2020/01/13 by Carina Prunkl, Jess Whittlestone, Prunkl, Carina +1 · 1 citation
Computer Science · Neuroscience · Social Sciences · #Artificial Intelligence (cs.AI) #Blockchain Technology Applications and Security #Computers and Society (cs.CY) #Ethics and Social Impacts of AI #FOS: Computer and information sciences #Neuroethics, Human Enhancement, Biomedical Innovations
paper · pdf · doi:10.48550/arxiv.2001.04335
openalex publication_date 2020/01/13 · openalex created_date 2020/01/23 · openalex updated_date 2026/07/28
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.