The aim of this study is to critically examine the transformation of EU industrial policy, focusing on the shift from a predominantly market-oriented governance model to one characterized by strategic interdependence. We ask how this evolution influences the EU's ability to manage dependencies, secure critical inputs, and enhance its productive capabilities in an increasingly interconnected global economy. To achieve this, we employed a mixed-methods approach, combining qualitative analysis of EU policy documents and quantitative assessments of industrial performance metrics. Our findings indicate that the integration of traditional principles, such as the Single Market and competition, with strategic measures is vital for fostering resilience and competitiveness. We identify key challenges and opportunities that arise from this new approach, emphasizing the need for a balanced strategy that promotes both openness and strategic management. Overall, we conclude that the future of EU industrial policy will hinge on its capacity to navigate geopolitical complexities while ensuring sustainable growth and innovation within its industrial sectors. The study further examines how emerging technologies, skills, infrastructure and industrial ecosystems will shape Europe's future productive capacity. It considers whether EU intervention should focus on market-making, market-shaping, or a combination of both. Particular attention is given to the allocation of public resources according to their contribution to productivity, social welfare, strategic resilience and citizen utility per euro spent. We also assess the potential benefits and risks of a more integrated industrial governance structure, including the possibility of a strategic budget line under DG Industry linking people, organisations and technology. Finally, the study argues that European industrial policy should focus less on protecting existing firms and more on creating the conditions in which globally competitive industries and high-quality employment can emerge.

Artificial Intelligence (AI) has increasingly become embedded in the everyday life of contemporary communities, influencing communication, education, healthcare, employment, public services, cultural participation, and decision-making. While AI systems offer significant opportunities for improving efficiency, accessibility, personalization, and human capabilities, their growing presence also raises fundamental questions concerning human values. Issues related to dignity, autonomy, privacy, fairness, transparency, accountability, inclusion, trust, and cultural diversity have become increasingly important as intelligent technologies interact with individuals and communities.

This review paper examines the relationship between artificial intelligence and human values within contemporary communities. The study focuses particularly on how AI systems influence community relationships, social participation, individual autonomy, cultural practices, trust, and collective decision-making. The paper adopts a qualitative conceptual review methodology based on the analysis and synthesis of relevant scholarly literature, international ethical frameworks, and contemporary research on human-centered and community-centered artificial intelligence. Particular attention is given to human-centered AI, community participation, value alignment, responsible AI governance, and the social consequences of intelligent technologies.

The analysis indicates that AI cannot be understood solely as a technical system because its design, deployment, and outcomes are closely connected with human institutions, cultural contexts, social relationships, and community expectations. Recent scholarship on community-centered AI emphasizes the importance of identifying stakeholder and community values rather than assuming that a universal understanding of human values can adequately represent diverse populations. Community participation can therefore contribute to more context-sensitive and socially legitimate AI systems. Taylor, O’Dell, and Murphy, for example, argue for community-oriented approaches that explicitly incorporate stakeholder values into AI development. Similarly, research on community-centred norm elicitation demonstrates the importance of engaging communities in questions of AI value alignment.

The review further finds that responsible AI requires more than technical accuracy. AI systems operating within communities should respect human dignity, protect privacy, reduce discriminatory outcomes, provide appropriate transparency, preserve meaningful human oversight, and support inclusive participation. International frameworks such as UNESCO’s Recommendation on the Ethics of Artificial Intelligence and the OECD AI Principles reinforce these values by placing human rights, fairness, transparency, safety, accountability, and human agency at the centre of responsible AI.

The paper concludes that the future relationship between AI and contemporary communities should be based on a human- and community-centred approach. AI should complement human capabilities rather than unnecessarily replace human judgment or weaken social relationships. Meaningful participation of communities, interdisciplinary collaboration, ethical governance, cultural sensitivity, and continuous evaluation are therefore essential for ensuring that AI contributes positively to contemporary social life.