Jul 2026· Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi· 0 citations· 71 references
TL;DR
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.
Abstract
This study examines the transformative impact of artificial intelligence (AI) on the future of work from a human-centered, interdisciplinary perspective. Drawing on insights from sociology, ethics, education and organizational behavior studies, it highlights how AI reshapes job roles, skills, workplace dynamics and labor identities. The paper emphasizes that AI is not a neutral or inevitable force but a socio-technical system shaped by power, culture and policy. Key challenges include algorithmic management, digital exclusion, emotional labor and a lack of ethical opacity. To address these issues, the study advocates for policies that prioritize transparency, inclusivity and human agency through educational reform, robust labor protections and ethical AI governance. Furthermore, the paper underscores that social scientists should not remain mere observers of these processes but can act as active agents in shaping a fair and equitable integration of AI into work life. Developed within a conceptual framework, this study offers guidance for future research and policymaking, highlighting the necessity of interdisciplinary collaboration to ensure that AI not only enhances efficiency but also promotes justice, well-being, and sustainability.
This conceptual paper argues that traditional technology governance models are insufficient and that leaders must develop an augmented moral compass to navigate algorithmic decision-making, data governance, and equity and proposes an original Moral Compass Model.
The rapid advancement and integration of Artificial Intelligence (AI) into various professional domains present a transformative, yet complex, challenge for social work. While AI holds immense potential to enhance efficiency, streamline administrative tasks, and provide data-driven insights for social services, its adoption also introduces profound ethical and practical dilemmas. This desktop literature review explores the landscape of AI in social work education, synthesizing existing research, professional guidelines, and scholarly discourse, to provide a comprehensive overview. The article argues that the ethical and responsible use of AI is not merely a technical concern but a core pedagogical imperative that must be woven into the fabric of social work curricula. It examines key themes, including the potential benefits of AI in education and practice, the critical ethical challenges, such as algorithmic bias, privacy, and the de-emphasis of the human-centred relationship, and the necessary competencies social work students must acquire. The review concludes with recommendations for social work educators, highlighting the need for a revised curriculum that fosters AI literacy, critical thinking, and a robust ethical framework to prepare future professionals for a technologically mediated world
Gift Saladi, Kudzai Mwapaura· Ngenani: The Zimbabwe Ezekie...· 0 citations
It is argued that the future of professional capital depends less on technological advancement itself and more on how AI is embedded within institutional design, professional learning cultures and teacher agency.
S. Yıldız, İbrahim Karagöl· Journal of Professional Capi...· 0 citations
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.
J. Schulz, Laura Robinson, Katia Moles· International journal of kno...· 0 citations
The findings suggest that while GenAI may enhance learner agency through personalisation and support, it also risks exacerbating educational inequalities and diminishing learner autonomy in certain contexts.
Jasper Roe, Mike Perkins· Academia AI and Applications· 23 citations
The integration of artificial intelligence (AI) into early childhood environments is most often judged through a binary lens of educational benefit versus technological harm. This framing overlooks a deeper question: how these systems reshape the ecological conditions on which child development depends. This exploratory, theory-generating conceptual inquiry examines how experts conceptualize the tension between the highly efficient illusion of agency presented by AI systems and the ecological conditions that support the development of authentic agency in young children. Using a qualitative expert-interview approach, we gathered the perspectives of six interdisciplinary scholars and analyzed them through a primarily deductive and partly inductive content analysis. Anchored in the multiple-realizability-of-agency thesis, actor-network theory, and complexity systems thinking, the analysis suggests that experts perceive AI’s simulation of interactivity, autonomy, and adaptability as potentially reducing the physical and social frictions that support developmental processes, redistributing decision-making within child–adult–AI networks, and limiting opportunities for the development of resilience. Drawing on these expert perspectives and the study’s theoretical framework, we argue for a conceptual reorientation from pedagogical scaffolding toward learning-ecosystem architecture and propose a pedagogy of friction that preserves the desirable difficulties through which authentic agency is nurtured.
Wenwei Luo, Minqi Gao, Jin Liu et al.· AI, Brain and Child· 0 citations