The field of AI research is shifting towards a more holistic understanding of the interplay between technological advancements and societal implications. Recent studies highlight the need for human-centric approaches to AI governance, emphasizing the importance of context-dependent human oversight and ethical considerations. The development of community-based economies, powered by AI and computational technologies, is also gaining attention as a potential path towards more democratic, egalitarian, and sustainable value circulations. Furthermore, researchers are increasingly recognizing the limitations of reductionist approaches to AI impact assessments, advocating instead for a systemic perspective that accounts for the interdependence of tasks, roles, and workplace contexts. Noteworthy papers in this area include:

• 'How to Test for Compliance with Human Oversight Requirements in AI Regulation', which identifies key challenges in testing for compliance with human oversight requirements in AI regulation.
• 'Computing for Community-Based Economies: A Sociotechnical Ecosystem for Democratic, Egalitarian and Sustainable Futures', which proposes a set of core principles for the use of computing in community-based economies.
• 'Assessing employment and labour issues implicated by using AI', which critiques the dominant reductionist approach in AI and work studies and advocates for a systemic perspective.