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One way of carving up the broad "AI ethics and society" research space thathas emerged in recent years is to distinguish between "near-term" and"long-term" research. While such ways of breaking down the research space canbe useful, we put forward several concerns about the near/long-term distinctiongaining too much prominence in how research questions and priorities areframed. We highlight some ambiguities and inconsistencies in how thedistinction is used, and argue that while there are differing priorities withinthis broad research community, these differences are not well-captured by thenear/long-term distinction. We unpack the near/long-term distinction into fourdifferent dimensions, and propose some ways that researchers can communicatemore clearly about their work and priorities using these dimensions. We suggestthat moving towards a more nuanced conversation about research priorities canhelp establish new opportunities for collaboration, aid the development of moreconsistent and coherent research agendas, and enable identification ofpreviously neglected research areas.

Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society