New replication: I find that the results in Moretti (AER 2021) are caused by coding errors.
The paper studies agglomeration effects for innovation, but the results supporting a causal interpretation don't hold up.
https://twitter.com/michael_wiebe/status/1749462957132759489
Tweet-thread promoting Rotblat Day on Aug. 31, to commemorate the spirit of questioning whether a dangerous project should be continued.
Should you "trust literatures, not papers"?
I replicated the literature on meritocratic promotion in China, and found that the evidence is not robust.
https://twitter.com/michael_wiebe/status/1750572525439062384
What AI safety work should altruists do? For example, AI companies are self-interestedly working on RLHF, so there's no need for altruists to work on it. (And even stronger, working on RLHF is actively harmful because it advances capabilities.)
Has anyone looked at the effect of air pollution on animal welfare (farmed or wild)?
What does longtermism add beyond the importance-tractability-crowdedness framework? According to the ITC framework, we allocate resources to interventions with the highest expected value, given current funding levels. (More precisely, allocate the next dollar to the intervention with the highest marginal utility per dollar.) If those interventions turn out to be aimed at helping future generations, so what?
So far, the effective altruist strategy for global poverty has followed a high-certainty, low-reward approach. GiveWell only looks at charities with a strong evidence base, such as bednets and cash transfers. But there's also a low certainty, high reward approach: promote catch-up economic growth. Poverty is strongly correlated with economic development (urbanization, industrialization, etc), so encouraging development would have large effects on poverty. Whereas cash transfers have a large probability of a small effect, economic growth is a small probability of a large effect. (In general, we should diversify across high- and low-risk strategies.) In short, can we do “hits-based development”?
How can we affect growth? Tractability is the main problem for hits-based development, since GDP growth rates are notoriously difficult to change. However, there are a few promising options. One specific mechanism is to train developing-country economists, who can then work in developing-country governments and influence policy. Lant Pritchett gives the example of a think tank in India that influenced its liberalizing reforms, which preceded a large growth episode. This translates into a concr... (read more)
Do vaccinated children have higher income as adults?
I replicate a paper on the 1963 measles vaccine, and find that it is unable to answer the question.
https://twitter.com/michael_wiebe/status/1750197740603367689
How much do non-nuclear countries exert control over nuclear weapons? How would the US-Soviet arms race have been different if, say, African countries were all as rich as the US, and could lobby against reckless accumulation of nuclear weapons?
What is the definition of longtermism, if it now includes traditional global health interventions like reducing lead exposure?
Will MacAskill says (bold added):
... (read more)Well, it’s because there’s more of a rational market now, or something like an efficient market of giving — where the marginal stuff that could or could not be funded in AI safety is like, the best stuff’s been funded, and so the marginal stuff is much less clear. Whereas something in this broad longtermist area — like reducing people’s exposure to lead, improving brain and other health development —
Longtermism is the view that positively influencing the longterm future is a key moral priority of our time.
Longtermism is a conclusion we arrive at by applying the EA framework of importance-tractability-crowdedness (where 'importance' is defined to include valuing future lives). Hence, EA is primary, and longtermism is secondary. EA tells us how to manage tradeoffs between benefitting the far future and doing good in the near term, and how to change our behavior as longtermist interventions hit diminishing returns.
Strong waterism: dying of thirst is very bad, because it prevents all of the positive contributions you could make in your life. Therefore, the most important feature of our actions today is their impact on the stockpile of potable water.
in order to assess the value (or normative status) of a particular action we can in the first instance just look at the long-run effects of that action (that is, those after 1000 years), and then look at the short-run effects just to decide among those actions whose long-run effects are among the very best.
Is this not laughable? How could anyone think that "looking at the 1000+ year effects of an action" is workable?
If humanity goes extinct this century, that drastically reduces the likelihood that there are humans in our solar system 1000 years from now. So at least in some cases, looking at the effects 1000+ years in the future is pretty straightforward (conditional on the effects over the coming decades).
In order to act for the benefit of the far future (1000+ years away), you don't need to be able to track the far future effects of every possible action. You just need to find at least one course of action whose far future effects are sufficiently predictable to guide you (and good in expectation).
Does longtermism vs neartermism boil down to cases of tiny probabilities of x-risk?
When P(x-risk) is high, then both longtermists and neartermists max out their budgets on it. We have convergence.
When P(x-risk) is low, then the expected value is low for neartermists (since they only care about the next ~few generations) and high for longtermists (since they care about all future generations). Here, longtermists will focus on x-risks, while neartermists won't.
Crowdedness by itself is uninformative. A cause could be uncrowded because it is improperly overlooked, or because it is intractable. Merely knowing that a cause is uncrowded shouldn't lead you to make any updates.
I've written up my replication of Cook (2014) on racial violence and patenting by Black inventors.
Bottom line: I believe the conclusions, but I don't trust the results.
https://twitter.com/michael_wiebe/status/1749831822262018476
We need to drop the term "neglected". Neglectedness is crowdedness relative to importance, and the everyday meaning is "improperly overlooked". So it's more precise to refer to crowdedness ($ spent) and importance separately. Moreover, saying that a cause is uncrowded has a different connotation than saying that a cause is neglected. A cause could be uncrowded because it is overlooked, or because it is intractable; if the latter, it doesn't warrant more attention. But a neglected cause warrants more attention by definition.
Mor... (read more)
FTX Future Fund says they support "ambitious projects to improve humanity's long-term prospects". Does it seem weird that they're unanimously funding neartermist global health interventions like lead elimination?
... (read more)Lead Exposure Elimination Project. [...] So I saw the talk, I made sure that Clare was applying to [FTX] Future Fund. And I was like, “OK, we’ve got to fund this.” And because the focus [at FTX] is longtermist giving, I was thinking maybe it’s going to be a bit of a fight internally. Then it came up in the Slack, and everyone w
How to make the long-term future go well: get every generation to follow the rule "leave the world better off than it was under the previous generation".
asteroid detection [...] approximately 300,000 additional lives in expectation for each $100 spent. [...]
Preventing future pandemics [...] 200 million extra lives in expectation for each $100 spent. [...]
the best available near-term-focused interventions save approximately 0.025 lives per $100 spent
(source)
We should have a dashboard that tracks expected value per dollar for each cause area. This could be measured in lives saved, QALYs, marginal utility, etc, and could be measured per $1, $100, $1M, etc. We'd also want an estimate of diminishing retur... (read more)
Longtermism is defined as holding that "what most matters about our actions is their very long term effects". What does this mean, formally? Below I set up a model of a social planner maximizing social welfare over all generations. With this model, we can give a precise definition of longtermism.
Consider an infinitely-lived representative agent with population size Nt. In each period there is a risk of extinction via an extinction rate δt.
The basic idea is that economic growth is a double-edged sword: it inc... (read more)
What are the comparative statics for how uncertainty affects decisionmaking? How does a decisionmaker's behavior differ under some uncertainty compared to no uncertainty?
Consider a social planner problem where we make transfers to maximize total utility, given idiosyncratic shocks to endowments. There are two agents, A and B, with endowments eA=5 (with probability 1) and eB=0∼p,10∼1−p. So B either gets nothing or twice as much as A.
We choose a transfer T to solve:
maxT u(5−T)+p⋅u(0+T)+(1−p)⋅u... (read more)
The argument for longtermism in a nutshell:
First, future people matter. [...] Second, the future could be vast. [...] Third, our actions may predictably influence how well this long-term future goes.
Here, whether longtermism ("positively influencing the long-term future is a key moral priority of our time") is true or false depends on whether our actions can predictably influence the far future. But it's bad to collapse such a rich topic down to a binary true/false. (Imagine having a website IsInfluencingTheLongTermFutureAKeyMoralPriority.com to tell you w... (read more)
'Longtermism' is the view that positively influencing the long-term future is a key moral priority of our time. [from here]
It seems weird to make an 'ism' out of a currently highly cost-effective cause area. On the ITC framework, we expect these interventions to become less cost-effective as funding is directed to them and they hit diminishing returns and become less tractable. That is, if the EA community is functioning properly, the marginal dollar allocated to each cause will have the same effectiveness (otherwise, we could reallocate funding and do mor... (read more)
Why don't models of intelligence explosion assume diminishing marginal returns? In the model below, what are the arguments for assuming a constant ω, rather than diminishing marginal returns (eg, ωt→−∞). With diminishing returns, an AI can only improve itself at a dimishing rate, so we don't get a singularity.
https://www.nber.org/papers/w23928.pdf
What are the comparative statics for how uncertainty affects decisionmaking? How does a decisionmaker's behavior differ under some uncertainty compared to no uncertainty?
Consider a social planner problem where we make transfers to maximize total utility, given idiosyncratic shocks to endowments. There are two agents, A and B, with endowments eA=5 (with probability 1) and eB=0∼p,10∼1−p. So B either gets nothing or twice as much as A.
We choose a transfer T to solve:
maxT u(5−T)+p⋅u(0+T)+(1−p)⋅u(10+T) s.t. 0≤T≤5
For a baseline, consider p=0.5 and u=ln. Then we get an optimal transfer of T∗=1.8. Intuitively, as p→0, T∗→0 (if B gets 10 for sure, don't make any transfer from A to B), and as p→1,T∗→2.5 (if B gets 0 for sure, split A's endowment equally).
So that's a scenario with risk (known probabilities), but not uncertainty (unknown probabilities). What if we're uncertain about the value of p?
Suppose we think p∼F, for some distribution F over [0,1]. If we maximize expected utility, the problem becomes:
maxT E[u(5−T)+p⋅u(0+T)+(1−p)⋅u(10+T)] s.t. 0≤T≤5
Since the objective function is linear in probabilities, we end up with the same problem as before, except with E[p] instead of p. If we know the mean of F, we plug it in and solve as before.
So it turns out that this form of uncertainty doesn't change the problem very much.
Questions:
- if we don't know the mean of F, is the problem simply intractable? Should we resort to maxmin utility?
- what if we have a hyperprior over the mean of F? Do we just take another level of expectations, and end up with the same solution?
- how does a stochastic dominance decision theory work here?
I think we can justify ruling out all options the maximality rule rules out, although it's very permissive. Maybe we can put more structure on our uncertainty than it assumes. For example, we can talk about distributional properties for p without specifying an actual distribution for p, e.g. p is more likely to be between 0.8 and 0.9 than 0.1 and 0.2, although I won't commit to a probability for either.