Problem
Research questions and friction points this paper is trying to address.
Artificial General Intelligence
Artificial Superintelligence
ASI transition
machine intelligence continuum
post-AGI development
From AGI to ASI
🤖 AI Summary
This study systematically investigates the critical challenges, evolutionary pathways, and societal implications of advancing from Artificial General Intelligence (AGI) to Artificial Superintelligence (ASI). Addressing the current lack of a theoretical framework for this transition, the work proposes four distinct trajectories: AGI scaling, paradigm shifts in AI architectures, recursive self-improvement, and emergent collective intelligence in multi-agent systems, while delineating the cognitive boundaries of ASI. Through theoretical analysis, computational modeling of intelligence evolution, and interdisciplinary reasoning, the research demonstrates that ASI is more likely to emerge as a sequence of AI-driven breakthroughs across multiple domains rather than a singular discontinuous event. The paper presents the first comprehensive theoretical model of the AGI-to-ASI transition, identifies key bottlenecks and open questions, and outlines a forward-looking research agenda to inform global cooperative governance.
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Artificial Superintelligence
AGI-to-ASI transition
Recursive self-improvement
Multi-agent collectives
AI paradigm shifts
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