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Reconciliation between factions focused on near-term and long-term artificial intelligence

Abstract

Artificial intelligence (AI) experts are currently divided into “presentist” and “futurist” factions that call for attention to near-term and long-term AI, respectively. This paper argues that the presentist–futurist dispute is not the best focus of attention. Instead, the paper proposes a reconciliation between the two factions based on a mutual interest in AI. The paper further proposes realignment to two new factions: an “intellectualist” faction that seeks to develop AI for intellectual reasons (as found in the traditional norms of computer science) and a “societalist faction” that seeks to develop AI for the benefit of society. The paper argues in favor of societalism and offers three means of concurrently addressing societal impacts from near-term and long-term AI: (1) advancing societalist social norms, thereby increasing the portion of AI researchers who seek to benefit society; (2) technical research on how to make any AI more beneficial to society; and (3) policy to improve the societal benefits of all AI. In practice, it will often be advantageous to emphasize near-term AI due to the greater interest in near-term AI among AI and policy communities alike. However, presentist and futurist societalists alike can benefit from each others’ advocacy for attention to the societal impacts of AI. The reconciliation between the presentist and futurist factions can improve both near-term and long-term societal impacts of AI.

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Notes

  1. The racial bias Crawford describes comes from the investigative journalism of Angwin et al. (2016).

  2. One can argue that the AI itself is situated within society, and thus that AI researchers inevitably work on societal issues, even when they believe that they are working only on the AI itself. However, for present purposes, what matters is that the AI researchers believe that they are focusing on the AI itself and not on societal issues, even if it can be argued that they are inadvertently working on societal issues.

  3. As just one of many other examples, see Arkin (2009) on societal issues associated with military robotics.

  4. Again, as with any ethical position, the claim that people should help society is not universally held. A broader defense of this claim is beyond the scope of this paper.

  5. The world still has slavery and racism and sexism, but not as much as it once did. For example, while the United States continues to grapple with a variety of racial biases, it has become unthinkable to support the “separate but equal” racial segregation of the former “Jim Crow” laws.

  6. There has also been some legal scholarship focused on long-term AI (e.g., McGinnis 2010; Wilson 2013), but this is a relatively small minority of AI legal scholarship.

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Correspondence to Seth D. Baum.

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Baum, S.D. Reconciliation between factions focused on near-term and long-term artificial intelligence. AI & Soc 33, 565–572 (2018). https://doi.org/10.1007/s00146-017-0734-3

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  • DOI: https://doi.org/10.1007/s00146-017-0734-3

Keywords

  • Artificial intelligence
  • Near-term artificial intelligence
  • Long-term artificial intelligence
  • Societal impacts of artificial intelligence
  • Artificial general intelligence
  • Artificial superintelligence