This chapter explores the geopolitics of AI governance from a sustainability perspective. The governance of AI is increasingly hybrid: there is a convergence on some principles and agreed upon challenges. In parallel, we witness the emergence of legally binding instruments, complemented by soft laws. We also analysed a selection of four international organisations’ AI strategies and three national strategies. Concerns identified are the need for common rules precise enough for implementation; navigating risks and benefits in the short and long term; and balancing technological sovereignty and the inherent need for collaboration in AI development. Despite some positive efforts, the current AI governance landscape does not foster sustainability. Ways forward include making large language models a public good accessible to all, supported by the public sector, as well as mainstreaming sustainability approaches in AI development.

The Strategic Research, Innovation, and Deployment Agenda (SRIDA) is a defining framework for the AI, Data, and Robotics Association (Adra) and a forward-looking roadmap for the advancement of AI, data, and robotics (ADR) in Europe. It aims to align ADR research and development efforts, address societal challenges, enhance economic competitiveness, and inform the European Commission’s Horizon Europe work program. This chapter outlines the SRIDA’s purpose and the stakeholders involved and proposes a collaborative methodology based on our practical experience preparing the SRIDA for the past 3 years. It describes the operational framework, including tools, contribution processes, development phases, and iterative updates that ensure the SRIDA evolves in alignment with diverse priorities and voices. The SRIDA’s dynamically evolving nature reflects its commitment to transparency, inclusivity, and balancing technical and non-technical goals. Building on previous SRIDA editions, the chapter examines constraints such as balancing agendas, fostering equitable representation within the ADR community, and aligning immediate objectives with long-term strategies. By addressing open challenges and providing actionable recommendations for future SRIDA iterations, this chapter demonstrates SRIDA’s potential as a driver of Europe’s ADR leadership, paving the way for sustainable innovation.

As artificial intelligence (AI) continues to seep into more areas of society and culture, critical social perspectives on its technologies are more urgent than ever before. Bringing together state-of-the-art research from experienced scholars across disciplines, this Handbook provides a comprehensive overview of the current state of critical AI studies. Moving beyond narrow technological definitions of AI, the Handbook provides readers with an in-depth understanding of its social, ethical and political implications. Chapters cover a broad range of timely issues related to AI, including the risk of bias and discrimination in its systems, its impact on democracy and governance, concerns surrounding privacy and surveillance, and the use of its technologies in decision-making processes. Underscoring the urgent need for deeper critical analyses of AI, the Handbook constitutes a major contribution to the ongoing discussion about what critical studies of AI can entail, what questions they may pose, and what concepts they can offer to address them. Rich in theoretical and empirical analysis, this cutting-edge Handbook will prove an invaluable resource for students and scholars of digital sociology and science and technology studies. Its extensive coverage of this emerging field will also appeal to practitioners, developers and policymakers seeking orientation in the complex social and political dynamics of AI

In this chapter, we situate Sweden in an international context focusing on how programming and computational thinking have been introduced into primary and lower-secondary education (grades 1–9 in the Swedish system). Our review shows that the strategies used in different countries have their own pros and cons, and there is no clear evidence establishing that one method is preferable. Moreover, due to a lack of clear guidelines, decisions on how programming is taught, by whom, and when, are commonly made at school level, also in Sweden. This freedom, or burden, to locally decide on how to implement the curriculum has left teachers in a difficult position, where they are to fulfil the requirements of the curriculum without proper training, time, and competence needed. This has naturally had a negative impact on how programming and computational thinking have been and are introduced at schools. Based on the review we provide six recommendations, which posit that to succeed, a much more systematic and holistic approach is needed, addressing the needs of teachers, students, and schools.

This chapter presents a distributed architecture for unmanned aircraft systems that provides full integration of both low autonomy and high autonomy. The architecture has been instantiated and used in a rotorbased aerial vehicle, but is not limited to use in particular aircraft systems. Various generic functionalities essential to the integration of both low autonomy and high autonomy in a single system are isolated and described. The architecture has also been extended for use with multi-platform systems. The chapter covers the full spectrum of functionalities required for operation in missions requiring high autonomy. A control kernel is presented with diverse flight modes integrated with a navigation subsystem. Specific interfaces and languages are introduced which provide seamless transition between deliberative and reactive capability and reactive and control capability. Hierarchical Concurrent State Machines are introduced as a real-time mechanism for specifying and executing low-level reactive control. Task Specification Trees are introduced as both a declarative and procedural mechanism for specification of high-level tasks. Task planners and motion planners are described which are tightly integrated into the architecture. Generic middleware capability for specifying data and knowledge flow within the architecture based on a stream abstraction is also described. The use of temporal logic is prevalent and is used both as a specification language and as an integral part of an execution monitoring mechanism. Emphasis is placed on the robust integration and interaction between these diverse functionalities using a principled architectural framework. The architecture has been empirically tested in several complex missions, some of which are described in the chapter.

Collaborative robotic systems have much to gain by leveraging results from the area of multi-agent systems and in particular agent-oriented software engineering. Agent-oriented software engineering has much to gain by using collaborative robotic systems as a testbed. In this article, we propose and specify a formally grounded generic collaborative system shell for robotic systems and human operated ground control systems. Collaboration is formalized in terms of the concept of delegation and delegation is instantiated as a speech act. Task Specification Trees are introduced as both a formal and pragmatic characterization of tasks and tasks are recursively delegated through a delegation process implemented in the collaborative system shell. The delegation speech act is formally grounded in the implementation using Task Specification Trees, task allocation via auctions and distributed constraint problem solving. The system is implemented as a prototype on Unmanned Aerial Vehicle systems and a case study targeting emergency service applications is presented.