Participants in recent discussions of AI-related issues ranging from
intelligence explosion to technological unemployment have made diverse claims
about the nature, pace, and drivers of progress in AI. However, these theories
are rarely specified in enough detail to enable systematic evaluation of their
assumptions or to extrapolate progress quantitatively, as is often done with
some success in other technological domains. After reviewing relevant
literatures and justifying the need for more rigorous modeling of AI progress,
this paper contributes to that research program by suggesting ways to account
for the relationship between hardware speed increases and algorithmic
improvements in AI, the role of human inputs in enabling AI capabilities, and
the relationships between different sub-fields of AI. It then outlines ways of
tailoring AI progress models to generate insights on the specific issue of
technological unemployment, and outlines future directions for research on AI
progress.

本研究旨在更加专业地评估 AI 进展的假设和定量推断 AI 的发展，通过硬件速度和算法改进的关系、人类输入对 AI 能力的影响以及不同子领域之间的关系等方面，为 AI 进步模型提供方法，为技术失业问题提供模型依据，并概述未来 AI 进步的研究方向。