#37 - GiveWell picks top charities by estimating the unknowable. James Snowden on how they do it.
80,000 Hours Podcast16 Heinä 2018

#37 - GiveWell picks top charities by estimating the unknowable. James Snowden on how they do it.

What’s the value of preventing the death of a 5-year-old child, compared to a 20-year-old, or an 80-year-old?

The global health community has generally regarded the value as proportional to the number of health-adjusted life-years the person has remaining - but GiveWell, one of the world’s foremost charity evaluators, no longer uses that approach.

They found that contrary to the years-remaining’ method, many of their staff actually value preventing the death of an adult more than preventing the death of a young child. However there’s plenty of disagreement: the team’s estimates of the relative value span a four-fold range.

As James Snowden - a research consultant at GiveWell - explains in this episode, there’s no way around making these controversial judgement calls based on limited information. If you try to ignore a question like this, you just implicitly take an unreflective stand on it instead. And for each charity they look into there’s 1 or 2 dozen of these highly uncertain parameters they need to estimate.

GiveWell has been trying to find better ways to make these decisions since its inception in 2007. Lives hang in the balance, so they want their staff to say what they really believe and bring their private knowledge to the table, rather than just defer to a imaginary consensus.

Their strategy is a massive spreadsheet that lists dozens of things they need to estimate, and asking every staff member to give a figure and justification. Then once a year, the GiveWell team get together and try to identify what they really disagree about and think through what evidence it would take to change their minds.

Full transcript, summary of the conversation and links to learn more.

Often the people who have the greatest familiarity with a particular intervention are the ones who drive the decision, as others defer to them. But the group can also end up with very different figures, based on different prior beliefs about moral issues and how the world works. In that case then use the median of everyone’s best guess to make their key decisions.

In making his estimate of the relative badness of dying at different ages, James specifically considered two factors: how many years of life do you lose, and how much interest do you have in those future years? Currently, James believes that the worst time for a person to die is around 8 years of age.

We discuss his experiences with such calculations, as well as a range of other topics:

* Why GiveWell’s recommendations have changed more than it looks.
* What are the biggest research priorities for GiveWell at the moment?
* How do you take into account the long-term knock-on effects from interventions?
* If GiveWell's advice were going to end up being very different in a couple years' time, how might that happen?
* Are there any charities that James thinks are really cost-effective which GiveWell hasn't funded yet?
* How does domestic government spending in the developing world compare to effective charities?
* What are the main challenges with policy related interventions?
* How much time do you spend discovering new interventions?

Get this episode by subscribing to our podcast on the world’s most pressing problems and how to solve them: search for '80,000 Hours' in your podcasting app.

The 80,000 Hours Podcast is produced by Keiran Harris.

Jaksot(325)

#220 – Ryan Greenblatt on the 4 most likely ways for AI to take over, and the case for and against AGI in <8 years

#220 – Ryan Greenblatt on the 4 most likely ways for AI to take over, and the case for and against AGI in <8 years

Ryan Greenblatt — lead author on the explosive paper “Alignment faking in large language models” and chief scientist at Redwood Research — thinks there’s a 25% chance that within four years, AI will b...

8 Heinä 20252h 50min

#219 – Toby Ord on graphs AI companies would prefer you didn't (fully) understand

#219 – Toby Ord on graphs AI companies would prefer you didn't (fully) understand

The era of making AI smarter just by making it bigger is ending. But that doesn’t mean progress is slowing down — far from it. AI models continue to get much more powerful, just using very different m...

24 Kesä 20252h 48min

#218 – Hugh White on why Trump is abandoning US hegemony – and that’s probably good

#218 – Hugh White on why Trump is abandoning US hegemony – and that’s probably good

For decades, US allies have slept soundly under the protection of America’s overwhelming military might. Donald Trump — with his threats to ditch NATO, seize Greenland, and abandon Taiwan — seems hell...

12 Kesä 20252h 48min

#217 – Beth Barnes on the most important graph in AI right now — and the 7-month rule that governs its progress

#217 – Beth Barnes on the most important graph in AI right now — and the 7-month rule that governs its progress

AI models today have a 50% chance of successfully completing a task that would take an expert human one hour. Seven months ago, that number was roughly 30 minutes — and seven months before that, 15 mi...

2 Kesä 20253h 47min

Beyond human minds: The bewildering frontier of consciousness in insects, AI, and more

Beyond human minds: The bewildering frontier of consciousness in insects, AI, and more

What if there’s something it’s like to be a shrimp — or a chatbot?For centuries, humans have debated the nature of consciousness, often placing ourselves at the very top. But what about the minds of o...

23 Touko 20253h 34min

Don’t believe OpenAI’s “nonprofit” spin (emergency pod with Tyler Whitmer)

Don’t believe OpenAI’s “nonprofit” spin (emergency pod with Tyler Whitmer)

OpenAI’s recent announcement that its nonprofit would “retain control” of its for-profit business sounds reassuring. But this seemingly major concession, celebrated by so many, is in itself largely me...

15 Touko 20251h 12min

The case for and against AGI by 2030 (article by Benjamin Todd)

The case for and against AGI by 2030 (article by Benjamin Todd)

More and more people have been saying that we might have AGI (artificial general intelligence) before 2030. Is that really plausible? This article by Benjamin Todd looks into the cases for and against...

12 Touko 20251h

Emergency pod: Did OpenAI give up, or is this just a new trap? (with Rose Chan Loui)

Emergency pod: Did OpenAI give up, or is this just a new trap? (with Rose Chan Loui)

When attorneys general intervene in corporate affairs, it usually means something has gone seriously wrong. In OpenAI’s case, it appears to have forced a dramatic reversal of the company’s plans to si...

8 Touko 20251h 2min

Suosittua kategoriassa Koulutus

rss-murhan-anatomia
voi-hyvin-meditaatiot-2
rss-narsisti
adhd-podi
psykopodiaa-podcast
rss-rahamania
rss-uskonto-on-tylsaa
rss-valo-minussa-2
rss-vapaudu-voimaasi
rss-duodecim-lehti
rss-niinku-asia-on
mielipaivakirja
rahapuhetta
aamukahvilla
ilona-rauhala
kesken
dear-ladies
rss-eron-alkemiaa
nakokulmia-rikollisuudesta-irrottautumiseen
rss-arkea-ja-aurinkoa-podcast-espanjasta