When social work meets AI: a philosophical look at adoption, context, and critical resistance

Narratives of Power: AI, Agency and the EU AI Act

Public debate around AI has been characterised by hegemonic narratives that delineate the scope of the conversation, suppressing different voices and limiting nuanced discussion of the technology’s harms and benefits. Scholars have identified technological or enchanted determinism, the arms race mentality and the utopia versus dystopia debate as key narratives around AI. These ideas saturate the conversation, driven primarily by the tech industry, which positions itself as the (only) expert voice. The industry’s capacity to drive these narratives is facilitated by its established institutional authority and dominant presence in public discourse, as well as the knowledge asymmetry inherent in the proprietary, ‘black-box’ nature of AI systems. Tech firms leverage the technical opacity of AI and their powerful societal position to define the contours of public debate, assigning agency to AI itself and the tech industry; constructing users and civil society as passive observers or recipients; and establishing a frame for debate that focuses on extreme consequences or hyperbolic benefits. This study, conducted early in 2024, investigates the effects of this interpretive frame on the policy choices and communications of the EU AI Act, through a mixed-methods computational and critical discourse analysis. Within EU governing body texts, the same discursive patterns that map agency and erase the middle ground of debate in AI are found, helping to marginalise alternative perspectives from other stakeholders and prevent nuanced understandings of potential harms. In the context of the Act itself, these patterns reverberate in the assignment of agentic roles and the scope of the regulation.

SOCIAL AND ETHICAL IMPLICATIONS OF FULLY AUTONOMOUS AI

This research raises broad questions regarding social and tech ethics in the Age of AI by asking what happens if AI systems acquire full autonomy as economic actors within a late capitalist economy, specifically as workers, capitalists, and consumers. Through a careful engagement with recent Marxian social theory and the speculative literature on “full automation,” the article builds a case that the analytical lens of labor displacement needs to be enlarged to encompass the displacement of capitalists and consumers as well as workers. We propose to rethink social and tech ethics from the standpoint of a renewed attention to the constitutions of these economic actors within the capitalist system. Such a rethinking can cast new light on what it means for AI systems to be designed and deployed more ethically within the contemporary global capitalist system. It further underlines the urgency of a cross-disciplinary dialogue between social theorists and the engineers, managers, and regulators who are shaping the trajectory of such systems and, accordingly, the prospects for ethical social and economic outcomes.

Toward a coalescent ethics of enactive AI: a synthetic analysis across frameworks of gender, agency, and AI design

Negotiating epistemic authority in the age of generative AI: AI reliance, responsibility, and usage intensity among GenAI-using coaching professionals

The emergence of generative AI (GenAI) within human-centered guidance professions marks a transformative shift in society that transcends mere improvements in technical efficiency. With large language models (LLMs) becoming increasingly embedded in professional practices centered on care, trust, and relational knowledge, critical questions arise about how algorithmic systems reshape human agency, autonomy, tacit expertise, and the ethical foundations of professional relationships. This study examines these questions through coaching, a socio-cultural practice characterized by tacit expertise, empathetic engagement, and care obligations. Through a survey with 205 self-identified GenAI-using coaches, this research explores how algorithmic systems mediate professional practice, what tensions emerge between human-centered values and algorithmic logic, and what this may reveal, within the boundaries of this exploratory sample, about emerging patterns in human–AI relations. The findings reveal that coaches report using GenAI extensively for structured, information-intensive tasks while maintaining control over relational and interpretative work. This pattern can be understood as boundary work preserving human authority over domains of tacit expertise. Significantly, frequent GenAI users report higher scores on self-reported ethical behaviors and beliefs, yet the majority rely on proprietary LLM platforms, highlighting structural constraints that shape technological choices. These patterns highlight critical societal questions about the valuation of tacit expertise, trust formation in AI-mediated relationships, and design justice issues in AI development. The study contributes to understanding how AI integration may reconfigure, and not just augment, the ethical foundations and cultural understanding of professional practice, with urgent implications for shaping AI-mediated futures for the common good.

ARTIFICIAL INTELLIGENCE AND THE FUTURE OF WORK: A HUMAN-CENTERED PERSPECTIVE FROM THE SOCIAL SCIENCES

This study examines the transformative impact of artificial intelligence (AI) on the future of work from a human-centered, interdisciplinary perspective, highlighting the necessity of interdisciplinary collaboration to ensure that AI not only enhances efficiency but also promotes justice, well-being, and sustainability.

The Great Wall of the Press: Layered Boundary Work of AI-Integrated Journalism

As artificial intelligence (AI) becomes increasingly embedded in journalistic practice, debates often frame it as either a disruptive force or a tool for efficiency. This study moves beyond this dichotomy by examining how journalists themselves interpret, negotiate, and position AI within journalism. Drawing on 19 in-depth interviews with Chinese journalists, and informed by boundary work and boundary object perspectives, the study analyses how AI is selectively integrated, justified, and governed across journalistic processes. The findings show that AI is primarily confined to routine and low-risk tasks, while being excluded from core editorial functions involving judgement, meaning-making, and accountability. The study argues that AI intensifies journalistic boundary work because it challenges journalism not only operationally, but also epistemically and infrastructurally. Journalists therefore engage in layered forms of boundary negotiation that operate across task, discursive, and structural dimensions. At the same time, AI functions as a boundary object mediating relationships among journalists, technology companies, and governance institutions under conditions of asymmetric platform dependency and institutional control.