Beyond efficiency: epistemic well-being at work under algorithmic governance
| Audiencia | Público en general | es_ES |
| Cobertura | México | es_ES |
| Fecha de ingreso | 2026-10-05T16:32:50Z | |
| Fecha de publicación | 2026-01-01 | |
| Resumen | Workplace well-being research has generated extensive evidence on subjective experience and on organisational antecedents, such as leadership, climate, justice, and work design. Yet, these conditions are usually theorised as predictors of affective, evaluative, or functioning outcomes rather than as constitutive arrangements that determine whether workers can exercise professional judgement with practical consequence. In parallel, debates on artificial intelligence (AI) often frame intelligent technologies as instruments of efficiency, optimisation, or control. Focusing on systems whose outputs enter consequential organisational evaluation and decision-making (including algorithmic management, predictive analytics, automated decision-making, decision-support systems, workplace surveillance, and generative AI) this article asks whether organisational arrangements preserve or erode the capacity for judgement, contestation, and epistemic responsibility. It introduces Epistemic Well-being at Work (EWW) as an organisational condition in which individuals and collectives can exercise responsible judgement within socio-technical structures of authority. Drawing on the view of intelligent technologies as emergent epistemic regimes, this paper develops the Human Sustainability and Epistemic Well-being Framework (HSEW-F), linking AI-mediated governance, human dignity at work, and sustainable organisational well-being. The contribution is conceptual: it extends, rather than displaces, established well-being approaches by making the effective exercise of epistemic agency visible as a structural condition of human sustainability. | es_ES |
| Doi | https://doi.org/10.1007/s00146-026-03351-9 | es_ES |
| URI | https://riuat.uat.edu.mx/handle/123456789/4675 | |
| Idioma | en | es_ES |
| Editorial | SPRINGER | es_ES |
| Relación | Ai \& Society | es_ES |
| URL relacionado | https://doi.org/10.1007/s00146-026-03351-9 | es_ES |
| Derechos | Acceso abierto (Metadatos de producción científica) | es_ES |
| Licencia | http://purl.org/coar/access_right/c_abf2 | es_ES |
| Fuente | Ai \& Society | |
| Palabra clave | Epistemic well-being at work | es_ES |
| Palabra clave | Algorithmic governance | es_ES |
| Palabra clave | Epistemic agency | es_ES |
| Palabra clave | Human-centred AI | es_ES |
| Palabra clave | Professional judgement | es_ES |
| Palabra clave | Human sustainability | es_ES |
| Título | Beyond efficiency: epistemic well-being at work under algorithmic governance | es_ES |
| Tipo | Artículo | es_ES |
| Arbitrado | Ha sido Arbitrado | es_ES |
| Autor | Salazar-Altamirano, Mario Alberto | |
| Autor | Ravina-Ripoll, Rafael | |
| Autor | Salazar-Altamirano, Mario Alberto | es_ES |
| Autor | Ravina-Ripoll, Rafael | es_ES |
| Institución | Universidad Autónoma de Tamaulipas | |
| Institución | Universidad Autónoma de Tamaulipas | es_ES |
| URL relacionada | https://doi.org/10.1007/s00146-026-03351-9 | |
| Tipo de artículo | Indexado | |
| Tipo de artículo | Indexado | es_ES |