Primarily, finishing my PhD thesis in mathematics. On the side, devouring through The Adapted Mind, The Cambridge Handbook of Experts & Expertise, and Russell and Norvig’s AI book (I can post LW summaries if anyone is interested).
Not much that I haven’t figured out on my own, but it helped me make my belief in belief congruent with my belief (I understand now that consuming certain media literally re-wires your brain in a way you have no control over, and it helped me understand how important it is to consciously only read / study certain things, and limit others.) Here are some important quotes:
“Research with these methods has shown that additional experience appears to make performance less effortful and less demanding, but to improve performance it is necessary to seek out practice activities that allow individuals to work on improving specific aspects, with the help of a teacher and in a protected environment, with opportunities for reflection, exploration of alternatives, and problem solving, as well as repetition with informative feedback.” (Deliberate practice)
Knowledge matters, and is almost exclusively characteristic of intelligence in humans: “In contrast, [computer] programs that are rich in general inference methods—some of which may even have some of the power of mathematical logic—but poor in domain-specific knowledge can behave expertly on almost no tasks.” There is no such thing as “general aptitude,” except maybe very subtly. The things you read, the people you socialize with, and the introspections you have to re-wire your thought, matter. This also means that going to a prestigious university is the best way to learn a given (academic) subject matter, neurophysiologically speaking, given the environment it immerses you in.
Unfortunately, “the history of psychology suggests that there is no one ‘truth’ about how to accomplish learning and instruction.”
When I started the program, I didn’t know anything about the singularity or rationality or friendly AI or even much chemistry or biology! So I am doing some very hard and difficult introspecting about what I must do next to fulfill Horace Mann’s eternal proverb, “be ashamed to die until you have scored a victory for humanity.” Somehow, my calculations keep showing that the subject of my PhD, constructing a p-adic L-function for a class of automorphic representations in a particular reductive group called Gsp4, is not the way to go! I only need $15-20k a year to subsist and work on SIAI issues, but humorously enough my biggest concern is a job. Having a PhD in pure math makes me overqualified for almost everything except academia, and in that setting I would not have much time for existential risk issues given the postdoc rat race. I enjoy mathematics immensely, but it’s about time I make some personal Level 3 decisions and think about whether this is where I will fulfill most utility. Sadly, my emails to SIAI for the visiting fellows program have gone unanswered, but perhaps I should try again. I could always enter a neuroscience or theoretical computer science program.
Sadly, my emails to SIAI for the visiting fellows program have gone unanswered, but perhaps I should try again.
Definitely! The folks at SIAI seem to have hyperactive spam-filters. You can also write someone ( I think Carl Shulman is the right one, but I don’t know for sure) a PM on LW.
Primarily, finishing my PhD thesis in mathematics. On the side, devouring through The Adapted Mind, The Cambridge Handbook of Experts & Expertise, and Russell and Norvig’s AI book (I can post LW summaries if anyone is interested).
I was thinking about buying a copy of the Cambridge Handbook. Does it offer any practically useful advice/insights?
Not much that I haven’t figured out on my own, but it helped me make my belief in belief congruent with my belief (I understand now that consuming certain media literally re-wires your brain in a way you have no control over, and it helped me understand how important it is to consciously only read / study certain things, and limit others.) Here are some important quotes:
“Research with these methods has shown that additional experience appears to make performance less effortful and less demanding, but to improve performance it is necessary to seek out practice activities that allow individuals to work on improving specific aspects, with the help of a teacher and in a protected environment, with opportunities for reflection, exploration of alternatives, and problem solving, as well as repetition with informative feedback.” (Deliberate practice)
Knowledge matters, and is almost exclusively characteristic of intelligence in humans: “In contrast, [computer] programs that are rich in general inference methods—some of which may even have some of the power of mathematical logic—but poor in domain-specific knowledge can behave expertly on almost no tasks.” There is no such thing as “general aptitude,” except maybe very subtly. The things you read, the people you socialize with, and the introspections you have to re-wire your thought, matter. This also means that going to a prestigious university is the best way to learn a given (academic) subject matter, neurophysiologically speaking, given the environment it immerses you in.
Unfortunately, “the history of psychology suggests that there is no one ‘truth’ about how to accomplish learning and instruction.”
Interested, but please post a sample before doing extra work.
Out of curiosity, what’s your PhD thesis about?
When I started the program, I didn’t know anything about the singularity or rationality or friendly AI or even much chemistry or biology! So I am doing some very hard and difficult introspecting about what I must do next to fulfill Horace Mann’s eternal proverb, “be ashamed to die until you have scored a victory for humanity.” Somehow, my calculations keep showing that the subject of my PhD, constructing a p-adic L-function for a class of automorphic representations in a particular reductive group called Gsp4, is not the way to go! I only need $15-20k a year to subsist and work on SIAI issues, but humorously enough my biggest concern is a job. Having a PhD in pure math makes me overqualified for almost everything except academia, and in that setting I would not have much time for existential risk issues given the postdoc rat race. I enjoy mathematics immensely, but it’s about time I make some personal Level 3 decisions and think about whether this is where I will fulfill most utility. Sadly, my emails to SIAI for the visiting fellows program have gone unanswered, but perhaps I should try again. I could always enter a neuroscience or theoretical computer science program.
Definitely! The folks at SIAI seem to have hyperactive spam-filters. You can also write someone ( I think Carl Shulman is the right one, but I don’t know for sure) a PM on LW.
And do you know the Existential Risk Reduction Career Network?