Superforecasting
Superforecasting is the art and science of making accurate predictions about future events by employing disciplined, evidence-based methods. It is grounded in probabilistic thinking, intellectual humility, and continuous learning.
Context
- Science: Knowledge about the nature of the world
- Technology: Knowledge about how to change the world
- Investing: Balance capital between Science and Technology
- Industries: Progress of Science and Technology
- Nation States: Optimisation of Assets and Resources
Principles
Below are the main principles and steps to practice superforecasting effectively.
- Think in Probabilities
- Avoid binary predictions; assign probabilities to outcomes and update them as new information arises.
- Use Bayesian reasoning to refine forecasts.
- Break Down Problems Decompose complex questions into smaller, manageable sub-questions (e.g., using Fermi estimation).
- Update Beliefs Dynamically
- Treat beliefs as hypotheses that can be revised based on evidence.
- Embrace "strong opinions loosely held" to adapt quickly to new data.
- Avoid Cognitive Biases Actively counter biases like overconfidence, anchoring, and confirmation bias.
- Balance Perspectives Combine inside views (specific expertise) with outside views (historical data or broader trends).
- Track Accuracy Measure the quality of predictions using tools like Brier scores to identify areas for improvement.
- Be Open-Minded and Humble Recognize the complexity of reality and approach forecasting with intellectual humility.
Process
Backward Reasoning: Imagining an ideal future and reasoning backward to identify potential obstacles or risks that could prevent humanity from achieving that outcome.
Forward Modeling: Reasoning through and modeling what societal, economic, and technological changes are to come. This includes anticipating rapid advancements and their cascading effects.
- Frame questions precisely with specific timeframes and measurable outcomes (e.g., "What is the likelihood of X happening by Y date?").
- Collect diverse data from multiple sources, including historical trends, expert opinions, and current developments.
- Decompose the main question into smaller components to make it more manageable. Example: To estimate a city's EV adoption rate, analyze factors like infrastructure readiness, consumer preferences, and policy incentives.
- Start with a base rate from historical data or similar scenarios before adjusting for current factors.
- Use probabilistic reasoning to estimate the likelihood of each potential outcome.
- Regularly revise forecasts as new information becomes available or circumstances change.
- Keep a record of your reasoning, assumptions, and probability estimates for future review.
- Work in diverse teams to incorporate multiple perspectives and reduce blind spots.
- Evaluate the accuracy of past predictions and refine your process based on lessons learned.
Discipline
Disciplines for Effective Superforecasting:
- Curiosity: Maintain an insatiable desire to understand how systems work and ask "what if" questions.
- Numeracy: Be comfortable working with probabilities and statistical concepts.
- Open-Mindedness: Be willing to consider alternative viewpoints and revise your opinions.
- Resilience: Cultivate grit to persist through uncertainty and setbacks.
- Communication: Share forecasts clearly and collaborate effectively with others.
- Reflection: Regularly review past forecasts to identify strengths and weaknesses in your approach.