EthicsAccountabilityTransparencycs.CY
Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society
Carina Prunkl, Jess Whittlestone
January 13, 2020
AAAI/ACM Conference on AI, Ethics, and Society
26 citations
1 influential
Key Takeaways
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The paper identifies significant ambiguities and inconsistencies in how AI ethics researchers use the "near-term" versus "long-term" distinction, suggesting this common framework may obscure rather than clarify research priorities in the field.
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Rather than a simple binary, the authors propose four distinct dimensions for categorizing AI ethics research, allowing for more precise communication about what different researchers actually prioritize and study—moving beyond the oversimplified near/long-term framing.
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The paper argues that clearer communication about research dimensions could unlock new collaboration opportunities among researchers who may currently seem misaligned but actually share complementary priorities that the near/long-term distinction fails to capture.
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By moving to a more nuanced framework, researchers can develop more consistent and coherent research agendas across the AI ethics community and identify research areas that have been neglected because they don't fit neatly into existing near/long-term categories.
Abstract
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.