arXiv:2606.12683cs.AIcs.CY2026-06被引 2

探讨从人类智能到超级智能的演化路径与社会影响

From AGI to ASI

  • 提出四条从AGI走向ASI的可能路径:规模扩展、范式变革、递归改进、多智能体集体涌现
  • 指出未来可能经历一系列渐进式技术突破,而非单一跃迁事件
  • 强调需全球跨学科协作应对超智能带来的复杂挑战

过去十年,构建人类水平的人工通用智能(AGI)已从遥不可及的设想转变为众多顶尖AI机构的十年目标。实现这一目标将对人类社会产生深远影响,引发诸多复杂问题。本报告研究了后AGI时代人工智能自身在机器智能连续体上的发展路径。该连续体的终点——通用人工智能(Universal AI)在理论上已有较好理解,因此本报告聚焦于从人类水平的AGI向人工通用超智能(ASI)的过渡,可直观理解为在认知能力上超越大型人类组织的系统。报告阐述了ASI的特征,并讨论了四条潜在路径:扩展现有AGI、AI范式转变、递归自我改进,以及由大规模多智能体集体涌现的ASI。随后分析了各路径中可能存在的摩擦与瓶颈。这些摩擦的影响是否微不足道或举足轻重,仍是一系列亟待解决的具体研究问题。由于对ASI进展存在巨大不确定性,无法排除未来几年内AI进步将持续加速的可能性。这可能意味着,由人类水平AGI引入社会所导致的单一颠覆性跃迁图景并不准确,更可能是由人工智能驱动的科学与技术多个领域的持续突破引发一系列渐进式社会变革。为此,必须开展大规模跨学科、全球性的准备行动。

原文摘要 · Abstract (English)

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 can intuitively 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.

AGIASI未来展望社会影响

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