Research direction

Modelling the future of AI

Building models for predicting when and how a transition to a world with advanced AI will occur

We aim to develop quantitative models to elucidate when a transition to a world with advanced AI will occur (AI timelines), and how quickly this transition might play out (AI takeoff dynamics).

The answer to these questions will help inform others about what avenues of work to prioritize. For example, on longer timelines we may want to prioritize building broad scientific and governance capacities that can be leveraged later, while shorter timelines might suggest investing in a suite of focused and targeted strategies for reducing risks.

This line of research involves:

  • Reviewing existing models to forecast AI development and deployment; critically evaluating their assumptions, and assessing their strengths and weaknesses
  • Developing and improving models to forecast AI development and deployment by carefully updating and improving modular components
  • Improving our estimates of key parameters in models of AI development, like the returns to hardware R&D or the growth in AI investment. These estimates can be improved by e.g. reviewing the relevant literature, or gathering relevant data.

Prior work


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