmetries in technology development. In addition, stakeholders conceptualize and demand different governance approaches depending on whether they refer to AI as an abstract idea or a specific AI system. End-users often view AI as an opaque force imposed upon them, leading to trust based on functional efficiency rather than informed understanding—however, their demands for transparency and human oversight increase when engaging with specific AI-mediated systems. Developers seek to demystify AI by shifting the focus from abstract capabilities to particular applications, emphasizing its mechanical nature and countering misconceptions shaped by anthropomorphic narratives. Decision-makers, meanwhile, negotiate the definition of AI technologies balancing between broad and specific definitions of AI and navigate tensions over governance frameworks from the Global North (US vs. Europe). This study emphasizes the need for transparency and public participation tailored to local sociopolitical contexts and contributes to global debates on AI’s understanding and governance, advocating for policies that reflect regional priorities rather than universalized frameworks.