by Luke
Music I most enjoyed discovering this quarter:
by Luke
Music I most enjoyed discovering this quarter:
by Luke
On May 28th, I resigned from the Anthropic Board of Directors (announced here).
Naturally, many people have asked why I resigned. In the wake of many recent safety-related resignations at OpenAI, some have wondered whether my own resignation was safety-related.
It was not. The main reason I resigned is that it became increasingly complicated over time for me to simultaneously be (a) an AI governance grantmaker at Open Philanthropy (my day job), where we support a wide variety of organizations including some who work on US AI policy, and (b) a Board member at a US-based frontier AI company (though I’ve never held any Anthropic equity).
I wish Anthropic the best of luck in its mission, and I continue to think Anthropic’s leadership team takes the challenges of AI safety, security, and public benefit very seriously.
by Luke
Music I most enjoyed discovering this quarter:
I also watched many YouTube “reaction” videos for my two favorite vocal performances of all time: Ankudinova’s “Can’t help falling in love” and Dimash’s “S.O.S.” Lots of warranted shock, goosebumps, speechlessness, and weeping on display. A few examples: one, two, three, four, five, six, seven, eight, nine. YouTuber “Fairy Voice Mother” has excellent explainers on how each performance is achieved technically: Ankudinova, Dimash. You may also enjoy her reaction/analysis for Johnny’s Cash’s “Hurt.”
Another very impressive vocal performance I discovered this quarter is Will Ramos’ “To the Hellfire,” but I can’t exactly say I “enjoy” it, so I didn’t list it above. How many different species of demon do you hear?
by Luke
Music I most enjoyed discovering this quarter:
Music I most enjoyed discovering this quarter:
This quarter, I was reminded that I often like orchestral arrangements of originally non-orchestral pieces (by a different composer). Here are some favorites, most of which I discovered for the first time this quarter [playlist]:
by Luke
Music I most enjoyed discovering this quarter:
by Luke
Music I most enjoyed discovering this quarter:
by Luke
Music I most enjoyed discovering this quarter:
by Luke
Music I most enjoyed discovering this quarter:
by Luke
Music I most enjoyed discovering this quarter:
by Luke
Here’s the main way I think about effective altruism, personally:
In other words, I’m pretty happy with the most canonical definition of effective altruism I know of, from MacAskill (2019), which defines effective altruism as:
(i) the use of evidence and careful reasoning to work out how to maximize the good with a given unit of resources, tentatively understanding ‘the good’ in impartial welfarist terms, and
(ii) the use of the findings from (i) to try to improve the world.
This notion of effective altruism doesn’t demand that you use all your resources to help others. It doesn’t even say that you should use your other-focused budget of resources to help others as much as possible.2 Instead, it merely describes an intellectual project (clause i) and a practical project (clause ii) that some people are excited about but most people aren’t.3
Effective altruism is radically different from many other suggestions for what it looks like to do good or help others.4 True, the portion of resources devoted to helping others may not differ hugely (though it may differ some5 ) between an effective altruist and a non-EA Christian or humanist or social justice activist, since the canonical notion of effective altruism doesn’t take a stance on what that portion should be.6 Instead, effective altruism differs from other approaches to helping others via one or more of its defining characteristics, namely its aspiration to be maximizing, impartial, welfarist, and evidence-based.7
For example, I think it’s difficult for an effective altruist to conclude that the following popular ideas for how to do good or help others are plausible contenders for helping others as much as possible (in an impartial, welfarist, evidence-based way):
Of course, even assuming effective altruism’s relatively distinctive joint commitment to maximization, impartialism, welfarism, and evidence, there will still be a wide range of reasonable debates about which interventions help others as much as possible (in an impartial, welfarist, evidence-based way), just as there will always be a wide range of reasonable debates about any number of scientific questions (and that’s no objection to scientific epistemology).9
Moreover, these points don’t just follow from the canonical definition of effective altruism; they are also observed in the practice of people who call themselves “effective altruists.” For example, EAs are somewhat distinctive in how they debate the question of how best to help others (the debates are generally premised on maximization, welfarism, impartialism, and careful interpretation of whatever evidence is available), and they are very distinctive with regard to which causes they end up devoting the most money and labor to. For example, according to this estimate, the top four EA causes in 2019 by funding allocated were:10
Global health is a fairly popular cause among non-EAs, but farm animal welfare, (existential) biosecurity, and potential (existential) risks from AI are very idiosyncratic. Indeed, I suspect that EAs are responsible for ≥40% of all funding for each of farm animal welfare, potential existential risks from AI, and existential biosecurity.12
Some EAs embrace a more morally demanding version of EA, even though strong moral demandingness is not part of the canonical definition of EA. I applaud and respect these EAs and think they are morally superior to me, but my sense is that they are in the minority of EAs, and of course many other morally-motivated communities also have a minority of practitioners who embrace an especially morally demanding lifestyle. [↩]
by Luke
Music I most enjoyed discovering this quarter:
by Luke
Spotify playlist for this quarter is here. Playlists for past quarters and years here.
Music I most enjoyed discovering this quarter:
by Luke
bold = especially excited
by Luke
Spotify playlist for this quarter is here. Playlists for past quarters and years here.
Music I most enjoyed discovering this quarter:
by Luke
bold = especially excited
by Luke
Over the years, my colleagues and I have spoken to many machine learning researchers who, perhaps after some discussion and argument, claim to think there’s a moderate chance — a 5%, or 15%, or even a 40% chance — that AI systems will destroy human civilization in the next few decades.1 However, I often detect what Bryan Caplan has called a “missing mood“; a mood they would predictably exhibit if they really thought such a dire future was plausible, but which they don’t seem to exhibit. In many cases, the researcher who claims to think that medium-term existential catastrophe from AI is plausible doesn’t seem too upset or worried or sad about it, and doesn’t seem to be taking any specific actions as a result.
Not so with Elon Musk. Consider his reaction (here and here) when podcaster Joe Rogan asks about his AI doomsaying. Musk stares at the table, and takes a deep breath. He looks sad. Dejected. Fatalistic. Then he says:
I tried to convince people to slow down AI, to regulate AI. This was futile. I tried for years. Nobody listened. Nobody listened. Nobody listened… Maybe [one day] they will [listen]. So far they haven’t.
…Normally the way regulations work is very slow… Usually it’ll be something, some new technology, it will cause damage or death, there will be an outcry, there will be an investigation, years will pass, there will be some kind of insight committee, there will be rulemaking, then there will be oversight, eventually regulations. This all takes many years… This timeframe is not relevant to AI. You can’t take 10 years from the point at which it’s dangerous. It’s too late.
……I was warning everyone I could. I met with Obama, for just one reason [to talk about AI danger]. I met with Congress. I was at a meeting of all 50 governors, I talked about AI danger. I talked to everyone I could. No one seemed to realize where this was going.
Moreover, I believe Musk when he says that his ultimate purpose for founding Neuralink is to avert an AI catastrophe: “If you can’t beat it, join it.” Personally, I’m not optimistic that brain-computer interfaces can avert AI catastrophe — for roughly the reasons outlined in the BCIs section of Superintelligence ch. 2 — but Musk came to a different assessment, and I’m glad he’s trying.
Whatever my disagreements with Musk (I have plenty), it looks to me like Musk doesn’t just profess concern about AI existential risk.2 I think he feels it in his bones, when he wakes up in the morning, and he’s spending a significant fraction of his time and capital to try to do something about it. And for that I am grateful.
by Luke
Spotify playlist for this quarter is here. Playlists for past quarters and years here.
Music I most enjoyed discovering this quarter:
by Luke
bold = especially excited