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 December 2019. 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.
|Effective Altruism Forum username||vipulnaik|
|Effective Altruism Hub username||vipul-naik|
|Data entry method on Donations List Website||Manual (no scripts used)|
|Org Watch page||https://orgwatch.issarice.com/?person=Vipul+Naik|
Miscellaneous notes: Disclosure: creator of the site
|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|
|Global health and development||1||2,000||2,000||2,000||2,000||2,000||2,000||2,000||2,000||2,000||2,000||2,000||2,000||2,000|
If you hover over a cell for a given cause area and year, you will get a tooltip with the number of donees and the number of donations.
Note: Cause area classification used here may not match that used by donor for all cases.
|Cause area||Number of donations||Number of donees||Total||2019||2018||2012||2011||2010||2008||2007|
|Global health (filter this donor)||3||1||8,350.00||0.00||0.00||0.00||0.00||8,350.00||0.00||0.00|
|Education (filter this donor)||1||1||7,500.00||0.00||0.00||0.00||0.00||7,500.00||0.00||0.00|
|Effective altruism (filter this donor)||1||1||4,167.10||4,167.10||0.00||0.00||0.00||0.00||0.00||0.00|
|Global health and development (filter this donor)||1||1||2,000.00||0.00||2,000.00||0.00||0.00||0.00||0.00||0.00|
|(filter this donor)||8||5||1,865.50||0.00||500.00||0.00||0.00||660.00||543.00||162.50|
|Alternate governance (filter this donor)||1||1||520.00||0.00||0.00||0.00||520.00||0.00||0.00||0.00|
|AI safety (filter this donor)||1||1||500.00||0.00||500.00||0.00||0.00||0.00||0.00||0.00|
|Cash transfers (filter this donor)||1||1||500.00||0.00||0.00||500.00||0.00||0.00||0.00||0.00|
Graph of spending by cause area and year (incremental, not cumulative)
Graph of spending by cause area and year (cumulative)
If you hover over a cell for a given subcause area and year, you will get a tooltip with the number of donees and the number of donations.
For the meaning of “classified” and “unclassified”, see the page clarifying this.
|Subcause area||Number of donations||Number of donees||Total||2019||2018||2012||2011||2010|
|Education/low-cost private education in developing world||1||1||7,500.00||0.00||0.00||0.00||0.00||7,500.00|
|Global health and development||1||1||2,000.00||0.00||2,000.00||0.00||0.00||0.00|
Graph of spending by subcause area and year (incremental, not cumulative)
Graph of spending by subcause area and year (cumulative)
|VillageReach (filter this donor)||FB Tw WP Site||8,350.00||0.00||0.00||0.00||0.00||8,350.00||0.00||0.00|
|Undisclosed recipient (filter this donor)||7,500.00||0.00||0.00||0.00||0.00||7,500.00||0.00||0.00|
|EA Hotel (filter this donor)||Effective altruism/housing||Site||4,167.10||4,167.10||0.00||0.00||0.00||0.00||0.00||0.00|
|GiveWell top charities (filter this donor)||Charity evaluation/global health/poverty||FB Tw WP Site||2,000.00||0.00||2,000.00||0.00||0.00||0.00||0.00||0.00|
|Children International (filter this donor)||FB Tw WP Site||1,203.00||0.00||0.00||0.00||0.00||660.00||543.00||0.00|
|The Seasteading Institute (filter this donor)||520.00||0.00||0.00||0.00||520.00||0.00||0.00||0.00|
|Donor lottery (filter this donor)||500.00||0.00||500.00||0.00||0.00||0.00||0.00||0.00|
|GiveDirectly (filter this donor)||Cash transfers||FB Tw WP Site GW||500.00||0.00||0.00||500.00||0.00||0.00||0.00||0.00|
|Machine Intelligence Research Institute (filter this donor)||AI safety||FB Tw WP Site CN GS TW||500.00||0.00||500.00||0.00||0.00||0.00||0.00||0.00|
|Wikimedia Foundation (filter this donor)||WP Site||125.00||0.00||0.00||0.00||0.00||0.00||0.00||125.00|
|Creative Commons (filter this donor)||FB Tw WP Site||25.00||0.00||0.00||0.00||0.00||0.00||0.00||25.00|
|Mozilla Foundation (filter this donor)||FB Tw WP Site||12.50||0.00||0.00||0.00||0.00||0.00||0.00||12.50|
Graph of spending by donee and year (incremental, not cumulative)
Graph of spending by donee and year (cumulative)
If you hover over a cell for a given influencer and year, you will get a tooltip with the number of donees and the number of donations.
For the meaning of “classified” and “unclassified”, see the page clarifying this.
|Influencer||Number of donations||Number of donees||Total||2018||2012||2011||2010||2008||2007|
|Direct online solicitation||3||3||162.50||0.00||0.00||0.00||0.00||0.00||162.50|
Graph of spending by influencer and year (incremental, not cumulative)
Graph of spending by influencer and year (cumulative)
Sorry, we couldn't find any disclosures information.
Sorry, we couldn't find any country information.
|Title (URL linked)||Publication date||Author||Publisher||Affected donors||Affected donees||Document scope||Cause area||Notes|
|My Q1 2019 EA Hotel donation||2019-03-31||Vipul Naik||Effective Altruism Forum||Vipul Naik||EA Hotel||Single donation documentation||Effective altruism/housing||The post documents the author's reasons for making a donation to the EA Hotel. The bulk of the post gives the author's general assessment of the EA Hotel, but the last section gives more details on how the donation decision was made. The author says he likes the idea of the EA Hotel, likes the skin-in-the-game of key players, likes the exevution so far, and finds the value of marginal donations high and easy to grasp. He also explains why the lack of interest from other donors does not dissuade him|
|My 2018 donations||2018-11-23||Vipul Naik||Effective Altruism Forum||Vipul Naik||GiveWell top charities Machine Intelligence Research Institute Donor lottery||Periodic donation list documentation||Global health and development|AI safety||The blog post describes an allocation of $2,000 to GiveWell for regranting to top charities, and $500 each to MIRI and the $500,000 donor lottery. The latter two donations are influenced by Issa Rice, who describes his reasoning at https://issarice.com/donation-history#section-3 Vipul Naik's post explains the reason for donating now rather than earlier or later, the reason for donating this amount, and the selection of recipients. The post is also cross-posted at https://vipulnaik.com/blog/my-2018-donations/ and https://github.com/vipulnaik/working-drafts/blob/master/eaf/my-2018-donations.md|
|Belief status: off-the-cuff thoughts!||2017-01-19||Vipul Naik||Machine Intelligence Research Institute||Reasoning supplement||AI safety||The post argues that (lack of) academic endorsement of the work done by MIRI should not be an important factor in evaluating MIRI, offering three reasons. Commenters include Rob Bensinger, Research Communications Manager at MIRI|
|GiveWell money moved in 2015: a review of my forecast and some future predictions||2016-05-15||Vipul Naik||Effective Altruism Forum||GiveWell GiveWell top charities Against Malaria Foundation GiveDirectly Schistosomiasis Control Initiative Deworm the World Initiative||Miscellaneous commentary||Global health and development||The post is a follow-up to the forecasting post https://forum.effectivealtruism.org/posts/JRZipptLFXvJQEvQh/givewell-money-moved-forecasts-and-implications in light of GiveWell's official report of money moved and web traffic for 2015 at https://blog.givewell.org/2016/05/13/givewells-money-moved-web-traffic-2015/ The post identifies the key reasons for the significant underestimation of money moved in the forecasting post, and some phenomena highlighted by the difference between the forecast and what transpired in reality|
|GiveWell money moved forecasts and implications||2015-12-19||Vipul Naik||Effective Altruism Forum||GiveWell GiveWell top charities Against Malaria Foundation GiveDirectly Schistosomiasis Control Initiative Deworm the World Initiative||Miscellaneous commentary||Global health and development||The blog post includes predictions on how much money GiveWell top charities will raise as part of the 2015 end-of-year giving season|
|Should you donate to the Wikimedia Foundation?||2015-03-28||Vipul Naik||Effective Altruism Forum||Wikimedia Foundation||Evaluator review of donee||Knowledge commons||The post says: "I believe that some of the common arguments people make in favor of the donating to the Wikimedia Foundation (WMF), the non-profit that hosts Wikipedia and a number of its sister sites, are flawed."|
|Evaluating GiveWell as a startup idea based on Paul Graham's philosophy||2014-04-12||Vipul Naik||LessWrong||GiveWell||Miscellaneous commentary||Charity evaluator||The blog post looks at the GiveWell founding story and compares it with essays from Paul Graham on the journeys of successful startups|
|Donee||Amount (current USD)||Amount rank (out of 17)||Donation date||Cause area||URL||Influencer||Notes|
|EA Hotel||4,167.10||3||Effective altruism/housing||https://forum.effectivealtruism.org/posts/BM2DYWpM6rSxyZ7AS/my-q1-2019-ea-hotel-donation||--||Reasoning for donation explained in detail in the blog post. Essentially, the donor liked the idea, skin-in-the-game of key players, execution, and marginal impact, and was not dissuaded by the lack of other funding. The amount listed as donated is based on Fixer.io currency conversion; the actual amount paid out by the donor was $4306.41 USD, including a foreign exchange fee. Percentage of total donor spend in the corresponding batch of donations: 100.00%.|
|GiveWell top charities||2,000.00||4||Global health and development||https://forum.effectivealtruism.org/posts/dznyZNkAQMNq6HtXf/my-2018-donations||GiveWell||In the explanatory blog post, the author says: "For the money directly allocated by me, GiveWell top charities won as a default baseline because the alternatives were not yet compelling enough.". Employer match: LiftIgniter matched 100.00; Percentage of total donor spend in the corresponding batch of donations: 100.00%.|
|Donor lottery||500.00||9||--||https://forum.effectivealtruism.org/posts/dznyZNkAQMNq6HtXf/my-2018-donations||Issa Rice||Donation decided on by Issa Rice. The lottery in question is a $500,000 donor lottery for the end of 2018, as described at https://app.effectivealtruism.org/lotteries/63715163508813 The blog post explaining the donation says: "For each of the years 2017 and 2018, I had given Issa the option of assigning $500 of my money to charitable causes of his choosing (with no strict requirement that these be recognized as charities). In 2017, Issa deferred the use of the money, so he had $1,000 to allocate. Issa ultimately decided to allocate 50% of the $1,000 (i.e., $500) to the $500,000 EA Donor Lottery, and another 50% to the Machine Intelligence Research Institute (MIRI). For the donor lottery, the understanding was that although the entry was under my name, Issa would make the decision as to how to allocate the winnings in the (0.1% probability) event that I win the lottery.". Percentage of total donor spend in the corresponding batch of donations: 50.00%.|
|Machine Intelligence Research Institute||500.00||9||AI safety||https://forum.effectivealtruism.org/posts/dznyZNkAQMNq6HtXf/my-2018-donations||Issa Rice||Donation decided on by Issa Rice. The blog post explaining the donation says: "For each of the years 2017 and 2018, I had given Issa the option of assigning $500 of my money to charitable causes of his choosing (with no strict requirement that these be recognized as charities). In 2017, Issa deferred the use of the money, so he had $1,000 to allocate. Issa ultimately decided to allocate 50% of the $1,000 (i.e., $500) to the $500,000 EA Donor Lottery, and another 50% to the Machine Intelligence Research Institute (MIRI).". Percentage of total donor spend in the corresponding batch of donations: 50.00%.|
|The Seasteading Institute||520.00||8||Alternate governance/seasteading||https://vipulnaik.com/donation-history/||Donor initiative|
|Undisclosed recipient||7,500.00||1||Education/low-cost private education in developing world||https://vipulnaik.com/donation-history/||Donor initiative|
|Children International||660.00||7||--||https://vipulnaik.com/donation-history/||Street sales|
|Children International||--||--||--||https://vipulnaik.com/donation-history/||Street sales||Percentage of total donor spend in the corresponding batch of donations: 100.00%.|
|Children International||125.00||13||--||https://vipulnaik.com/donation-history/||Street sales|
|Children International||418.00||12||--||https://vipulnaik.com/donation-history/||Street sales|
|Wikimedia Foundation||125.00||13||--||https://vipulnaik.com/donation-history/||Direct online solicitation|
|Mozilla Foundation||12.50||16||--||https://vipulnaik.com/donation-history/||Direct online solicitation|
|Creative Commons||25.00||15||--||https://vipulnaik.com/donation-history/||Direct online solicitation|
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