Charles Dillon

Experienced quant trader. Currently a volunteer at Rethink Priorities, mostly focused on forecasting research.

Wiki Contributions


The importance of optimizing the first few weeks of uni for EA groups

I've seen it in highly trafficked central areas in Trinity College in Dublin, though usually there's some upcoming catalyst for it like an event in the near future.

An analysis of Metaculus predictions of future EA resources, 2025 and 2030

It is definitely easier - the answer is more one dimensional, and for continuous questions there's a lot more going back and forth between the cumulative distribution function and the probability density function, and thinking about corner cases.

E.g. For "When will the next supreme court vacancy arise" vs "will there be a vacancy by [year]", in the former case you have to think about when a decision to retire might be timed, in the latter you just need to think about whether the judge will do it.

Other mechanisms - it's possible the average binary question is more interesting or attention grabbing.

As for your second question, I looked at all the questions from 2019 and 2020 just now, and the median number of unique predictors on a binary question was 75, vs 38 for a continuous one. The mean was 97 vs 46. But this does not control for the questions being different. There were 942 continuous questions over the time window and 727 binary questions.

Suggested norms about financial aid for EAG(x)

The tax point is particularly relevant. I felt obliged to pay for a ticket previously as a high earner, but it felt odd and somewhat performative to do so when the net effect of donating directly to movement building instead seemed clearly better because the donation could be increased by doing so.

APPLY NOW | EA Global: London (29-31 Oct) | EAGxPrague (3-5 Dec)

It is a little more vague than that. It means (at least as I interpret it) something like 'there currently exists $46bn which Ben Todd thinks is quite committed to eventually being spent to improve the world using an EA framework of trying to do the most good'

Most of those assets currently belong to Dustin Moskovitz and Sam Bankman-Fried

Promoting Simple Altruism

Some questions this post made me realise I didn't have answers to, which seem useful to have answers to and there may be research in this somewhere already:

  • What  attempts have been made to motivate people to be more altruistic, and did any of  them work?
  • Is there much effort being made to do this currently besides specific charity advocacy? What would this look like
  • Has anyone studied the effect of more charity advertising/advocacy and whether it diverts money which would have been donated anyway or causes extra money to be donated?

It seems to me that knowing the answers to these questions might help me judge whether this area is something I think EAs should be pursuing. I may look into these myself in the next few days but I'm putting them here in case someone already knows relevant info about the topic.

How much money donated and to where (in the space of animal wellbeing) would "cancel out" the harm from leasing a commercial building to a restaurant that presumably uses factory farmed animals?

Epistemic status: extremely rough model, please don't take too seriously, just trying to get ballpark estimates which someone might correct me on

It seems like there are a few considerations here:

  1. Would this create a restaurant which would otherwise not exist, or a restaurant which would sell more meals than it otherwise would if it were in a different location?
  2. If so, how many extra animals would be factory farmed?

For (i), if the rent you can get for a restaurant is higher than for a non-restaurant business then it seems like the market is implying the "best" (financial) use of the space is as a restaurant, suggesting the answer to (i) is at least in part yes.

For (ii), this suggests 12-15 sq ft per diner and assuming 70% of the area is dining space you get approx 300 diners at one time. Lets say 1000/day at capacity. If they eat more meat than they would at home (intuitively I guess they would but this is small, i can't find any source on this).

Lets imagine you get an extra 100 people/day eating out once from this decision, and they eat 25% more meat than they otherwise would. Then the average person in the US eats 100kg of meat a year or 270g/day. An extra 25% is about 60g or about 0.06 chickens, 0.001 pigs or  0.0003 cows (based on numbers I got from a quick google) so you get ~2100 extra chickens, ~11 extra cows or ~35 extra pigs  a year. If the restaurant is a chicken restaurant then this is clearly much more weighted towards chickens, and in fact if it causes people to eat chicken if they would've eaten beef at home, this is an underestimate. Let's use 2100 chickens for now.

There are not very precise estimates available for how effective animal interventions are, but this by Rethink Priorities in 2019 suggests corporate campaigns such as those by the Humane League saved 120 chickens per dollar from broiler cages (with extremely wide error bars). If subsequent campaigns are 10x less effective (I don't know what a good estimate is here but I'd guess future campaigns will be less effective than past ones as they hit diminishing returns) then you get 12 per dollar, or 2100 chickens with better quality of life for $175. If you think non caged lives are 10% better than caged lives this would be more like $1750 to offset the harm I estimate here.

[PR FAQ] Sharing readership data with Forum authors

I would find this very useful. My two longest posts did well karma wise but neither received any comments, and it would be valuable to know whether people are actually reading them through to the end.

For reading time, how does this work for a page I have opened in a new tab but don't look at for several hours? Is it able to tell if I've actually got that page active?

One other thing:

How does the viewership data count multiple views from the same person?

We only share unique views; if you see that your post has 100 views, that means it was viewed from 100 different (logged-in Forum accounts + unique IP addresses from readers who weren't logged in).

Seeing the values for each of "logged in user" and "unique IP" (i.e. non logged in users) would be nice. For example, one of my posts was shared on ACX and I expect it had far more viewership from non-regular forum users than my other posts, it would be convenient to see this.

On what kinds of Twitter accounts would you be most interested in seeing research?

Specifically when looking at policy related stuff, I like to look at whether they are being followed by very good forecasting people, as that's an indication to me that their posts contain a lot of decision relevant information / that they have higher than average epistemic standards.

There's a pretty big overlap between the forecasting people and EA folk though.

Thoughts on being overqualified for EA positions

Strongly agree with this, as someone who had approximately the level of responsibility Khorton described until recently.

In my industry (quant trading) the extra value of further experience to outside goals past the level I've already reached is limited except potentially as a status signal.

Predicting Open Phil Grants

Agreed, and changed, though I preferred "grants" to "grant amounts"

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