Cross-posted from LessWrong after a friend finally convinced me. Lighter reading here
Last month, Julia Galef interviewed Vitalik Buterin. Their responses to Glen Weyl’s critiques of the EA community struck me as missing perspectives he had tried to raise.
So I emailed Julia to share my thoughts. Cleaned-up text:
Personally, I thought Vitalik’s and your commentary on Glen Weyl’s characterisation of the EA and rationality community missed something important.
Glen spent a lot of time interacting with people from the black community and other cultural niches and asking for their perspectives. He said that he learned more from that than from the theoretical work he did before.
To me, Glen’s criticism came across as unnuanced (eg. EAs also donate to GiveDirectly, and it’s not like we force people to take what we give them). I also resonate with that critiques of rationality and EA often seem unfair and devoid of reason. They lack specific examples and arguments relating to what the community actually does, and come across as a priori judgements of our community being cold, reductionist and weird. It’s also frustrating that such critiques can constrain EA efforts to improve the lives of others.
But Glen’s criticism hit an important point: our community wields usefully biased styles of thinking to comprehend the world and impact the lives of beneficiaries far removed from us. But we overlook the perspectives held by persons we affect, perspectives which are adapted to the contexts they live in (with ‘adapted’ I roughly mean that their perspectives are useful for navigating their surrounding environment in ways that allow them to reach opportunities and avoid hazards).
It’s hard though to discern these perspectives without hanging out and talking.
Most rationalists, me included, have spent little time travelling overseas and immersing themselves in local cultures different from theirs. It’s also hard for Glen (or Tyler) to convey perspectives unfamiliar to listeners in x minutes.
If it’s helpful, I could try and share a summary with you of views and styles of thinking that the rationality community is not much in touch with. I read about 150 psychology papers in my spare time to try and form a better understanding of our blindspots (and complementary 'brightspots').
Julia graciously replied that she was interested in a summary of what I think EAs might be missing, or how in particular our views on philanthropy might be biased due to lack of exposure to other cultures/communities.
I emailed her a summary of my upcoming sequence – about a tool I’m developing to map group blindspots. It was tough to condense 75 pages of technical explanation clearly into 7 pages, so bear with me! I refined the text further below:
Here are brightspots (vs. blindspots) that EAs and rationalists might hold in common, ie. areas we notice (vs. miss) that map to relevant aspects of reality.
We often focus on analysing how an abstract thing will function.
This focus is narrow (compared to the portion of hypothetical space that humans are able to perceive and meta-learn from). This is because we are mapping the territory at the intersection of several views.
I think we especially focus on viewing...
- future (vs. past),
- far (vs. near vs. centrally present),
- precisely (vs. imprecisely) sorted
- structures (vs. processes) of
- independent individuals (vs. the interdependent collective) that are
- externally (vs. internally) present.
Different-minded groups can illuminate the aspects we miss in viewing our brightspots:
1. We reference future possibilities
We seem to neglect past case studies or historical accounts somewhat in predicting the effects our philanthropic actions have on beneficiaries. Some conservative cultures attach more value to passing on and studying past accounts and practices. Our community has a progressive leaning. We seem more open to letting go of past learnings and to reimagine the future. As a result, we also reinvent the wheel more (comment).
– Over the years, EA orgs fixated more on upholding established paradigms. Community building practices
arehave especially become more conservative. Unconventional entrepreneurs receive less support.
– I'm confusing different meanings of conservatism. Is this about being closed to unfamiliar people or things, a need to maintain purity and order, deferring to authority or tradition, preventing the loss of what you acquired in the past, updating less on novel inferences, referencing past experiences in planning..?
Update: I rarely hear people at events discuss historical trends relevant to EA work, but have seen ideas posted by EA-dedicated staff now-and-then:
– History of philanthropy: OpenPhil's research, and Future Perfect's podcast series
(eg. on Rockefeller funding forced sterilisation of Indians residing in slums).
– Mercy for Animals building on grassroots advocacy work over earlier decades.
– Intellectual history: FHI on why prior generations missed existential risks.
2. We represent far across distances we perceive
I. Far across more far-fetched scenarios, sequenced over time.
eg. existential risk ends society’s long-term trajectory (vs. current civic issue)
II. Far across places stitched into space.
eg. global poverty (vs. local homelessness)
III. Separated from the bounded entities that neighbour us:
inanimate objects, goal-directed beings, social partners.
eg. pandemic containment (vs. on-the-ground fieldwork)
IV. Decoupled from the context of individual identities we sort entities into:
things, agents, persons.
eg. LW on game-theoretic agents (vs. activists on rescuing a caged animal)
Since we aim to impact the lives of persons far removed from us, we get loose or no feedback on how our actions affected our supposed beneficiaries. Instead, we rely on feedback from our social circle to correct our beliefs. We talk with trusted collaborators who understand what we aim to do. But people close to us share similar backgrounds and use similar mental styles to map and navigate their environment.
Worryingly, contexts to which EAs were exposed in the past (W.E.I.R.D. academia, coding, engineering, etc), and later generalised arguments from, are very dissimilar to the contexts in which their supposed beneficiaries reside (villages in low-income countries, non-human animals in factory farms, cultural and ethnic groups who will be affected by technology developments).
Many of us seem motivated to focus and act on beliefs for doing good by a Calvinistic sense of responsibility that was impressed on us through social interactions since our childhood. We later generalised it to other hypothetical humans, out of a need to have a coherent ontology, as well as to assess value and pursue our derived goals consistently. Such underlying motivations are different from actually caring, and therefore drive a subtle wedge between the information we seek and act on, and what’s actually true, relevant, and helpful for the persons we claim to be trying to improve the lives of.
Going by projects I've coordinated, EAs often push for removing paper conflicts of interest over attaining actual skin in the game (comment).
3. We sort entities precisely into identities
Rationalists who detachedly and coolly model the external world (vs. say nature-loving hippies who feel warm and close to their surroundings), are guided by an aesthetic preference, is my sense:
We distill individual identities into abstract types that are elegant and ordered, based on primary features held in common (your interview on beauty in physics highlighted these aesthetics). Distillation allows us to block out context-specific features that appear messy and noisy.
Perhaps, we perceive contexts as more messy because we sort more precisely. Rationalists have, on average, more pronounced autistic traits. People diagnosed with autism tend to precisely sort entities they notice around them within a narrower confidence band of identity. They need tighter coherence amongst instances to feel certain about them being the same. So their threshold for perceiving ambiguity is lower: a smaller deviation in an entity’s features (superficial or essentialised) will trigger ambiguity as to which identity that entity belongs to.
Upon entering a new context, they fixate on sorting out all these special instances. They get overwhelmed, missing the proverbial forest for the trees. But if they’re able to select primary features individuals hold in common, they can extract a signal from the noise. By distilling individuals as general elements of an ordered system, they can draw neat lines of inference between them.
When we describe that representation of the world to a non-STEM group, it may come across as clinical, segregated, barren, and impoverished of meaning (look into how this post or Brave New World is worded). They struggle with ambiguity of a different kind – about which real-life concrete features embody such an abstract concept (what the hell does a ‘game-theoretic agent’ mean?).
Decoupling conflicts with their motivation to read into concrete nuances. They want to get close to, and be part of, a context that is rich, alive and interwoven.
Glen's personal quote: ❝I work to imagine, build and communicate a pluralistic future for social technology truer to the richness of our diversely shared lives.
EAs and rationalists tend to be context-blind. We are more likely to miss subtle social cues. We are also more naively confident about our models fitting uniformly across various contexts (vs. say the peasants Luria interviewed who were hesitant to speculate about places they hadn't seen before).
One pattern: early EA thinkers proposing explicit arguments that were elegant and ordered. Their analysis of causes and interventions was idealised – only refined later by new entrants who considered concrete applications.
In hindsight, judgements read as simplistic and naive in similar repeating ways (relying on one metric, study, or paradigm and failing to factor in mean reversion or model error there; fixating on the individual and ignoring societal interactions; assuming validity across contexts):
- Eliezer Yudkowsky's portrayal of a single self-recursively improving AGI (later
overturneddisputed by some applied ML researchers)
- Will MacAskill's claim that you can do 100x more good by giving to low-income countries
- Toby Ord’s analysis of DCP2: 'the best of these interventions is estimated to be 1,400 times as cost-effectiveness as the least good'
- ACE researchers’ estimate of 1.4 animals saved per vegan leaflet
- CEA staff recommending community building models derived from Oxford settings to all local organisers (fortunately opened up to criticism and adapted)
Current EA arguments still tend to build on mutually exclusive categorisations (unlike this email :), generalise across large physical spaces and timespans (comment), and assume underlying structures of causation that are static. Authors figure out general scenarios and assess the relative likelihood of each, yet often don't disentangle the concrete meanings and implications of their statements nor scope out the external validity of the models they use in their writing (granted, the latter are much harder to convey). Posts usually don't cover variations across concrete contexts, the relations and overlap between various plausible perspectives, or the changes in underlying dynamics much.
RadicalxChange, on the other hand, emphasises combining relevant perspectives in their modelling, and co-creating solutions with stakeholders who are working from different contexts. I could make a case say for GiveWell doing the former (eg. cluster thinking), but not much of the latter.
4. Our views are built out of structures
We perceive the world as consisting of locatable parts:
- A. We represent + recognise an observation to be a fixed cluster (a structure).
eg. an observation’s recurrence, a place, a body, a stable identity
- B. We predict + update on the possible location of this structure.
eg. how likely it ends up present within some linear sequence, geographic surface, physical boundaries, or levels of feature abstraction
Our structure-based view is a reflection of our Westernised culture. English sentence descriptions centre around the subject, object, and adjectives. Westerners also often perceive active causation as the inherent causal feature of something or someone (eg. a mechanical function, a growth gene, or an aggressive personality).
Conversely, some traditional cultures foster a process-based view. Things are perceived as impermanent and ever-changing (see (action) verb-based Native American languages, or this wacky interpretation of Dzogchen philosophy).
- A. They represent + recognise an observed change to be a trajectory in presence (a process).
eg. a transition, movement, interaction, relation
- B. They predict + update on whenever, wherever, and so forth, this process may initiate again.
Update: Some readers said they were confused by this distinction, or its relevance.
→ See cases of focussing on (interpreting and forecasting) processes vs. structures.
5. We view individuals as independent
Since we prefer sorting different things into ordered and mutually exclusive categories, we aren't as aware of the relations between them (besides maybe endorsing this as a fact of reality upon reflection). In our attempts to carve nature at its joints, we neglect the ways persons and things are causally interdependent. That is, we do this even more strongly than broader Western individualist society (vs. say Asian collectivist cultures).
Quoting from the paper Culture and the Self:
❝Western view of the individual as an independent, self-contained, autonomous entity who
(a) comprises a unique configuration of internal attributes (eg., traits, abilities, motives, and values) and
(b) behaves primarily as a consequence of these internal attributes
❝Experiencing interdependence entails seeing oneself as part of an encompassing social relationship and recognizing that one's behavior is determined, contingent on, and, to a large extent organized by what the actor perceives to be the thoughts, feelings, and actions of others in the relationship.
The RadicalxChange community recognises the interdependence of people as part of a collective whole. They attract members who often take up a more interdependent culture or mindset (social scientists, artists, African-Americans, women). To be fair, this might also be because RxC engages minority groups more, who in turn feel empowered to contribute to mechanisms that can overcome systemic exploitation. Update: minorities are less represented than I thought.
Revisiting Glen's critiques, I interpret one basis to be our neglect of social interconnectedness:
❝We’re not going to pay that much attention to getting feedback from the people whose lives that affects or being in conversation with them.
❝cloistering themselves into a room
❝You have to think of the things you’re doing as speech acts and not purely intellectual acts... They condition a certain sort of a society.
❝a lot of the overly field experiment driven, effective ways of charitable giving that didn’t think about broader social structures and effects of that sort of stuff
❝the actual power that people derive in a decentralized way almost always comes from their ability to act collectively. It’s almost never possible on your own to exercise much power.
Update: Climate change is a case I think where noticing causal interdependencies can be especially insightful (if you don't rely on a priori notions of interconnectedness).
– Carbon emissions are not 'one global thing' but downstream from eg. farming animals intensively, cutting trees to expand farmland and to supply firewood for cooking, burning biomass that releases air pollutants, and subsidising polluting industries over investing in lower-cost clean alternatives. These activities harm local residents too through respiratory illness, self-reinforcing poverty cycles, estrangement from their surroundings, etc. Since these localised harms intertwine with global emissions, overlapping interventions can address both.
– Carbon emissions are upstream from gases released into the atmosphere trapping heat, inducing anomalous weather patterns that further harm citizens worldwide, and also suck up their representatives' attention and coordinated use of resources to mitigate other human-originated threats.
6. We view things as being external to us
In conversations, EAs and rationalists often attempt to convey a more impartial or objective view of the external world. This leads us to disregard personal interpretations when those are actually relevant (eg. for supporting a collaborator, or considering a friend's needs and constraints when advising them on their career options).
In terms of individual persons, we could do worse though. Though people can be socially awkward, they do check in and consider how their conversation partner is feeling. Some of us are also really into introspection techniques and self-awareness (eg. rationalists writing about meditation experiences, Qualia Research Institute).
But since we focus more on the individual than the interdependent collective, we're particularly unaware of the cultural feeling of our community, as well as any broader social repercussions of our actions.
- cases where 80,000 Hours staff didn’t catch on to the effects that their general career recommendations were having on the broader EA community (they've now more clearly specified the scope of their goals and whom they can serve)
- criticism around EAs neglecting the effects of what they say and do on societal norms (eg. Rob Reich's criticism of GiveWell)
- LessWrong members who felt unwelcome and lonely, prompting Project Hufflepuff's start (effective animal advocacy meetups though are more warm and cozy in my experience; one organiser shared more or less with me that outsiders see them as cutesy Hufflepuffs)
Update: Cases of people working well with different social perspectives:
– Past non-violent resistance movements led by Ghandi & Martin Luther King
– Tsai Ing-wen transparently engaging, relating & empowering Taiwan citizens
– Therapists and social workers who uncover relationship contexts & dynamics
– Human-centric computer tool designers (eg. at Apple, early internet innovators)
– Acumen Fund incubating a mosquito bednet factory & localised voice surveys
More speculative brightspots (vs. blindspots):
I updated and added to the sections below:
7. (Interpret vs.) forecast
- A. Interpret: recognise + represent aspects
eg. classical archaeologists focus on differentiated recognition of artefacts,
linguistic anthropologists on representing differentiated social contexts
- B. Forecast: sample + predict aspects
eg. development economists focus more on calibrated sampling of metrics,
global prio scholars on calibrating their predictions of distilled scenarios
Our forecasting style focuses on calibrating likelihoods of a minimal set of aspects we deem to be primary or most important. eg. AI existential safety researchers who seek to improve the accuracy of their AGI timeline forecasts, rather than seek out other complementary interpretations relevant to developing beneficial AI.
A 'reader of technological landscapes' like Kevin Kelly can tell various trends or possibilities that others can't (like an urbanite can't tell the rich signs of natural landscapes). Similarly, venture capitalists focus less on predicting start-up exit scenarios and more on reading into markers of performance (eg. founders 'living in the future' who confidently pursue their alternative vision for future products) that competing VCs and tech corps neglect.
Even in evaluating hit-miss rates, there's a trade-off between calibrating likelihoods of a clean reference class(B), and differentiating amongst aspects to reference(A).
Dialectic between views:
A: VCs anticipated tech trends before others did.
B: Those VCs were overconfident; it rarely turned out as they specifically claimed.
A: But they identified new frontiers and gaps to invest in, giving them an edge.
B: An impartial sample of VC investors shows they got sub-par returns on average.
A: A subpopulation of some geographical & intellectual origin got high returns.
B: Those are spurious correlations you cherry-picked after the fact.
8. Gain vs. loss focus
To attain more positive valence vs. remove more negative valence.
Personal motivation matters because it guides how people frame their focus, pursue strategies, and assess aims. For example, x-risk leaders and s-risk managers may be predisposed to and socially reinforced to set goals differently, going by my stereotyped impressions:
- Eliezer and Nick – to eagerly leap towards attaining their ideal for a more positive world state (powering over obstacles, towards the possible presence of a gain). Each originally led the start-up phase of a techno-optimistic institute. But they realised they needed to go pioneer research to prevent AGI misalignment in order to not sadly miss out on utopia.
- Center on Long-Term Risk – to vigilantly maintain their responsibility to prevent a more negative world state (shut off any intrusion of a potential loss, to control its absence). Founders originally met through discussions of moral philosophy, infused with German Weltschmerz. Managing secure, incremental charity operations is their core competence (update: an ops employee said CLT's processes are more loose and exploratory than I let on). But they're prepared to promote innovative start-up practices in order to relieve the universe from pessimistic scenarios of suffering.
9. (Sensory groundedness vs.) representational stability of beliefs
Markers of perception:
0. Present I. Time-bound II. Stitched III. Enclosed IV. Categorised
observation’s recurrence vs. sorted identity
observed transition vs. analogised relation
0. Arises I. Follows II. Moves III. Crosses IV. Links
If you got this far, I’m interested to hear your thoughts! Do grab a moment to call so we can chat about and clarify the concepts. Takes some back and forth.