---
title: Generalist tendencies in people with a single cause area focus
author: Issa Rice
created: 2018-08-14
date: 2018-08-14
# documentkind:
status: notes
# belief:
---

*I describe something I've been puzzling over for several months, along with
some possible solutions. I still feel confused about this and I think some of
the solutions I list aren't that good (but I list them for completeness). I
consider this page to be rough notes based on scattered musings.*

The basic idea is to consider people who have a "single cause area focus", i.e.
people who have "locked-in" to a single cause area or who are "diehard" about
their cause area, and then to ask how "generalist" we should expect them to be.
I should mention that I'm most interested in people who have "locked-in" to AI
safety/alignment as a cause area, and the examples below will mostly be from
there.

When I try to think of what my _a priori_ view would be, I think I expect
people to be less generalist than they actually are. The basic feeling is
something like, if this really is the One True Cause, then shouldn't one want
to devote almost all of one's resources to it? So the puzzle for me is to
reconcile my _a priori_ view with what is actually going on. Obviously this
question interests me because I am wondering how generalist I should be.

Here are some reasons I've thought of for why we might see generalist
tendencies in people with a single cause area focus:

-   The knowledge is actually from *before* locking in on the cause area. So
    maybe the most expensive part of the cost has already been paid (in terms
    of learning a new field), and the rest is just paying small amounts to keep
    up with a field or to write small things.

-   Knowing a lot of other fields is actually useful for your "locked
    in" cause/problem. You can sort of see this in MIRI's research
    guide. There's a lot of different subjects in there that are
    supposed to help with alignment research.

-   "Division of labor is all well and good, but if you've spent much
    time around others in a business you soon realise that it isn't all
    that it's cracked up to be. There's a reason why so many of
    histories prolific inventors had an enormous array of skills in many
    different areas: because the only person you can really count on to
    be there is yourself. Employees and colleagues come and go, the only
    constant is you."
    ([source](http://lesswrong.com/lw/5me/scholarship_how_to_do_it_efficiently/46ar))

-   Explore/exploit trade-off and dealing with the possibility that one's own
    cause area might not be the best. See things like [Cause
    X](https://causeprioritization.org/Cause_X), [multi-armed
    bandit](https://en.wikipedia.org/wiki/Multi-armed_bandit), etc.

-   What allowed you to find the good cause in the first place was due to your
    curiosity, generalist tendency, etc. Maybe it's pretty hard to restrain
    your high curiosity even once you've locked in on a cause you think is most
    important. In this case you might want to try to become less curious?

-   Here's Wei Dai: "One solution \[to the problem of stupidity from
    having high status\] that might work (and I think has worked for me,
    although I didn't consciously choose it) is to periodically *start
    over*. Once you've achieved recognition in some area, and no longer
    have as much interest in it as you used to, go into a different
    community focused on a different topic, and start over from a
    low-status (or at least not very high status) position. Of course
    this doesn't work unless there are several things that you can work
    on whose marginal utilities aren't too far apart. (It probably
    doesn't apply to Eliezer for example.)"
    ([source](http://lesswrong.com/lw/1lo/high_status_and_stupidity_why/1fxd))

-   These people don't see the world as being broken up into different
    fields; rather they are better at "seeing reality for how it is".
    That means they cross field boundaries more easily. Many things
    really *are* connected and show up in many different fields
    simultaneously. I think some people would even say that one of the ways to
    discover things is to find connections between fields.[^ltm]

    Scott Alexander [writes](https://www.reddit.com/r/slatestarcodex/comments/6tt3gy/a_history_of_the_rationality_community/):

    > Eliezer had a lot of weird and varying interests, but one of his talents
    > was making them all come together so you felt like at the root they were
    > all part of this same deep philosophy. This didn't work for other people,
    > and so we ended up with some people being amateur decision theory
    > mathematicians, and other people being wannabe self-help gurus, and still
    > other people coming up with their own theories of ethics or metaphysics
    > or something. And when Eliezer did any of those things, somehow it would
    > be interesting to everyone and we would realize the deep connections
    > between decision theory and metaphysics and self-help. And when other
    > people did it, it was just "why am I reading this random bulletin board
    > full of stuff I'm not interested in?"

    And [Eliezer himself](https://intelligence.org/files/TDT.pdf):

    > The map is not the territory. Nature is a single flow, one continuous
    > piece. Any division between the science of psychology and the science of
    > physics is a division in human knowledge, not a division that exists in
    > things themselves. If you dare break up knowledge into academic fields,
    > sooner or later the unreal boundaries will come back to bite. So long as
    > psychology and physics *feel* like separate disciplines, then to say that
    > physics determines choice *feels* like saying that psychology cannot
    > determine choice. So long as electrons and desires *feel* like different
    > things, to say that electrons play a causal role in choices *feels* like
    > leaving less room for desires."

    See also how diverse the [problems that motivated Wei Dai to develop
    UDT](http://lesswrong.com/lw/cs9/list_of_problems_that_motivated_udt/) are.

    Tooby and Cosmides in "The Psychological Foundations of Culture":

    > Disciplines such as astronomy, chemistry, physics, geology, and biology
    > have developed a robust combination of logical coherence, causal
    > description, explanatory power, and testability, and have become examples
    > of how reliable and deeply satisfying human knowledge can become. Their
    > extraordinary florescence throughout this century has resulted in far
    > more than just individual progress within each field. These disciplines
    > are becoming integrated into an increasingly seamless system of
    > interconnected knowledge and remain nominally separated more out of
    > educational convenience and institutional inertia than because of any
    > genuine ruptures in the underlying unity of the achieved knowledge.

    Apparently this idea has been named ["Intertwingularity"](https://en.wikipedia.org/wiki/Intertwingularity).

-   The role of popularization/getting help from experts in many fields.
    It isn't because of Eliezer's decision theory work that he is now
    well-known; rather, it is his popularization work (though the
    Sequences are not purely popularization) and fiction writing. So
    might it make sense to go into other fields to popularize them?

-   Eliezer [writes](https://www.facebook.com/yudkowsky/posts/10156147605134228):

    > Back when Bitcoin was gaining a little steam for the first time, enough
    > that nerds were starting to hear about it, I said to myself back then
    > that it wasn't my job to think about cryptocurrency. Or about clever
    > financial investment in general. I thought that actually winning there
    > would take a lot of character points I didn't have to spare, if I could
    > win at all. I thought that it was my job to go off and solve AI
    > alignment, that I was doing my part for Earth using my own comparative
    > advantage; and that if there was really some low-hanging investment fruit
    > somewhere, somebody else needed to go off and investigate it and then
    > donate to MIRI later if it worked out.
    >
    > I think that this pattern of thought in general may have been a kind of
    > wishful thinking, a kind of argument from consequences, which I do
    > regret. In general, there isn't anyone else doing their part, and I wish
    > I'd understood that earlier to a greater degree. But that pattern of
    > thought didn't actually fail with respect to cryptocurrency. In 2017,
    > around half of MIRI's funding came from cryptocurrency donations. That
    > part more or less worked.

    Especially the "In general, there isn't anyone else doing their
    part" part.

-   See the exchange between Wei Dai and Eliezer
    [here](http://lesswrong.com/lw/hh4/the_robots_ai_and_unemployment_antifaq/9g1t).
    In particular: "Partially dispel the view of MIRI wherein we're
    allegedly supposed to pontificate on something called 'AI risk' and
    look gravely concerned about it. Lure young economists into looking
    at the intelligence explosion microeconomics problem."

-   ["Is there a Connection Between Greatness in Math and Philosophy?"](https://www.greaterwrong.com/posts/KWJTn4bB5uzdxdNSZ/is-there-a-connection-between-greatness-in-math-and)
    Maybe people are just good at many things so they do all of them.

-   The sensitivity of one's cause prioritization to many factors, such that if
    some of those factors change, one might want to switch to a different cause
    area. This might then mean having generalist tendencies to be able to know
    which cause area to switch into. See e.g. ["AI timelines and cause
    prioritization"](https://causeprioritization.org/AI_timelines_and_cause_prioritization).

-   Eliezer [writes](https://www.lesswrong.com/posts/HnPEpu5eQWkbyAJCT/the-simple-math-of-everything):

    > I remember when I finally picked up and started reading through my copy
    > of the _Feynman Lectures on Physics_, even though I couldn't think of any
    > realistic excuse for how this was going to help my AI work, because I
    > just got fed up with not knowing physics.  And -- you can guess how this
    > story ends -- it gave me a new way of looking at the world, which all my
    > earlier reading in popular physics (including Feynman's QED) hadn't done.
    > Did that help inspire my AI research?  Hell yes.  (Though it's a good
    > thing I studied neuroscience, evolutionary psychology, evolutionary
    > biology, Bayes, and physics _in that order_ -- physics alone would have
    > been _terrible_ inspiration for AI research.)

-   [Brian Tomasik](https://foundational-research.org/education-matters-for-altruism/ "Education Matters for Altruism. October 30, 2017."):

    > If you're trying to advance the state of the art in one
    > particular domain, it suffices to dig very deep into that field
    > and probe it as much as possible. But if you're trying to do the
    > most good in a global sense, you need a global perspective,
    > which requires learning a little bit of everything.

-   From [this interview](http://commonsenseatheism.com/?p=12147):

    > ELIEZER: To put it in a nutshell, my best and worst mistake was thinking
    > that intelligence was a big, complicated kluge with no simple principles
    > behind it. The reason that it’s my best mistake, as mistakes go, is that
    > this belief that there were no simple answers caused me to go out and
    > study neuroscience, cognitive psychology, and various A.I. machine
    > learning stuff, and this whole big grab bag of information that was
    > actually very useful to know.

    > As mistakes go, this mistake motivated me to go out and learn a whole lot
    > of different things. Which is certainly a very good sort of mistake to
    > make if you view it from that perspective. But for other and even more
    > complicated reasons that we may or may not end up getting into later in
    > this particular interview, I later realized that A.I. work was going to
    > have to meet a higher standard of precision than I’d been visualizing.

    Eliezer writes more about this in [this post](https://www.lesswrong.com/posts/BA7dRRrzMLyvfJr9J/my-best-and-worst-mistake).

-   Anna Salamon describes the 50/50 rule in a [comment](https://lw2.issarice.com/posts/96N8BT9tJvybLbn5z/we-run-the-center-for-applied-rationality-ama#ggCv4GJgrvya7c65d):
    "The 50/50 rule is a proposed heuristic claiming that about half of all
    progress on difficult projects will come from
    already-known-to-be-project-relevant subtasks [...]. The other half of
    progress on difficult projects (according to this heuristic) will come from
    taking an interest in the rest of the world, including parts not yet known
    to be related to the problem at hand". (However, see the note at the top of
    that comment, which says she might change her mind about this if she were
    to actually write a blog post about it.)

-   <https://www.greaterwrong.com/posts/XvN2QQpKTuEzgkZHY/being-the-pareto-best-in-the-world>
    gives an argument for specializing in multiple directions and being
    generalist so as to claim more problems that only you can solve.

-   Possibly related, a [comment](https://www.greaterwrong.com/posts/t6Fe2PsEwb3HhcBEr/the-litany-against-gurus/comment/DYdFGjLf76SfdoSrY) about people specializing in modes of cognition.

-   <https://www.greaterwrong.com/posts/XcDSmXecYiubPjxAj/eric-drexler-on-learning-about-everything>

Could this sort of generalist tendency be bad? In other words, why might it
make sense to *not* become a generalist? I think the main arguments against
would be things like division of labor and economy of scale. Also, things like
how you need to "climb higher" to get to the frontier nowadays in some fields,
so the only way you will make novel contributions is by specializing to get to
the frontier.

[^ltm]: See e.g. ["Don’t be afraid to learn things outside your field"](https://terrytao.wordpress.com/career-advice/don%E2%80%99t-be-afraid-to-learn-things-outside-your-field/), although this is just about mathematics.

    Also related are things like the following quote from ["Augmenting Long-term Memory"](http://augmentingcognition.com/ltm.html):

    > The world isn't divided up into neatly separated components, and I
    > believe it's good to collide very different types of questions. One
    > moment Anki is asking me a question about the temperature chicken should
    > be cooked to. The next: a question about the JavaScript API. Is this
    > mixing doing me any real good? I'm not sure. I have not, as yet, found
    > any reason to use JavaScript to control the cooking of a chicken. But I
    > don't think this mixing does any harm, and hope it is creatively
    > stimulating, and helps me apply my knowledge in unusual contexts.

    and:

    > But for creative work and for problem-solving there is something special
    > about having an internalized understanding. It enables speed in
    > associative thought, an ability to rapidly try out many combinations of
    > ideas, and to intuit patterns, in ways not possible if you need to keep
    > laboriously looking up information.

    From ["Anki Tips: What I Learned Making 10,000 Flashcards"](http://rs.io/anki-tips/):

    > Take the production of insight, for instance. I find that insight often
    > arises when two ideas that have been recently activated in memory collide
    > and I think, “Oh, wait, that’s related to that.”
    >
    > If everything is carefully partitioned, you limit opportunities for this
    > serendipity. Topic organization says “ideas about computer science don’t
    > belong with those about economics,” except applying ideas across
    > disciplines is precisely where the insights are likely to be most
    > fertile.