Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade target for many of the largest AI organisations. Achieving this goal would have profound and far-reaching impacts on human society, which raises many complex questions for the decade ahead. This report investigates how AI itself might continue to develop in a post-AGI world along the continuum of machine intelligence. The endpoint of this continuum, Universal AI, is theoretically well understood, which provides some formal grounding for the main focus of this report: the transition from human-level AGI to artificial general superintelligence, which, intuitively, can be understood as a system that is more intelligent and cognitively capable than large organisations of humans. After characterizing ASI, the report discusses four potential pathways from AGI to ASI: scaling AGI, AI paradigm shifts, recursive improvement, and ASI emerging from large-scale multi-agent collectives. The report then discusses possible frictions and bottlenecks along these pathways. Determining whether the impact of these frictions will be negligible or substantial raises a number of concrete open research questions. Due to large uncertainties for predicting ASI progress, it cannot be ruled out that AI progress might continue to accelerate over the next years. This could imply that the image of a single transformative step change, caused by the introduction of human-level AGI into our society, could be inaccurate. More apt might be the prospect of a series of transformative societal changes caused by AI-enabled progress and breakthroughs across many areas of science and technology. Preparing for this prospect requires a massively interdisciplinary endeavour of global scope and interest.

翻译：过去十年间，构建人类水平的通用人工智能已从遥不可及的推测转变为许多大型人工智能组织未来十年的具体目标。实现这一目标将对人类社会产生深远而广泛的影响，由此引发未来十年中诸多复杂问题。本报告探讨了在通用人工智能时代之后，人工智能自身如何沿着机器智能连续谱系持续发展。该连续谱系的终极目标——通用人工智能——在理论上已得到充分理解，这为本报告的核心关注点提供了形式化基础：即从人类水平通用人工智能向通用人工智能超级智能的过渡。直观上，超级智能可被理解为比大型人类组织更智能、认知能力更强的系统。在界定超级智能后，本报告讨论了从通用人工智能迈向超级智能的四种潜在路径：扩展通用人工智能、人工智能范式转变、递归改进，以及从大规模多智能体集体中涌现超级智能。随后，报告探讨了这些路径中可能存在的摩擦与瓶颈。确定这些摩擦的影响是微不足道还是举足轻重，将引发一系列具体的开放研究问题。由于预测超级智能发展存在巨大的不确定性，不能排除未来几年人工智能进展持续加速的可能性。这意味着因人类水平通用人工智能引入社会而引发的单一变革性跃迁图景可能并不准确。更为贴切的或许是，人工智能驱动的科技进步与突破将在众多科技领域引发一系列变革性的社会变革。为迎接这一前景，需要开展全球范围、全民关注的跨学科大规模协作。