Broad Timelines

Abstract

Predicting the onset of transformative artificial intelligence (AI) is characterized by profound uncertainty, rendering single-point estimates or binary “short versus long” debates insufficient for strategic planning. An epistemically humble approach requires adopting broad probability distributions that encompass a wide range of potential arrival dates, often spanning several decades. Expert forecasts and community predictions consistently exhibit heavy-tailed distributions, where even proponents of short timelines acknowledge significant probabilities for much later arrival. Strategic planning must therefore account for divergent scenarios: short timelines necessitate immediate defensive hedging, while longer timelines demand preparation for a fundamentally altered geopolitical and socioeconomic landscape. In extended scenarios, the world may experience shifted regulatory environments, different market leaders, and significant labor market disruptions before civilizational thresholds are met. Consequently, investments in long-term infrastructure—such as field-building, foundational research, and organizational growth—retain substantial expected value. These activities often provide higher leverage in scenarios where AI development is delayed, offsetting the risk that they may not reach fruition in accelerated timelines. Balancing immediate risk mitigation with sustained, compounding efforts ensures a robust portfolio of interventions across the full range of credible AI timelines. – AI-generated abstract.