[trigger warning: everything]

What’s the point of any of this?

This is not for the purpose of cause prioritization. Unfortunately, the severity of a problem is not necessarily related to its tractability, especially for lay people looking to donate money or time. If that’s your interest, check out the 80,000 hours problem profiles.

This is also an explicitly short-termist list. There’s no mention of climate change or existential risks. There’s no mention of abstract causes like “failures of international cooperation”, even if these may be the “underlying cause”.

The point is:

• Gain perspective to avoid being distracted by relatively minor heat-of-the-moment crises.
• Provide a corrective against the optimistic Steven Pinker / Our World in Data style worldview
• Motivate myself to work on problems that actually matter

There’s a bit of a tension here. I both believe in the severity of current problems, and the Against Empathy-style argument that we ought to avoid reasoning too much from passions in our attempts to alleviate suffering. Since most of my work is abstract and future-oriented, the severity of concrete and short-term problems forces me to more seriously justify this stance to myself. Maybe that’s a distraction, but I think it’s a worthwhile one.

But aren’t things getting better?

Our World in Data shows decreasing famine mortality, decreasing deaths from genocide, and decreasing deaths from armed conflict.

These are good trends, but they’re no guarantee. Things can always become arbitrarily bad.

There’s also a Omelas-style argument to be made here. The more technologically advanced and glorious human civilization becomes, the worse it is that we allow any level of tragedy to persist. As Scott Alexander put it: “It is glorious that we can create something like this. It is shameful that we did.”

The List

Uyghur genocide
Scale: ~1,000,000+ detained
Type: “Forced abortion, forced sterilization, forced birth control, rape (including gang rape), forced labor, torture, internment, brainwashing, organ harvesting, killings”

Famine in Yemen and Blockade of Yemen
Scale: 85,000 children dead of starvation, 2 million children acutely malnourished, estimated 50,000 new child deaths per year, adults unknown, 24,000,000 people “in need of humanitarian assistance”, 500,000 cases of cholera
Notes: “U.S. is regarded as an indirect partner for Saudi Arabia in the war and blockade on Yemen.”, “UK government has officially supported the Saudi-led coalition”

Rohingya genocide
Scale: 24,000+ dead, 18,000+ rapes, 116,000 beaten, 700,000 – 1,000,000+ refugees
Type: Ethnic and religious persecution, Genocide

COVID-19 pandemic
Scale: ~2,700,000 deaths. 126 million confirmed cases, 780 million estimated cases (October 2020)

Syrian civil war
Scale: 388,652–594,000 deaths, 117,388 civilian deaths, 7,600,000+ internally displaced, 5,116,097+ refugees
See also: Refugees of the Syrian civil war, European migrant crisis

Tigray War and Mai Kadra massacre
Scale: 1000 – 100,000 deaths, ~2,500,000 displaced
Type: Mass killing, Ethnic cleansing

Other
Sinicization of Tibet
Central African Republic Civil War
Democratic Republic of Congo Humanitarian Crisis

Long Lasting (> 10 years)
Crisis in Venezuela
Lord’s Resistance Army insurgency
Colombian conflict
War in Darfur
Papua conflict
Moro conflict
Arab–Israeli conflict
Mexican drug war
Kurdish rebellions in Turkey
Kivu conflict
Kashmir conflict

US Specific
Incarceration in the United States
Scale: 2,200,000 incarcerated, 4,751,400 on probation or parole

Opioid epidemic in the United States
Scale: 399,000 deaths

Intensive animal farming
Annual Scale: 9.2 billion chickens, 124 million pigs, 34 million cows, 3.8 billion finned fish, 43.1 billion shellfish, 23 billion bycatch deaths, 68 billion feed fish
Notes: Non-wikipedia source
See Also: Wild Animal Welfare

Human rights in the United States
Type: “systemic racism,^[15][16][17] weaker labor protections than most western countries,^[18] imprisonment of debtors,^[19] criminalization of homelessness and poverty,^[20][21][22] invasion of its citizens’ privacy through mass surveillance programs,^[23] police brutality,^[24][25] police impunity and corruption,^[26][27] incarceration of citizens for profit, mistreatment of prisoners, the highest number of juveniles in the prison system of any country, some of the longest prison sentences in the world, continued use of the death penalty despite its abolition in nearly all other western countries,^[28] abuse of both legal and illegal immigrants[29][30][31] (including children),^[32][33][34] the facilitation of state terrorism,^[35] a health care system favoring profit via privatization over the wellbeing of citizens,^[36][37] the lack of a universal health care program unlike most other developed countries,^[38] one of the most expensive and worst-performing health care systems of any developed country,^[39] continued support for foreign dictators (even when genocide has been committed),^[40][41] forced disappearances, extraordinary renditions, extrajudicial detentions, the torture of prisoners at Guantanamo Bay and black sites, and extrajudicial targeted killings (e.g. the Disposition Matrix).^{[23][42][43][44]}
See also: Immigration detention in the United States, Human rights violations by the CIA

FAQ

You left out X / You shouldn’t include Y.
Feel free to let me know if I’m missing something, and I’ll consider adding it. The initial list was off the top of my head, so I am probably missing many things.

The (very rough) inclusion criteria is 100,000+ dead, or 1,000,000+ displaced, or an immediate threat of genoicide.

I would like to limit links to Wikipedia or Our World in Data.

This is an evergreen post. It’s linked from the header, and will be updated periodically.

Lambda School Incentives

Google Sheet
Post: Lambda School’s Incredibly Naive Incentive Alignment
Description: Modeling Lambda School’s ISA incentive structure with consideration of taxation. A fully functional California income tax calculator.
Findings: There is only a brief window where student and LS returns grow in tandem. LS is mostly not aligned with students, or actually incentivized against their interests. Based on student outcome data, only around one third of LS students fall within the incentive alignment window.

Independence Referendums

Google Sheet
Post: Base Rates on Secession
Description: Historical data on Independence Referendums from Wikipedia subjected to sensitivity analysis.
Findings: The rate of referendums per country per 4 year period varies by 4x depending on when you start counting. It’s at least 0.01, and at most 0.04 if you start counting right as the Soviet Union collapses.

TSMD and Intel R&D Spending

Google Sheet
Post: Isolated Demands for Rigour in New Optimism
Description: I extend the dataset from Bloom et al.’s Are Ideas Getting Harder to Find? to include 2016-2019 data from 10-K filings, adjusted for exchange rates
Findings: Intel nominal R&D peaked in 2018. TSMC nominal R&D continues to increase exponentially.

Herd Immunity Guesstimate

Google Sheet
Post: Contra StatNews: How Long to Herd Immunity?
Status: Out of date, useful as a template for future modeling.
Description: Toy model of time to herd immunity based on vaccine acceleration, cases per day and different immunity thresholds.

Giving What We Can Growth

Google Sheet
Post: Why Hasn’t Effective Altruism Grown Since 2015?
Description: Scarped archive.org data for GWWC member count, dollars pledged and donations actualized.
Findings: Growth has continued, growth rate peaked in 2015.

Open Philanthropy and Good Ventures Allocation

Google Sheet
Post: Why Hasn’t Effective Altruism Grown Since 2015?
Description: Grant databases from Open Philanthropy and Good Ventures aggregated by focus area and year.
Findings: Both increased rapidly from 2015 to 2017, and have sort of stagnated since. Global Health & Development is around 34% of all Open Philanthropy giving. Scientific Research is another 16%.

Substack Author Experience

Google Sheet
Post: How to Become Famous on Substack Overnight (in Ten Years)
Description: Top 25 free Substack authors from the old leaderboard and the time they’ve spent on Substack. Years of previous experience and notable work for the top 10.
Findings: Top Substack authors have around 10 years of prior experience in research or writing.

Byrne Hobart’s Portfolio

Google Sheet
Post: The Byrne Hobart Portfolio
Description: Scaped stock ticker disclosures from Byrne Hobart’s The Diff. Historical prices at the time of disclosure and performance since.
Findings: Subject to some assumptions, this portfolio dramatically outperformed hedge funds.

Constitutional Amendments

Google Sheet
Post: Wake Up, You’ve Been Asleep for 50 Years
Description: Proposal date of constitutional amendments that were later successfully ratified.
Findings: There were long gaps with no proposals leading to ratification from 1804 – 1865, 1870 – 1909 and 1972 – present.

Founders of Top 10 YC Startups

Google Sheet
Post: Replying to Robert Wiblin on Young Rationalists, Empirical Estimates of Golden Handcuffs
Description: Investigation into the backgrounds of top YC founders as ranked here.
Findings: Median age at founding was 27, median age now is 37. Median age of startup is 9 years. Founders attend elite universities, but don’t typically work at large or prestigious companies.

Google Alumni Estimate

Google Sheet
Post: Empirical Estimates of Golden Handcuffs
Description: Based on historical headcount data and simulated churn, I estimate how many people have ever worked at Google up through 2010.
Findings: Although Google’s employee count in 2010 was 24,400, I estimate there were an additional 25,400 ex-Google employees.

Model of Correlated Returns

Google Sheet
Post: Correlated Returns are Insufficient for True Alignment
Description: Modeling correlated returns in domains without proper incentive alignment, followed by seemingly correlated returns adjusted for opportunity cost.

Miike vs Tarantino

Google Sheet
Post: No One is Even Trying
Description: Rotten Tomatoes critic and audience score for the top 10 movies of Takashi Miike and Quentin Tarantino.
Findings: Miike’s top 10 movies are as well reviewed as Tarantino’s. Meanwhile, Miike has made 10 times as many movies overall.

This is an evergreen post. It’s linked from the header, and will be updated periodically. If I’ve made mistakes not listed here, let me know and I’ll issue a correction.

Vaccine Acceptance

Post: Was Vaccine Production Actually Delayed?
Summary: I wrote that historical ills, including the Tuskegee study may play a role in diminishing vaccine acceptance. Two links from Marginal Revolution (1, 2) indicate that there is no link.
Severity: Minor. This was an appendix to the post, and not central to the argument. Both links are to article published after my post, but one references this study published in 2007. So it only has a minor impact on my argument, but I am moderately embarrassed.

Techno-Pessimism

Post:: Isolated Demands for Rigour in New Optimism
Summary: Noah Smith is currently on part 3 of a 4 part rebuttal. I haven’t taken a good look yet, but will write a response if appropriate once the series is complete.

Substack

Post: How Substack Became Milquetoast

Type: Factual errors.
Summary: I wrote that Substack had 44 employees based on their LinkedIn profile. Nadia corrected me, they only had 17 employees at the time.
Severity: This weakens my argument that Substack has failed to use it’s immense resources effectively, but does not defeat the central thesis and is only mentioned in an epilogue to the main article.
Response: The article is corrected, with the original error preserved for posterity. An apology was issued over email.

Type: Punching down.
Summary: When I wrote this article, Substack was widely hyped, and had received little substantial criticism. Since then, they have been the subject of various critiques, some of them quite poor. As a result, I somewhat regret associating with this side of the argument. See for example, the misleading NYT headline The Site Trump Could Run To Next, and Here’s why Substack’s scam worked so well. My critique was focused on Substack as a replacement for eclectic blogs. I neglected to mention that it seems to be a much better replacement for op-ed pieces, and many of my criticisms do not apply in this capacity.

Effective Altruism Slowing Down

Post: Why Hasn’t Effective Altruism Grown Since 2015?
Type: Incomplete analysis.
Summary: Katja Grace wrote a reply, pointing out that I neglected several pieces of evidence pointing at continued growth. She was kind enough to email this to me directly.
Response: I wrote a reply here, agreeing with many of Katja’s points, but defending the bulk of my original piece.

Effective Altruism Shifting Priorities

Post: Responses and Testimonies on EA Growth
Type: Misattribution.
Summary: Scott Alexander wrote this comment, which I attempted to summarize in a follow up post. He then wrote that my summary of his position did not accurately capture his views.
Response: The summary was amended, and a retraction was added as a footnote.

S&P Annualized Returns

Post: The Byrne Hobart Portfolio
Type: Factual error.
Summary: I wrote that the S&P had returned “113.7% annualized since the May 2020 bottom”. The bottom was in March, not in May, giving annualized returns of 76.6%, not 113.7%.
Severity: Minor. The article is about how good Byrne’s portfolio is, and the mistake only strengthens this stance.
Response: This is corrected in the article. The original mistake is preserved and noted.

Forecasting Herd Immunity

Post: Contra StatNews: How Long to Herd Immunity?

Type: Misinterpreting evidence.
Summary: I wrote that antibodies only last 8 months. Alvaro noted that the papers actually indicate antibodies lasting at least 8 months.
Severity: Moderate. This alters projections by 1-2 weeks depending on other parameters. I was careful to list out model assumptions, but had said that antibody duration was among my more confident assumptions. There is an “Speculative armchair epidemiology” warning at the top of the article. This does not affect the central criticism of the original Stat News article. I repeatedly noted that the estimates should not be taken too seriously.
Response: This is noted in the article with a detailed correction.

Type: Mistaken assumptions.
Summary: Despite having previously summarized the survey data on vaccine acceptance, I neglected to realize just how low it would continue to be. I also forecasted 200,000 new confirmed cases per day, but they have since dropped drastically.
Severity: Moderate/Low. I didn’t account for low vaccine acceptance, or the lack of a vaccine for children. I did note that daily confirmed cases was my lowest confidence assumption.
Response: None.

Age of Top YC Founders

Post: Replying to Robert Wiblin on Young Rationalists
Type: Factual error.
Summary: I got a couple ages wrong in the original spreadsheet. Mean/median age at founding was previously listed as 26, but is actually 27. Mean/median age in 2020 was listed as 36 and 35, but are actually both 37. Thanks to Gytis Daujotas for catching these.
Severity: Minor. Ages are off by 1 or 2 years, which slightly weakens my argument.
Response: The post and data has been corrected, with the original mistake noted.