One can convert the utility-per-researcher into utility-per-dollar by dividing everything by a cost per researcher. So if before you would have 1e-6 x-risk reduction per researcher, and you also decide to value researchers at $1M/researcher, then your evaluation in terms of cost is 1e-12 x-risk per dollar.
For some values (i.e. fake numbers but still acceptable for comparing orders-of-magnitude of cause areas) that I've saw used: The Oxford Prioritisation Project uses 1.8 million (lognormal distribution between $1M and $3M) for a MIRI researcher over their career, 80,000 Hours implicitly uses ~$100,000/year/worker in their yardsticks comparing cause areas, and Effective Altruism orgs in the 2018 talent survey claim to value their junior hires at $450k and senior hires at $3M on average (over three years).
Right. For comparison software engineers (of all kinds, including ML engineers) at early-stage startups generally add between $500k and $1mm to the company's valuation, i.e. investors believe these employees make the company worth buying/selling for that much additional money. There's a lot that goes into where that number comes from, but it does at least suggest that O($1mm) is reasonable.
In MIRI's fundraiser they released their 2019 budget estimate, which spends about half on research personnel. I'm not sure how this compares to similar organizations.
is there a quantitative model for money going to ai safety like this (http://globalprioritiesproject.org/2015/08/quantifyingaisafety/) but for donations ? not including far future utopia effects but just x-risk
Note: This post was crossposted from the Coefficient Giving Farm Animal Welfare Research Newsletter by the Forum team, with the author's permission. The author may not see or respond to comments on this post.
Subtitle: On vegan advocacy, effective altruism, and FIFA
I turn 40 today. Here are some hot takes.
On factory farming
1. Our biggest challenge is salience. If factory farming led the evening news, it wouldn’t last lo...
On October 22nd starting at 10:00am Pacific Time, Every.org is matching donations to select animal welfare organizations at a 2:1 rate, up to $2,000 per donor per nonprofit (so if you give up to $2,000, they will contribute up to $4,000 and the nonprofit will get up to $6,000). The first donation a donor makes to each eligible nonprofit will be matched, and donors can get the match for multiple $2,000 donations. So, you can get more than $2,000 matched by donating $2,000 one time to multiple...
One can convert the utility-per-researcher into utility-per-dollar by dividing everything by a cost per researcher. So if before you would have 1e-6 x-risk reduction per researcher, and you also decide to value researchers at $1M/researcher, then your evaluation in terms of cost is 1e-12 x-risk per dollar.
For some values (i.e. fake numbers but still acceptable for comparing orders-of-magnitude of cause areas) that I've saw used: The Oxford Prioritisation Project uses 1.8 million (lognormal distribution between $1M and $3M) for a MIRI researcher over their career, 80,000 Hours implicitly uses ~$100,000/year/worker in their yardsticks comparing cause areas, and Effective Altruism orgs in the 2018 talent survey claim to value their junior hires at $450k and senior hires at $3M on average (over three years).
ok, im not sure if ai researchers get paid that much though
The cost per researcher is typically larger than what they get paid, since it also includes overhead (administration costs, office space, etc).
Right. For comparison software engineers (of all kinds, including ML engineers) at early-stage startups generally add between $500k and $1mm to the company's valuation, i.e. investors believe these employees make the company worth buying/selling for that much additional money. There's a lot that goes into where that number comes from, but it does at least suggest that O($1mm) is reasonable.
whats the charity overhead for something like miri or fhi?
In MIRI's fundraiser they released their 2019 budget estimate, which spends about half on research personnel. I'm not sure how this compares to similar organizations.