Introducing A New Open-Source Prediction Registry

post by ozziegooen · 2019-10-16T14:23:47.229Z · LW · GW · 11 comments


  The Main Concept
  Intended Uses
  Select Screenshots

I’m happy to announce a semi-public beta of for the EA/LessWrong community. I’ve spent much of the last year working on coding & development, with lots of help by Jacob Lagerros on product and scoring design. Special thanks to the Long-Term Future Fund and its donors, who’s contribution to the project helped us to hire contractors to do much of the engineering & design.

You can use right away by following this link. Currently public activity is only shown to logged in users, but I expect that to be opened up over the next few weeks. There are currently only a few public communities of predictable questions, but that will change over time.

The Main Concept

We aim for to be useful as a general-purpose prediction registry, with the potential to be used for more specific prediction purposes.

The main features of a prediction registry include things like:

In addition to the essentials, we focused on some other useful features including:

Full distribution forecasts for continuous variables
In, variables are estimated with arbitrary probability distributions. Most existing forecasting tools only allow for binary and categorical binary questions, or relatively simple distributions. saves arbitrary cumulative density functions. The main input editor is a fork of that in Guesstimate. We plan to add more input methods in the future.

“Communities” with custom privacy settings allows for groups to collaborate on forecasting different sets of questions. Communities can be public or private, and question creators can easily move their questions between communities. I’ve talked to several Effective Altruist organizations that have internal forecasting setups, but almost all use in-house solutions with Google Docs. One of the main bottlenecks seems to be easy private community support.

A GraphQL API, with support for bots
Users can create bots that get scored individually. They can use the same GraphQL API that the client uses. You can see information about how to use the API here. This part is still early, but will continue to improve.

In the future we hope that the API will be used to do things like:

Intended Uses

Similar to Guesstimate, itself is not domain-specific. It could be used in multiple kinds of setups; for instance, for personal use, group use, or for a sizable open prediction tournament. Hopefully over the coming years we’ll identify which specific uses and setups are the most promising and optimize accordingly.

Recently it’s been used for:

We encourage broad experimentation. Feel free to make as many public & private communities as you like for different purposes. If you'd be interested in discussing possible details, please reach out.


I’m interested in performing an experiment that could use the tracking of probability distributions. Can I use
Yes! is open-source, and we’re very happy to give special support to researchers and similar interested in working with probability distributions and/or forecasts. It’s made to be reasonably general-purpose and extendable via the API.

To get started, simply create a community on and make a few questions. If you prefer, you can also fork the codebase and run the app separately.

Are you coordinating with other forecasting projects?
In the last few years several efforts and research projects around “forecasting” have emerged, specifically around AI. Most of these are focused on domain-specific research, rather than technical infrastructure. I have been talking with several of the other groups, and have been working particularly closely with Ben Goldhaber and Jacob Lagerros of Parallel Forecast.

Why not just partner with an existing technical forecasting registry and add features to that?
In general, I’ve found that it’s really hard to join a group and get them to dramatically change their priorities. Many of the new additions in are pretty significant, and the roadmap is ambitious.

Is there any connection between and Guesstimate? uses a fork of the distribution editor from Guesstimate. The distribution syntax is the same (“5 to 20”). In the future we plan to make it easy to import variables into Guesstimate, and to use Guesstimate variables for predictions in


Technical details uses Node.js and Express.js with Apollo for the GraphQL server, and ReasonML and React for the client. The database is PostgreSQL. The application is currently hosted on Heroku.

The project has raised $90,000 from the Long-Term Future Fund. Around $25,000 of that has been spent so far, mostly on programming and design help.

Ownership is open source. In the future, I intend for it to be supported via a nonprofit.

Get Involved is free & open to use of all (legal) kinds. That said, if you intend to make serious use of the API, please let me know beforehand.

If you’re interested in collaborating on either the platform, formal experiments, or related research, please reach out to me, either via private message or email ( I’m particularly looking for engineers and people who want to set up forecasting tournaments on important topics.

Select Screenshots

Index View

Question View

Many thanks to Jacob Lagerros, Ondřej Bajgar, and Rose Hadshar for several useful comments on this post


Comments sorted by top scores.

comment by ozziegooen · 2019-10-16T18:56:20.837Z · LW(p) · GW(p)

There are a few curated communities you can join and begin predicting in now. Note you must log in to Foretold before accessing these pages.

Amplifying Spot-Checks
Instructions Document

Elizabeth Van Nostrand [LW · GW] will be evaluating several statements from the book The Unbound Prometheus. Predict how she will judge these statements. You can earn up to $65 per predicted question.

EA Survey 2019&2020
Instructions Document
Predict questions about the upcoming EA surveys. There are two rounds, with multiple cash prizes each.

Apple Inc. Updates Predict things about Apple's new product announcements and stock price.

Slate Star Codex 2019
Scott Alexander made several predictions in the beginning of 2019. Even though 2019 is mostly over, there's still some uncertainty left.

Forecast the karma of this post, and several other things. Feel free to make new questions for posts or parameters you may be interested in.

comment by ioannes (ioannes_shade) · 2019-10-16T15:28:20.378Z · LW(p) · GW(p)


What are the main ways by which is differentiated from Metaculus?

Replies from: ozziegooen
comment by ozziegooen · 2019-10-16T15:54:25.607Z · LW(p) · GW(p)

I believe the items in the "other useful features" section above are unique from Metaculus. There are also lots of other small details. For one, all predictions are visible in Foretold (for people with access to the relevant community), while they are hidden in Metaculus. This could be either a good or bad thing depending on your workflow.

Metaculus has several different features that Foretold does not have. It has a pretty different scoring system. If you're interested in the questions on Metaculus, in particular, then I probably suggest predicting and following them there. I think Metaculus is pretty impressive and the community is quite active.

I could detail all the specific differences, but that doesn't feel right. Both are moving targets, and a breakdown by myself could be biased.

Instead it may help a bit (though this is much more abstract) to attempt to describe the higher-level product philosophies.

Metaculus is a bit like one optimized workflow for one large list of questions. New "clusters" are made by setting up different Metaculus instances, like,

I think Foretold is made with more experimentation of forecasting methods in mind; more exploration instead of exploitation. It's very easy to create private clusters of questions through communities. One downside of the communities model is that it's not well aimed to directing forecasters to one central set of valuable questions.

If you play around with both for a little while, the most of the differences should be obvious.

Foretold is also open source, which can be useful for some who may want to host or fork it.

comment by Matt Goldenberg (mr-hire) · 2019-10-16T19:49:58.929Z · LW(p) · GW(p)

This is excellent! I think this and Guesstimate represent some of the most useful tools to come out of the rationality/EA community, and I'm particularly excited about the inclusion of the GraphQL API.

Thanks for all your hard work.

Replies from: ryan_b
comment by ryan_b · 2019-10-16T21:12:36.750Z · LW(p) · GW(p)

I second this. The architecture of prediction feels like rationality tooling.

Replies from: ozziegooen
comment by ozziegooen · 2019-10-17T12:03:06.326Z · LW(p) · GW(p)

Thanks so much! :)

comment by ioannes (ioannes_shade) · 2019-10-25T17:23:56.533Z · LW(p) · GW(p)

Recently published in Science – Predict science to improve science

The associated platform:

comment by VipulNaik · 2019-10-19T14:41:28.912Z · LW(p) · GW(p)

Directly visiting gives an ERR_NAME_NOT_RESOLVED. Can you make it so that redirects to

Replies from: ozziegooen
comment by ozziegooen · 2019-10-25T17:56:14.217Z · LW(p) · GW(p)

Will do soon, thanks.

Replies from: ozziegooen
comment by ozziegooen · 2019-10-25T19:04:54.539Z · LW(p) · GW(p)

I think it should be fixed now.