  One way of carving up the broad "AI ethics and society" research space that
has emerged in recent years is to distinguish between "near-term" and
"long-term" research. While such ways of breaking down the research space can
be useful, we put forward several concerns about the near/long-term 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 well-captured by the
near/long-term distinction. We unpack the near/long-term 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.
