This is an online portal with information on donations that were announced publicly (or have been shared with permission) that were of interest to Vipul Naik. The git repository with the code for this portal, as well as all the underlying data, is available on GitHub. All payment amounts are in current United States dollars (USD). The repository of donations is being seeded with an initial collation by Issa Rice as well as continued contributions from him (see his commits and the contract work page listing all financially compensated contributions to the site) but all responsibility for errors and inaccuracies belongs to Vipul Naik. Current data is preliminary and has not been completely vetted and normalized; if sharing a link to this site or any page on this site, please include the caveat that the data is preliminary (if you want to share without including caveats, please check with Vipul Naik). We expect to have completed the first round of development by the end of March 2023. See the about page for more details. Also of interest: pageview data on analytics.vipulnaik.com, tutorial in README, request for feedback to EA Forum.
We do not have any donee information for the donee Andrew Lohn in our system.
|Cause area||Count||Median||Mean||Minimum||10th percentile||20th percentile||30th percentile||40th percentile||50th percentile||60th percentile||70th percentile||80th percentile||90th percentile||Maximum|
|Open Philanthropy (filter this donee)||15,000.00||15,000.00|
Graph of top 10 donors by amount, showing the timeframe of donations
|Donor||Amount (current USD)||Amount rank (out of 1)||Donation date||Cause area||URL||Influencer||Notes|
|Open Philanthropy||15,000.00||1||AI safety||https://www.openphilanthropy.org/focus/global-catastrophic-risks/potential-risks-advanced-artificial-intelligence/andrew-lohn-paper-machine-learning-model-robustness||Luke Muehlhauser||Intended use of funds (category): Direct project expenses
Intended use of funds: Grant "to write a paper on machine learning model robustness for safety-critical AI systems."
Donor reason for selecting the donee: Nothing is specified, but the grantee's work had previously been funded by Open Phil via the RAND Corporation for AI assurance methods.