This is a special post for quick takes by Rob Gledhill. Only they can create top-level comments. Comments here also appear on the Quick Takes page and All Posts page.
Curated and popular this week
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*Disclaimer* I am writing this post in a personal capacity; the opinions I express are my own and do not represent my employer.
I think that more people and orgs (especially nonprofits) should consider negotiating the cost of sizable expenses. In my experience, there is usually nothing to lose by respectfully asking to pay less, and doing so can sometimes save thousands or tens of thousands of dollars per hour. This is because negotiating doesn’t take very much time[1], savings can persist across multiple years, and counterparties can be surprisingly generous with discounts. Here are a few examples of expenses that may be negotiable:
For organizations
* Software or news subscriptions
* Of 35 corporate software and news providers I’ve negotiated with, 30 have been willing to provide discounts. These discounts range from 10% to 80%, with an average of around 40%.
* Leases
* A friend was able to negotiate a 22% reduction in the price per square foot on a corporate lease and secured a couple months of free rent. This led to >$480,000 in savings for their nonprofit. Other negotiable parameters include:
* Square footage counted towards rent costs
* Lease length
* A tenant improvement allowance
* Certain physical goods (e.g., smart TVs)
* Buying in bulk can be a great lever for negotiating smaller items like covid tests, and can reduce costs by 50% or more.
* Event/retreat venues (both venue price and smaller items like food and AV)
* Hotel blocks
* A quick email with the rates of comparable but more affordable hotel blocks can often save ~10%.
* Professional service contracts with large for-profit firms (e.g., IT contracts, office internet coverage)
* Insurance premiums (though I am less confident that this is negotiable)
For many products and services, a nonprofit can qualify for a discount simply by providing their IRS determination letter or getting verified on platforms like TechSoup.
In my experience, most vendors and companies
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Forethought[1] is a new AI macrostrategy research group cofounded by Max Dalton, Will MacAskill, Tom Davidson, and Amrit Sidhu-Brar.
We are trying to figure out how to navigate the (potentially rapid) transition to a world with superintelligent AI systems. We aim to tackle the most important questions we can find, unrestricted by the current Overton window.
More details on our website.
Why we exist
We think that AGI might come soon (say, modal timelines to mostly-automated AI R&D in the next 2-8 years), and might significantly accelerate technological progress, leading to many different challenges. We don’t yet have a good understanding of what this change might look like or how to navigate it. Society is not prepared.
Moreover, we want the world to not just avoid catastrophe: we want to reach a really great future. We think about what this might be like (incorporating moral uncertainty), and what we can do, now, to build towards a good future.
Like all projects, this started out with a plethora of Google docs. We ran a series of seminars to explore the ideas further, and that cascaded into an organization.
This area of work feels to us like the early days of EA: we’re exploring unusual, neglected ideas, and finding research progress surprisingly tractable. And while we start out with (literally) galaxy-brained schemes, they often ground out into fairly specific and concrete ideas about what should happen next. Of course, we’re bringing principles like scope sensitivity, impartiality, etc to our thinking, and we think that these issues urgently need more morally dedicated and thoughtful people working on them.
Research
Research agendas
We are currently pursuing the following perspectives:
* Preparing for the intelligence explosion: If AI drives explosive growth there will be an enormous number of challenges we have to face. In addition to misalignment risk and biorisk, this potentially includes: how to govern the development of new weapons of mass destr
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Hey everyone, I’ve been going through the EA Introductory Program, and I have to admit some of these ideas make sense, but others leave me with more questions than answers. I’m trying to wrap my head around certain core EA principles, and the more I think about them, the more I wonder: Am I misunderstanding, or are there blind spots in EA’s approach?
I’d really love to hear what others think. Maybe you can help me clarify some of my doubts. Or maybe you share the same reservations? Let’s talk.
Cause Prioritization. Does It Ignore Political and Social Reality?
EA focuses on doing the most good per dollar, which makes sense in theory. But does it hold up when you apply it to real world contexts especially in countries like Uganda?
Take malaria prevention. It’s a top EA cause because it’s highly cost effective $5,000 can save a life through bed nets (GiveWell, 2023). But what happens when government corruption or instability disrupts these programs? The Global Fund scandal in Uganda saw $1.6 million in malaria aid mismanaged (Global Fund Audit Report, 2016). If money isn’t reaching the people it’s meant to help, is it really the best use of resources?
And what about leadership changes? Policies shift unpredictably here. A national animal welfare initiative I supported lost momentum when political priorities changed. How does EA factor in these uncertainties when prioritizing causes? It feels like EA assumes a stable world where money always achieves the intended impact. But what if that’s not the world we live in?
Long termism. A Luxury When the Present Is in Crisis?
I get why long termists argue that future people matter. But should we really prioritize them over people suffering today?
Long termism tells us that existential risks like AI could wipe out trillions of future lives. But in Uganda, we’re losing lives now—1,500+ die from rabies annually (WHO, 2021), and 41% of children suffer from stunting due to malnutrition (UNICEF, 2022). These are preventable d
I've recently made an update to our Announcement on the future of Wytham Abbey, saying that since this announcement, we have decided that we will use some of the proceeds on Effective Venture's general costs.
Can you give a sense of what proportion? Should we expect 'some' to mean ≤10% or something more significant?
I've heard people express the idea that top of funnel community building is not worth the effort, as EA roles often get 100+ applicants.
I think this is misguided. Great applicants may get a job after only a few applications. Poor applicants may apply to many many jobs without getting a job. As a result you should expect poor applicants to be disproportionately well represented in the applicant pool - hence the pure number of applicants isn't that informative. This point is weakened by recruitment systems being imperfect, but as long as you believe recruitment systems have some ability to select people, then I think this take holds.
I'm really only making a claim about a specific argument, not whether or not top of funnel community building is a good idea on the margin.
H/T Amarins for nudging me to post this
Agreed – my favorite "acceptance rates aren't that meaningful" stat is that Walmart is much more selective than Harvard.
I strongly agree that the reasoning "top of funnel community building is not worth the effort, as EA roles often get 100+ applicants" is misguided. But I think the argument about many applicants being "poor applicants" because they get rejected more often is not that important compared to other reasons.
Here are 3 reasons that I think are much more relevant:
There are many tens of thousands of jobs that are at least as promising as the median "EA role". And after all those are filled by hyper-competent people, there will still be millions more FTE needed just to end: factory farming, easily preventable illness, global poverty, near term x-risks, wild animal suffering, ... (And many would need to do earning to give to fund all the above.)
Reflecting on how to do altruism more effectively can help people in those roles help more (e.g. learning about scope insensitivity, expected value, counterfactual reasoning, the Copenhagen interpretation of ethics, how to make and evaluate a theory of change, cost-effectiveness analyses, radical empathy, longtermism, ...)
Less relevant to your main point, but I strongly want to urge readers against "poor applicants get rejected often" kind of reasoning. I see it very often in this community and I think it's greatly overrated. Some relevant links and thoughts:
This is already super long, but I also want to quickly note that 7.3% of EA-survey-respondents are from one city, which seems to indicate that there might be lots of opportunities for top of funnel community building.
Other examples in this great comment of yours.
This feeds into Jonas’ argument in his recent Quick Take about focusing on talent development rather than community building - focusing on bringing in top potential applicants rather than on the number of people interested in EA jobs