Alternative models for distributing funding are probably better and are definitely under-explored in EA
I’m particularly optimistic about “impact markets” here, where you get:
countless mostly profit-oriented investors that use their various kinds of localized knowledge (language, domain expertise, connections, flat mates) to fund promising projects and compete with each other on making the best predictions, and
retroactive funders who reward investors and projects that, after some time (say, one or two years), look successful.
That model promises to greatly cut down on the work that funders have to do, and separates the concern “priorities research” or “What does success look like?” from the concern “due diligence” or “What sort of author or entrepreneur is likely to achieve such success and how to find them?”
Fittingly, we, Good Exchange, have received funding through the FTX Regrantor Program and are running our first MVP here.
Note that we started Good Exchange because we were already optimistic about this approach, and that it’s likely the most impactful thing that we can do with our time.
Some other solution concepts that come to mind:
Retrox – an experiment in “democratizing” retroactive funding, where the electorate is one of select experts.
Manifund – an impact market similar to ours but based on Manifold dollars.
Using delegated voting and PageRank to determine weights of experts in votes on funding decisions (Matt Goldenberg and Justin Shovelain have thought more about this)
I’m particularly optimistic about “impact markets” here, where you get:
countless mostly profit-oriented investors that use their various kinds of localized knowledge (language, domain expertise, connections, flat mates) to fund promising projects and compete with each other on making the best predictions, and
retroactive funders who reward investors and projects that, after some time (say, one or two years), look successful.
That model promises to greatly cut down on the work that funders have to do, and separates the concern “priorities research” or “What does success look like?” from the concern “due diligence” or “What sort of author or entrepreneur is likely to achieve such success and how to find them?”
The SFF is using a similar system internally.
Fittingly, we, Good Exchange, have received funding through the FTX Regrantor Program and are running our first MVP here.
Note that we started Good Exchange because we were already optimistic about this approach, and that it’s likely the most impactful thing that we can do with our time.
Some other solution concepts that come to mind:
Retrox – an experiment in “democratizing” retroactive funding, where the electorate is one of select experts.
Quadratic funding without matching pool
Using delegated voting and PageRank to determine weights of experts in votes on funding decisions (Matt Goldenberg and Justin Shovelain have thought more about this)