Like a collector, I gather resources and information. Storing it and categorizing it. I do this for any project I undertake. But for Forecasting AI Futures, I realized the collection might be quite useful for others.
So, I set to work on restructuring it and make it look nice!
Here is the result: Forecasting AI Futures Resource Hub
The resource hub is still in its infancy but will grow to become more comprehensive over time. If you have ideas for how to improve it—helping it mature into its adult form—they are very welcome.
There are two major parts. The Prediction Database:
And the Forecasting AI Ecosystem:
I’ve also included some of the resources in this post.
Key Links
Some remarks
The prediction database
The current space of predictions
The prediction database highlights where forecasting communities are focusing their attention, and what they are missing. It is a tool for discovering questions that have yet to be asked—and then asking them.
Why a hierarchical structure?
A spreadsheet would have been more flexible than the current hierarchical structure of the database—each prediction could have several tags. It would, however, be harder to include important information in the database, such as links to benchmark leaderboards and other resources. Additionally, I find a hierarchical structure more intuitive—it mirrors my way of thinking about information and forecasting.
Selected predictions
Not every AI-related prediction is included in the database. The ones included reflect what I find meaningful and interesting. I have, however, surely introduced some pointless or vague predictions as well—I have not been extremely prudent with the selection since the database was originally created for personal use. I plan to refine the selections over time.