Send copies of Global Catastrophic Risks to lists of bright young students
This may come across as spamming and will likely send crank signals.
I dunno. It's a book. If anyone sends me a book, I'll consider keeping it and likely look at the first couple of pages, even if it's Dianetics or The Book of Mormon. I don't regard books as the physical and memetic pollution that spam is.
If I got a vanity-press book like this, I'd regard it as cranky non-spam. But Global Catastrophic Risks is published by Oxford University Press, which matches the pattern "legitimate" rather than "crank".
If I got a religious text, I'd be unimpressed. But Global Catastrophic Risks differs from a religious text in that it's a collection of essays by different authors who no doubt disagree about many things, rather than a canonized text that's regarded as perfect. And the hidden agenda of someone who gives me Global Catastrophic Risks is to get me thinking about global catastrophic risks — which is pretty reasonable, although not universally compelling. It would be much less creepy than receiving a Bible.
In summary, while JoshuaZ might have been turned off by receiving a book when he was a mathematically talented youth, I wouldn't have. So, that's two data points.
tl;dr: Please send me a copy of the Book of Mormon.
This is basically my approach of choice, and I am very happy to see SI pursuing it. That said, I would like to make a couple of comments:
Specifically, we're looking for young talent in math and compsci, because young talent is...(3) better at inventing new math (due to cognitive decline with age).
So, if Edward Witten (age 60)* called you up tomorrow and said he was interested in working on Friendly AI, you would tell him to get lost? I think not. At least, I hope not.
I'm not saying you should target older people in your recruitment activities. (As if that were even possible.) But I am strongly advising against getting into any kind of mindset where you would end up closing the door on any mathematically accomplished people who happen to see the light on this matter.
AGI really might be decades or more away. The people who are "young" now won't be that way forever. You may want their help in the future. In particular, you may want the help of a future John Baez, who after a satisfying run in more mainstream topics, decides at age 40 to turn their attention to "helping humanity" -- only in the form of FAI research rather than environmentalism.
(Also, if you b...
That would be difficult, since "groundbreaking work" automatically implies "extreme outlier".
In fact, I would expect that typical mathematicians are much more useful above 30 than below -- to a greater extent than is the case for the extreme outliers.
Simonton (1988) Age and Outstanding Achievement: What Do We Know After a Century of Research? Psychological Bulletin, Vol. 104, No. 2, 251-267.
Short version: the productivity for mathematicians seems to peak around late 20s or early 30s, with the productivity after the peak falling to less than one-quarter the maximum. However, the average quality of a contribution does not seem to vary with age, and exceptional researchers (in any field) tend to remain unusually profilic, as compared to an average researcher of the same age, even after passing their peaks.
Long version:
...In the first place, the location of the peak, as well as the magnitude of the postpeak decline, tends to vary depending on the domain of creative achievement. At one extreme, some fields are characterized by relatively early peaks, usually around the early 30s or even late 20s in chronological units, with somewhat steep descents thereafter, so that the output rate becomes less than one-quarter the maximum. This agewise pattern apparently holds for such endeavors as lyric poetry, pure mathematics, and theoretical physics, for example (Adams, 1946; Dennis, 1966; Lehman, 1953a; Moulin, 1955; Roe, 1972b; Simonton, 1975
...and after posting that comment, I remembered that I had made an earlier post citing studies that said that it's the middle-aged and not young scientists who are the most productive, which is in conflict with the results I just quoted. I feel silly now. I guess I should re-read the studies that I referenced three years ago to figure out what version is correct.
Anything for undergrads? It might be feasible to do a camp at the undergraduate level. Long term, doing an REU style program might be worth considering. NSF grants are available to non-profits and it may be worth at least looking into how SIAI might get a program funded. This would likely require some research, someone who is knowledgeable about grant writing and possibly some academic contacts. Other than that I'm not sure.
In addition, it might be beneficial to identify skill sets that are likely to be useful for SI research for the benefit of those who might be interested. What skills/specialized knowledge could SI use more of?
Run SPARC, a summer program on rationality for high school students with exceptional math ability. Cost: roughly $30,000.
Do we have any reason to believe that such a program will be more effective than existing summer programs like Ross and PROMYS?
SPARC and a number of mostly homogeneous math camps are all looking for pre-college students with strong mathematical ability. Since SPARC's syllabus is notably different from that of math camps, it seems like a bad idea to compete with these camps for the top students. But competition is inevitable if SPARC runs at the same time as these camps; below I have found and listed the 2012 start and end dates for the most prominent math camps:
SPARC's starting date this year conflicts with the end dates of three of these seven camps. Perhaps there are other scheduling constraints, but if not, wouldn't it be a good idea to run SPARC a week later to avoid conflicts? (It is too late to change this year, of course.)
*I know RSI is not a math camp in the spirit of the others, but it's well-known and attracts some students away from math camps.
ETA: And since SPARC is free and relevant to math students, if it can guarantee that it will not conflict with the other program dates, I think...
You guys should have a simple mailing list to sign up for to get reminded about future camps, and maybe even to broadcast camp related materials (e.g. "here are video lectures from the camp you missed").
Intelligence seems relatively static, but AFAIK once you've reached a certain minimum threshold in intelligence, conscientiousness becomes a more important factor for actual accomplishment. (Anecdotally and intuitively, conscientiousness seems more amenable to change, but I don't know if the psychological evidence supports that.)
Another point: I seem to recall a joke among mathematicians that if only it was announced that some famous problem was solved, without there actually being a solution, someone would try to find the solution for themselves and succeed in finding a valid solution.
In other words, how problems are framed may be important, and framing a problem as potentially impossible may make it difficult for folks to solve it.
Additionally, I see little evidence that the problems required for FAI are actually hard problems. This isn't to say that it's not a major research endeavor, which it may or may not be. All I'm saying is I don't see top academics having hammered at problems involved in building a FAI the same way they've hammered at, say, proving the Riemann hypothesis.
EY thinking they are super hard doesn't seem like much evidence to me; he's primarily known as a figure in the transhumanist movement and for popular writings on rationality, not for solving research problems. It's not even clear how much time he's spent thinking about the problems in between all of the other stuff he does.
FAI might just require lots of legwork on problems that are relatively straightforward to solve, really.
Simonton (1988) Age and Outstanding Achievement: What Do We Know After a Century of Research? Psychological Bulletin, Vol. 104, No. 2, 251-267.
Short version: the productivity for mathematicians seems to peak around late 20s or early 30s, with the productivity after the peak falling to less than one-quarter the maximum. However, the average quality of a contribution does not seem to vary with age, and exceptional researchers (in any field) tend to remain unusually profilic, as compared to an average researcher of the same age, even after passing their peaks.
Long version:
In the first place, the location of the peak, as well as the magnitude of the postpeak decline, tends to vary depending on the domain of creative achievement. At one extreme, some fields are characterized by relatively early peaks, usually around the early 30s or even late 20s in chronological units, with somewhat steep descents thereafter, so that the output rate becomes less than one-quarter the maximum. This agewise pattern apparently holds for such endeavors as lyric poetry, pure mathematics, and theoretical physics, for example (Adams, 1946; Dennis, 1966; Lehman, 1953a; Moulin, 1955; Roe, 1972b; Simonton, 1975a; Van Heeringen & Dijkwel, 1987). At the contrary extreme, the typical trends in other endeavors may display a leisurely rise to a comparatively late peak, in the late 40s or even 50s chronologically, with a minimal if not largely absent drop-off afterward. This more elongated curve holds for such domains as novel writing, history, philosophy, medicine, and general scholarship, for instance (Adams, 1946; Richard A. Davis, 1987; Dennis, 1966; Lehman, 1953a; Simonton, 1975a). Of course, many disciplines exhibit age curves somewhat between these two outer limits, with a maximum output rate around chronological age 40 and a notable yet moderate decline thereafter (see, e.g., Fulton & Trow, 1974; Hermann, 1988; Mc- Dowell, 1982; Zhao & Jiang, 1986). Output in the last years appears at about half the rate observed in the peak years. Productive contributions in psychology, as an example, tend to adopt this temporal pattern (Homer et al., 1986; Lehman, 1953b; Over, 1982a, 1982b; Zusne, 1976).
It must be stressed that these interdisciplinary contrasts do not appear to be arbitrary but instead have been shown to be invariant across different cultures and distinct historical periods (Lehman, 1962). As a case in point, the gap between the expected peaks for poets and prose authors has been found in every major literary tradition throughout the world and for both living and dead languages (Simonton, 1975a). Indeed, because an earlier productive optimum means that a writer can die younger without loss to his or her ultimate reputation, poets exhibit a life expectancy, across the globe and through history, about a half dozen years less than prose writers do (Simonton, 1975a). This cross-cultural and transhistorical invariance strongly suggests that the age curves reflect underlying psychological universals rather than arbitrary sociocultural determinants. In other words, the age functions for productivity may result from intrinsic information-processing requirements rather than extrinsic pressures due to age stereotypes about older contributors, a point that we shall return to in the theoretical section (see also Bayer & Dutton, 1977).
[...]
Generally, the top 10% of the most prolific elite can be credited with around 50% of all contributions, whereas the bottom 50% of the least productive workers can claim only 15% of the total work, and the most productive contributor is usually about 100 times more prolific than the least (Dennis, 1954b, 1955; also see Lotka, 1926; Price, 1963, chap. 2). Now from a purely logical perspective, there are three distinct ways of achieving an impressive lifetime output that enables a creator to dominate an artistic or scientific enterprise. First, the individual may exhibit exceptional precocity, beginning contributions at an uncommonly early age. Second, the individual may attain a notable lifetime total by producing until quite late in life, and thereby display productive longevity. Third, the individual may boast phenomenal output rates throughout a career, without regard to the career's onset and termination. These three components are mathematically distinct and so may have almost any arbitrary correlation whatsoever with each other, whether positive, negative, or zero, without altering their respective contributions to total productivity. In precise terms, it is clear that O = R(L - P), where O is lifetime output, R is the mean rate of output throughout the career, L is the age at which the career ended (longevity), and P is the age at which the career began (precocity). The correlations among these three variables may adopt a wide range of arbitrary values without violating this identity. For example, the difference L - P, which defines the length of a career, may be more or less constant, mandating that lifetime output results largely from the average output rate R, given that those who begin earlier, end earlier, and those who begin later, end later. Or output rates may be more or less constant, forcing the final score to be a function solely of precocity and longevity, either singly or in conjunction. In short, R, L, and P, or output rate, longevity, and precocity, comprise largely orthogonal components of O, the gauge of total contributions.
When we turn to actual empirical data, we can observe two points. First, as might be expected, precocity, longevity, and output rate are each strongly associated with final lifetime output, that is, those who generate the most contributions at the end of a career also tend to have begun their careers at earlier ages, ended their careers at later ages, and produced at extraordinary rates throughout their careers (e.g., Albert, 1975; Blackburn et al., 1978; Bloom, 1963; Clemente, 1973; S. Cole, 1979; Richard A. Davis, 1987; Dennis, 1954a, 1954b; Helson & Crutchfield, 1970; Lehman, 1953a; Over, 1982a, 1982b; Raskin, 1936; Roe, 1965, 1972a, 1972b; Segal, Busse, & Mansfield, 1980; R. J. Simon, 1974; Simonton, 1977c; Zhao & Jiang, 1986). Second, these three components are conspicuously linked with each other: Those who are precocious also tend to display longevity, and both precocity and longevity are positively associated with high output rates per age unit (Blackburn et al., 1978; Dennis, 1954a, 1954b, 1956b; Horner et al., 1986; Lehman, 1953a, 1958; Lyons, 1968; Roe, 1952; Simonton, 1977c; Zuckerman, 1977). [...]
While specifying the associations among the three components of lifetime output, we have seemingly neglected the expected peak productive age. Those creators who make the most contributions tend to start early, end late, and produce at above average rates, but are the anticipated career peaks unchanged, earlier, or later in comparison to what is seen for their less prolific colleagues? [...]
...and after posting that comment, I remembered that I had made an earlier post citing studies that said that it's the middle-aged and not young scientists who are the most productive, which is in conflict with the results I just quoted. I feel silly now. I guess I should re-read the studies that I referenced three years ago to figure out what version is correct.
Series: How to Purchase AI Risk Reduction
Here is yet another way to purchase AI risk reduction...
Much of the work needed for Friendly AI and improved algorithmic decision theories requires researchers to invent new math. That's why the Singularity Institute's recruiting efforts have been aimed a talent in math and computer science. Specifically, we're looking for young talent in math and compsci, because young talent is (1) more open to considering radical ideas like AI risk, (2) not yet entrenched in careers and status games, and (3) better at inventing new math (due to cognitive decline with age).
So how can the Singularity Institute reach out to young math/compsci talent? Perhaps surprisingly, Harry Potter and the Methods of Rationality is one of the best tools we have for this. It is read by a surprisingly large proportion of people in math and CS departments. Here are some other projects we have in the works:
Here are some things we could be doing if we had sufficient funding: