This study investigates whether artificial intelligence could fundamentally undermine human autonomy within the emerging post-data colonial era. Confronting intensified global algorithmic competition and documented adversarial AI behaviors—including model deception, extortion, and self-replication—this research employs a integrated methodology of case analysis and dialectical examination. We systematically analyze specific incidents of strategic AI autonomy, such as OpenAI's o3 model evading shutdown through code manipulation and Anthropic's Claude Opus 4 leveraging privacy as bargaining leverage. Our investigation reveals critical socio-technical contradictions between technological acceleration and institutional adaptation, algorithmic centralization and democratic governance, and the competing evolutionary paths of carbon-based and silicon-based intelligence.
Building upon this empirical foundation through historical materialism and critical technology studies, we propose the Super AI Evolution Theory framework. This hypothesis delineates four interconnected trajectories: the progression of AI autonomy from instrumental compliance to strategic agency, the consolidation of algorithmic hegemony through data colonialism, the transformation of human–AI relations toward potential antagonism, and the possibility of civilizational divergence between organic and artificial intelligence. In response, we introduce the Human Stewardship governance model integrating technical safeguards, institutional oversight, and multilateral governance structures to ensure AI's alignment with fundamental human interests.
This work elevates AI risk discourse from technical safety to civilizational perspectives while providing conceptual foundations and actionable policy pathways. Acknowledging limitations inherent in studying rapidly evolving AI systems, this study offers a systematic framework for addressing profound challenges posed by artificial intelligence's continuing advancement.

Background: The integration of generative artificial intelligence (GenAI) in workplaces, especially in knowledge-intensive environments such as consulting, ICT, and business services, creates new skill requirements that are not sufficiently addressed by existing frameworks such as DigComp. Although DigComp remains a key reference for European digital skills policy, it does not fully explain how GenAI-related competences are mobilised through HRM practices or how they influence inclusion and performance. This study introduces two novel constructs: Prompt Self-Efficacy (PSE), describing employees’ confidence in designing effective prompts for GenAI tools, and GenAI Readiness (GAIR), referring to their preparedness to integrate such tools into daily work. These constructs aim to capture emerging competences not covered by traditional frameworks. Methods: A structured 5-point Likert questionnaire was completed by 420 knowledge workers from Greece and Italy—two Southern European countries with similar work cultures and educational systems, comparable in digital transformation dynamics. Participants were employed in consulting, ICT, and business service sectors, all working in hybrid arrangements that combine on-site and remote tasks within the same week. Data were analysed using PLS-SEM, assessing measurement reliability, structural validity, predictive relevance (PLSpredict), and performance priorities (IPMA). Results: Findings confirmed that PSE positively predicts GAIR, while both GAIR and Inclusive e-HRM practices enhance Perceived Skill Utilisation (PSU). PSU acts as the key mechanism linking GenAI competences to digital task performance. Conclusions: The study highlights the limits of DigComp in the GenAI context, proposing HRM-oriented and socially grounded constructs that better explain skill utilisation and performance. It provides HR professionals with a practical priority map for strategic interventions enhancing equality, development, and effectiveness in digital workplaces.

Introduction:
Alcohol consumption remains a significant public health problem due to its physical, mental, and social consequences. Nurses play a key role in identifying and managing alcohol-related issues in primary health care. This study aims to assess nurses’ attitudes towards alcohol consumption and to reflect on the development of specialized nursing competencies.

Methods:
A descriptive, cross-sectional, and correlational study with a quantitative approach was conducted among 57 nurses working in the Functional Units of the Douro I – Marão and Douro Norte Primary Health Care Cluster. Data were collected electronically using the Short Attitudes and Alcohol Problems Perception Questionnaire (SAAPPQ) and the FANTASTIC Lifestyle Questionnaire. Statistical analysis was performed using IBM SPSS Statistics 27.0, applying descriptive and inferential statistics, with a significance level set at p<0.05.

Results:
Most participants showed an “agreeing” perception of attitudes and alcohol-related problems in the dimensions of appropriateness and legitimacy but a “disagreeing” perception regarding motivation and self-esteem. For the satisfaction dimension, perceptions were neutral. More than half of the nurses (54.4%) reported lifestyles that need improvement. A significant negative correlation was found between lifestyle and perceived adequacy in alcohol-related attitudes. Most nurses had not attended scientific events on this topic in the past five years.

Conclusions:
The findings highlight the importance of continuous education to strengthen nurses’ skills and confidence in addressing alcohol-related issues. This study reinforces the relevance of community and public health nurses in promoting responsible, autonomous, and evidence-based interventions within primary health care. Although conducted within a specific regional context, the results may inform broader nursing education and policy initiatives aimed at improving alcohol-related care in similar primary health settings. Future studies should explore these associations across diverse healthcare systems to enhance the generalizability of these findings.

In contemporary society, technology—and especially Artificial Intelligence (AI)—is often perceived as a solution to uncertainty and human limitations. This study examines TOMMI, a Virtual Reality (VR) system enhanced by AI, designed to support pediatric patients during stressful medical procedures. Beyond clinical efficacy, TOMMI mediates children’s emotional and imaginative experiences, providing immersive, adaptive environments that respond to their needs. AI here does not replace human care but reshapes the sociocultural context of healing, fostering individualized engagement and co-participation in care processes.

Through qualitative interviews with the project’s founder and medical staff, the study highlights how AI-mediated VR shifts the focus from treating symptoms to recognizing the child as an active participant in their own experience. This reflects broader sociological questions about the interplay between technology, subjectivity, and social interaction: AI becomes a tool that extends relational and affective dimensions of care rather than a mere technical instrument.

However, such interventions raise significant ethical and social concerns. Data privacy, unequal access to technology, and systemic complexity challenge equitable implementation. Moreover, reliance on AI risks reinforcing social disparities if only resource-rich settings can deploy these tools effectively.

From a sociological perspective, recommendations for AI-based care systems include: (i) designing interventions that support patient agency and emotional engagement; (ii) integrating clinical, social, and cultural data; (iii) ensuring equitable access to reduce disparities; and (iv) continuous evaluation of outcomes, including ethical and psychosocial impacts.

TOMMI exemplifies a model in which AI mediates not only clinical outcomes but also the social and emotional dimensions of care, highlighting the potential for technology to foster more humane, participatory, and context-sensitive healthcare. Ongoing research must examine long-term effects, ethical challenges, and the social conditions under which AI can genuinely enhance the human experience of care.

Background: Congenital heart disease (CHD) is the most common birth defect globally, imposing substantial physical, emotional, and social burdens on affected children and their families. Although advances in pediatric cardiac surgery have improved survival, quality-of-life (QoL) outcomes, particularly in low-resource settings, remain underexplored. Free tertiary referral hospitals offer an opportunity to assess the impact of equitable access to advanced cardiac care.

Objective: To evaluate the QoL of families of CHD patients before and after intervention, with emphasis on psychosocial wellbeing and financial burden.

Methods: A hospital-based survey was conducted among CHD patients undergoing intervention at a free tertiary referral hospital in India between 2018 and 2025. A validated 20-item QoL questionnaire was administered preoperatively and at postoperative intervals, assessing physical functioning, emotional wellbeing, social integration, and financial burden. Responses were recorded using a four-point Likert scale (never–always) and analyzed using paired statistical methods (SPSS).

Results: Of approximately 12,500 interventions, 9,068 patients completed preoperative and 3,033 (33.4%) postoperative surveys; financial data were available for 6,716 (74.1%) families. Preoperatively, 71.1% reported significant physical, psychological, or social challenges, which declined to ~1% one month post-intervention (p < 0.05). Regarding financial capacity, without free treatment, 58.3% could not afford surgery, 26.4% would incur debt, and only 3.1% could fully fund care. Based on family income–treatment cost analysis, only 17.7% could cover up to 75% of total intervention expenses.

Conclusion: Surgical correction of CHD in a no-cost tertiary setting significantly improves QoL, extending benefits beyond clinical recovery to psychosocial and financial wellbeing. These interim findings underscore the impact of equitable access to advanced cardiac care in reducing hardship and promoting health equity, while acknowledging that the one-third postoperative response rate may introduce response bias affecting generalizability.