Are AI Capabilities Increasing Exponentially? A Competing Hypothesis
This addresses forecasting uncertainties in AI capabilities, which impact safety and labor markets, but is incremental as it critiques existing models without providing new rigorous forecasts.
The authors challenge the claim that AI capabilities are growing exponentially, arguing that data does not support this even in short-term horizons and that inflection points may have already passed or are near, based on fitting sigmoid curves and proposing a decomposed model.
Rapidly increasing AI capabilities have substantial real-world consequences, ranging from AI safety concerns to labor market consequences. The Model Evaluation & Threat Research (METR) report argues that AI capabilities have exhibited exponential growth since 2019. In this note, we argue that the data does not support exponential growth, even in shorter-term horizons. Whereas the METR study claims that fitting sigmoid/logistic curves results in inflection points far in the future, we fit a sigmoid curve to their current data and find that the inflection point has already passed. In addition, we propose a more complex model that decomposes AI capabilities into base and reasoning capabilities, exhibiting individual rates of improvement. We prove that this model supports our hypothesis that AI capabilities will exhibit an inflection point in the near future. Our goal is not to establish a rigorous forecast of our own, but to highlight the fragility of existing forecasts of exponential growth.