AI systems have become pervasive and deeply integrated into the fabric of social life. As they influence crucial everyday activities and decision-making processes, they hold the power to both support and harm people. Recognizing their dual potential and their sociotechnical nature is essential to rethinking how such systems are designed and how relevant stakeholders interact with them, fostering responsible and trustworthy human–AI interactions.

This topical collection examines how participatory approaches might address risks and limitations in AI-powered technologies by engaging diverse stakeholders in the design process. The collection explores what methods Participatory AI offers for shaping systems that better align with human values and community principles, while critically examining the challenges and tensions that these approaches encounter in practice.

Aim and scope

Drawing on the sociotechnical tradition that conceives social and technical elements as co-constructed, the aim of the collection is to bring together works at the intersection of sociotechnical studies and participatory design, exploring how AI and digital systems can be co-designed to reflect shared values, accountability, and agency. In particular, we welcome contributions that explore how participatory approaches can make AI systems more aligned with, responding to, and driven by specific users, communities, and contexts, rather than pursuing universal solutions. This collection emphasizes the inclusion of stakeholders in the earliest stages of decision-making, including discussions on whether a technology should be developed in the first place—welcoming submissions that ask whether these technologies are truly needed or wanted by communities.

Participatory AI is conceived not as a binary label but as a spectrum of practices and degrees of involvement, encompassing a variety of methods, intensities, and moments of engagement. Participatory approaches provide ways not only to design with and for communities to prevent bias from the outset, but also to perform bias control and mitigation in already deployed or existing AI systems, as well as possibilities of designing by communities. To advance these methods, we are also interested in critical discussions of the tensions and challenges they encounter in practice, such as the resource-intensive nature of genuine participation, how to address power imbalances that persist even in participatory settings, and how to mediate between community and individual values.

A central concern of this collection is ethical and responsible AI design, development, and deployment. Participatory approaches are uniquely positioned to both surface ethical challenges and embed values such as fairness, accountability, and inclusivity directly into the design process, rather than treating ethics as an afterthought. Submissions are expected to engage substantively with these dimensions; manuscripts addressing AI without a specific focus on ethics and/or participatory design are outside the scope of this collection.

Areas of Interest

We welcome technical and non-technical submissions with theoretical, methodological, or experimental contributions, explicitly encouraging interdisciplinary submissions.

Topics of interest include:

• Methods, frameworks, and design solutions for participatory AI (co)design
• Experiments, simulations, prototypes, or case studies of co-design processes in AI development
• Strategies for balancing individual and collective needs in AI design
• Critical reflections on the motivations, challenges, and limitations of participatory approaches
• Analyses of power dynamics and ethical considerations in participatory AI design
• Experiences and lessons learned from co-design and stakeholder engagement
• Assessing AI impacts on diverse stakeholders through participatory approaches and stakeholder engagement

This topical collection is based on the previously organized workshop Mind the AI GAP: Co-designing sociotechnical systems (https://aigap2025.isti.cnr.it/) hosted at the 4th International Conference on Hybrid Human-Artificial Intelligence, 2025, Pisa (Italy) but is also open to other non-listed topics closely aligned with the overall scope of the collection.

This topical collection invites contributions that critically examine how central concepts and theories of AI ethics function when applied to children and adolescents, and where their limits become visible. While terms such as trust, explainability, informed consent, privacy, bias, justice, and well-being are well established in AI ethics, they are usually developed with adult users and decision-makers in view, which means that in contexts concerning children and adolescents they frequently rest on assumptions that do not hold or at least require critical examination.

Children and adolescents encounter AI systems under conditions of developing autonomy, heightened vulnerability, and dependence on others, which does not mean, however, that they are merely passive objects of protection – rather, they possess emerging forms of agency and a moral right to participation and development. Ethical analysis must therefore go beyond simple transfers of adult-centered frameworks and instead ask how AI ethics concepts must be specified, adapted, or fundamentally reconceived in developmentally appropriate and relational ways, whereby it is likely to emerge that such adaptations are not only relevant for children and adolescents but can also enrich the general debate.

We welcome submissions engaging in conceptual and normative analysis, as well as ethically informed empirical work. Contributions may focus on individual concepts, compare different ethical approaches, or explore concrete application contexts, with particular welcome given to work that makes explicit which assumptions about agency, competence, responsibility, or rationality are embedded in existing AI ethics frameworks and how these assumptions are challenged by childhood and adolescence. Also of interest are contributions addressing the question of how AI systems must be designed to meet the particular needs and rights of children and adolescents, or examining what governance structures are required to ensure child-sensitive AI.

Topics

Topics may include, but are not limited to:

• Trust and trustworthiness of AI systems in childhood and adolescence, including questions of overtrust, emotional attachment, and manipulative design strategies

• Explainability and transparency under conditions of developing cognitive capacities, whereby the danger of "explainability washing" must also be considered

• (Informed) consent, shared decision-making, and participation, including the question of how concepts such as transitional paternalism are to be evaluated ethically

• Privacy, surveillance, and data protection for children and adolescents, particularly in the context of digital phenotyping and other data-intensive applications

• Bias, discrimination, and justice affecting marginalized children, whereby intersectional perspectives should also be taken into account

• AI and the well-being of children and adolescents, including the question of socialization effects of AI

• Autonomy development, vulnerability, and dependence in AI-mediated environments, whereby the role of human relationships in an AI-permeated childhood must also be reflected upon

• Ethical governance and child-sensitive AI design, including the question of democratic participation of children and adolescents in decisions about their technological future.

Please find a detailed call for papers and submission guidelines at https://link.springer.com/journal/43681/updates/27841622.