📄️ Motivation
The world faces unprecedented challenges, from climate change to safe artificial intelligence, that require billions to trillions of dollars of public goods funding. High-upside/high-uncertainty endeavors are often overlooked due to the absence of strong incentives to pursue them in the dominant public goods funding framework of at-cost grants or even a milestone-bounty framework (which directly exposes small contributors to aversive risk levels). Yet these should be pursued when the expected positive value is very high, as it often is. New impact funding mechanisms can address this. One such mechanism is retrospective funding, which rewards projects based on the impact they create after the impact is observable. If projects can reasonably expect such retrospective rewards, they are incentivized to maximize their impact and – together with prospective funders – take risky bets when the expected positive value is high.
📄️ Defining Impact Funding Systems (IFSs)
An IFS consists of
📄️ Hypercerts as a data layer
In order for impact funding systems to be most effective, they should be interoperable regarding (1) funding mechanisms, (2) funding sources and (3) evaluations. Figure 1 shows a potential dynamic between the actors of an IFS. In that scenario hypercerts can account for the prospective funding (steps 2-3) as well as for the retrospective funding (steps 8-9) from different funders. Evaluations are made public and can be discovered through the hypercerts for all funders (steps 5-7). Retrospective funders can reward not only the contributors but also the prospective funders (steps 10-11).
📄️ Papers, Articles, Presentations
Writings