substack = nwprtnarrative.substack.com
Executive Director of the Swift Centre for Applied Forecasting (led projects with U.K. Gov., Google DeepMind, and on AI security and capability risks).
Co-founder of ‘Looking for Growth’ - a political movement for growth in the U.K.
CTO of Praxis—a AI led assessment platform for schools
Former Head of Policy at ControlAI (co-authored ‘A Narrow Path’)
Former Director of Impactful Government Careers
Former Head of Development Policy at HM Treasury
Former Head of Strategy at the Centre for Data Ethics and Innovation
Former Senior Policy Advisor at HM Treasury, leading on the economic and financial response to the war in Ukraine, and the modelling and allocation of the UK’s ‘Official Development Assistance’ budget.
MSc in Cognitive and Decision Sciences from UCL, my dissertation was an experimental study using Bayesian reasoning to improve predictive reasoning and forecasting in U.K. public policy officials and analysts
(Copied my comment from the EA Forum and related to my post)
I don’t disagree with some of the fundamentals of this post. Before diving into that, I want to correct a factual error:
“the Swift Centre have received millions of dollars for doing research and studies on forecasting and teaching others about forecasting”
The Swift Centre for Applied Forecasting has not received millions in funding. The majority of our earnings have been through direct projects with organisations who want to use forecasting to inform their decisions.
On your wider argument. I think forecasting has probably received too much funding and the vast majority of that has misallocated on platforms and research. I believe some funding (hundreds of thousands) to maintain core platforms like Metaculus as a public good of information. Though, services like Polymarket can probably fill most of this need in the future (but many useful, informative markets would never reach the necessary volume to be reliable).
Where I think we disagree most is in the application of forecasting and some of the achievements. We’ve worked with frontier AI labs to inform their decisions, are currently advising a U.K. Minister’s team on a central piece of their policy, and are about to start a secondment where I will be advising one of the most influential decision making committees in the country to help improve their scenario analysis and forecasting. Forecasting, and specifically, the science of decision making that it is built on, has the ability to structurally improve decisions in institutions. Significantly better than asking two or three of your smartest friends. That was just never funded, so instead we conclude forecasting is not useful.