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Social robots were initially designed within frameworks of assistance, accompaniment, and relational support, particularly in contexts of ageing, care, and social isolation. Yet their diffusion has been accompanied by recurring concerns regarding loss of control, dehumanization of social relations, emotional dependency, human replacement, and the artificialization of care practices. Drawing on an analysis of media discourses devoted to social robots, this article proposes to shift the conventional question of technological acceptability toward an anthropology of contemporary relational imaginaries. The central hypothesis advanced here is that controversies surrounding social robots do not merely reveal resistance to technological innovation; rather, they make visible a deeper crisis affecting social bonds, care infrastructures, and forms of human presence. Media representations thus emerge as privileged sites of symbolic production where the boundaries between human and non-human, assistance and substitution, relationship and simulation are continuously negotiated. The article argues that the acceptability of social robots cannot be reduced to functional evaluation alone but must instead be understood as a cultural and anthropological construction of technical alterity and human–machine relations.
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Artificial Intelligence in Healthcare: A Holistic Approach for Successful, Human-Centered Implementation
Emmanuel Carré, Marjorie Garofalo
EPISTÉMÈ 2025;33:6.   Published online March 31, 2025
DOI: https://doi.org/10.38119/cacs.2025.33.6

The integration of Artificial Intelligence (AI) in the healthcare sector represents a major transformation that raises complex issues concerning the technical, organizational, and relational dimensions of the profession. This contribution analyzes the key success factors and obstacles to the implementation of AI in healthcare facilities, adopting a holistic perspective that emphasizes communicational and interprofessional dynamics. Through an analysis of recent literature, we identify promising approaches and necessary conditions for successful AI integration, while preserving the quality of caregiver-patient relationships and interactions among professionals. Our analysis reveals that successful implementation relies on a balanced combination of leadership, end-user training, support for teams in modifying their daily work, and ethical governance. The central role of communication in this transformation process is emphasized, both in change management and in the adaptation of professional practices. We propose recommendations that integrate these different dimensions to guide the development and implementation of AI projects in healthcare, focusing on preserving and enriching human relationships within healthcare organizations.

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