Activism by the AI Community: Analysing Recent Achievements and Future Prospects. The artificial intelligence community (AI) has recently engaged in activism in relation to their employers, other members of the community, and their governments in order to shape the societal and ethical implications of AI. It has achieved some notable successes, but prospects for further political organising and activism are uncertain. We survey activism by the AI community over the last six years; apply two analytical frameworks drawing upon the literature on epistemic communities, and worker organising and bargaining; and explore what they imply for the future prospects of the AI community. Success thus far has hinged on a coherent shared culture, and high bargaining power due to the high demand for a limited supply of AI talent. Both are crucial to the future of AI activism and worthy of sustained attention.

Beyond Near and LongTerm: Towards a Clearer Account of Research Priorities in AI Ethics and Society. One way of carving up the broad AI ethics and society research space that has emerged in recent years is to distinguish between nearterm and longterm research. While such ways of breaking down the research space can be useful, we put forward several concerns about the nearlongterm distinction gaining too much prominence in how research questions and priorities are framed. We highlight some ambiguities and inconsistencies in how the distinction is used, and argue that while there are differing priorities within this broad research community, these differences are not wellcaptured by the nearlongterm distinction. We unpack the nearlongterm distinction into four different dimensions, and propose some ways that researchers can communicate more clearly about their work and priorities using these dimensions. We suggest that moving towards a more nuanced conversation about research priorities can help establish new opportunities for collaboration, aid the development of more consistent and coherent research agendas, and enable identification of previously neglected research areas.