4.6 Article

Mediating artificial intelligence developments through negative and positive incentives

期刊

PLOS ONE
卷 16, 期 1, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0244592

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资金

  1. Future of Life Institute [RFP2-154]
  2. Leverhulme Research Fellowship [RF-2020-603/9]
  3. NOVA LINCS [UIDB/04516/2020]
  4. FCT-Fundacao para a Ciencia e a Tecnologia, Portugal
  5. FCT Portugal [UIDB/50021/2020, PTDC/MAT-APL/6804/2020, PTDC/CCI-INF/7366/2020]
  6. TAILOR - EU Horizon 2020 research and innovation programme [952215]
  7. FuturICT2.0 project - FLAG-ERA JTC 2016
  8. Fundação para a Ciência e a Tecnologia [PTDC/CCI-INF/7366/2020] Funding Source: FCT

向作者/读者索取更多资源

The field of Artificial Intelligence is experiencing great expectations, but also anxiety, driven by a narrative of AI competition that may lead stakeholders to compromise safety measures in order to win. Both positive and negative incentives can influence outcomes, with rewards for following safety measures potentially increasing development speed, while punishment may have unintended consequences like over-regulation. This study provides insights into regulatory actions that can improve safety compliance in the face of technological advancements.
The field of Artificial Intelligence (AI) is going through a period of great expectations, introducing a certain level of anxiety in research, business and also policy. This anxiety is further energised by an AI race narrative that makes people believe they might be missing out. Whether real or not, a belief in this narrative may be detrimental as some stake-holders will feel obliged to cut corners on safety precautions, or ignore societal consequences just to win. Starting from a baseline model that describes a broad class of technology races where winners draw a significant benefit compared to others (such as AI advances, patent race, pharmaceutical technologies), we investigate here how positive (rewards) and negative (punishments) incentives may beneficially influence the outcomes. We uncover conditions in which punishment is either capable of reducing the development speed of unsafe participants or has the capacity to reduce innovation through over-regulation. Alternatively, we show that, in several scenarios, rewarding those that follow safety measures may increase the development speed while ensuring safe choices. Moreover, in the latter regimes, rewards do not suffer from the issue of over-regulation as is the case for punishment. Overall, our findings provide valuable insights into the nature and kinds of regulatory actions most suitable to improve safety compliance in the contexts of both smooth and sudden technological shifts.

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