AI for Epistemics is about helping to leverage AI for better truthseeking mechanisms — at the level of individual users, the whole of society, or in transparent ways within the AI systems themselves. Manifund & Elicit recently hosted a hackathon to explore new projects in the space, with about 40 participants, 9 projects judged, and 3 winners splitting a $10k prize pool. Read on to see what we built!

Resources

• See the project showcase: https://moxsf.com/ai4e-hacks
• Watch the recordings: project demos, opening speeches
• See the outline of project ideas: link
  • Thanks to Owen Cotton-Barratt, Raymond Douglas, and Ben Goldhaber for preparing this!
• Lukas Finnveden on “What's important in ‘AI for epistemics’?”: link
• Automation of Wisdom and Philosophy essay contest: link

Why this hackathon?

From the opening speeches; lightly edited.

Andreas Stuhlmüller: Why I'm excited about AI for Epistemics

In short - AI for Epistemics is important [...]

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Outline:

(00:42) Resources

(01:14) Why this hackathon?

(01:22) Andreas Stuhlmüller: Why Im excited about AI for Epistemics

(03:25) Austin Chen: Why a hackathon?

(05:25) Meet the projects

(05:36) Question Generator, by Gustavo Lacerda

(06:27) Symphronesis, by Campbell Hutcheson (winner)

(08:21) Manifund Eval, by Ben Rachbach and William Saunders

(09:36) Detecting Fraudulent Research, by Panda Smith and Charlie George (winner)

(11:14) Artificial Collective Intelligence, by Evan Hadfield

(12:05) Thought Logger and Cyborg Extension, by Raymond Arnold

(14:09) Double-cruxes in the New York Times' The Conversation, by Tilman Bayer

(15:37) Trying to make GPT 4.5 Non-sycophantic (via a better system prompt), by Oliver Habryka

(16:37) Squaretable, by David Nachman (winner)

(17:45) What went well

(20:18) What could have gone better

(22:23) Final notes

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First published:

Source:

Narrated by TYPE III AUDIO.

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