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Re10: Living to Guess Another Day
Retraice1
On guessing, checking and fighting.
Air date: Monday, 2nd Nov. 2020, 12 : 00 PM Pacific/US.
1 Natural intelligence
We've already talked about strategic and artificial intelligence.
Side note: by listening to a podcast, or to anything, you are almost by definition 'smartish', to borrow Yudkowsky's term.2 Listening and hearing might be different, but a rock can do neither, which is not smartish.
You've realized you're dumb
Right? If you're not still an overconfident whipper-snapper, we safely assuming that your own dumb mistakes have humbled you about your own smartishness.
There's genius there, in all of us, to be sure. And the same is true of stupidity.
Stubbing your toe is 'body stupidity', not brain stupidity, if there's a difference.
What (natural) intelligence might be
Maybe it's guessing correctly, maybe its checking and hunting down answers.
Historical candidates for smartish and dumb
Ptolemy vs Copernicus: Was it really easier to construct a complex system of patterns than to gather lots of data and look for the simplest model of it?
Germ theory vs humours, spirits, etc: We knew that invisible things, such as wind, were real; why didn't we guess that there might be others?
Bowling balls, feathers and classical mechanics: While this is arguably a more surprising result, still we can ask why it took us so long for us to make this guess that was checkable.3
But we don't all check the work done by the smart people who pioneered these ideas. This is a crucial point (see below).
The truth comes out
True things tend to stay true, whether or not we're right about them. For this reason, they force their way to our attention over time.4
2 Guessing
The unity behind all intelligence is "the goal of improving the reliability of predictions by exploiting the redundancy of sensory massages—in other words, intelligence helps us to guess right", according to Barlow. 5
He says intelligence is about detecting new, non-chance associations (patterns) in an environment6, and that there are three distinct tasks that make up guessing correctly: formulating the guess, testing (checking) it, and working out (elaborating) the implications.7
Intelligence and learning might be unconnected
On Macphail's claim8 that there is no apparent correlation between learning and intelligence in many species, see Barlow9 and Shettleworth.10
Intelligence might be about perception
Barlow says intelligence is about perception, not learning.11
An absolute measure of intelligence
Barlow also says that information theory, combined with statistics, can be used to define an absolute scale of intelligence:
"The idea that there is an absolute zero of intelligence, where none of the available information about a new association is used, or 100 per cent intelligence, where all of it is used, may be new to some people, as will be the idea that one aspect of intelligence is in principle measurable on an absolute scale, free of reference to population norms."12
Other work has been done on absolute measures of intelligence.13
IQ
An absolute measure of intelligence would be an impressive improvement over current tests like IQ, which can feel unsatisfying.14
3 Checking
Nothing to do with learning ability or perceptual ability, per se, is the prudent, effective armory of right-answer-finding tools called science and logic. Checking one's work methodically, notwithstanding the apparent wiz kids who don't do it in elementary school, seems smart, i.e. intelligent.
Both a natural sprinter, and the author, might improve in their abilities if they were to learn techniques of sprinting that have been checked by the scientific method.15
Feynman's Cargo Cult Science
There are always crazy ideas out there. We should check them. To do so:
- bend over backwards to report everything you find, to help others see the value of your idea-checking work;
- don't fool yourself (and you're the easiest one to fool), and then it will be easy to not fool your fellow checkers—by just being honest;
- don't fool outsiders, as a matter of integrity.16
Side note—for machines, easy is hard and hard is easy
The gist of the last seventy years of artificial intelligence is: The things we think are difficult turn out to be easy for machines (formal logic, mathematics, working without rest), and the things we think are easy turn out to be difficult for machines (image and speech recognition, common sense).17
Pseudoscience
Consider cargo cults, witch doctors, UFOlogy, ESP-ology, reflexology.18
A shining example of a science—and disappointment
Feynman describes a scientist named 'Young' going to great rational lengths to make sure he knew how his rats were finding food.19 Then, Feynman says, no one in his field followed his lead; instead, they made dumb mistakes.
He took away the information
Taking away all the clues from the rats' environment rendered them unable to find the food. This jibes with what Barlow says, that intelligence is about perception, not memory.
Reasons to reproduce checks
Reason 1: to make sure the person who says they had the right answer actually did.
Reason 2: to make sure there's nothing funny about your setup that will lead you to misinterpret your results.
4 Fighting
Fight or flight are the two options. Fighting all the time, and flight-ing all the time, are bad strategies. The choice should depend on the challenge, the given environmental circumstances.
A lion, a crocodile, a spreadsheet. All are matters of fight or flight.
Fighting for guesses
If one person fights to defend a guess because it feels good, and another person works on checking the guess prior to fighting for it, which one is more intelligent? It's not obvious. It depends on the environment.
Darwin's belated fight
[During the livestream, it was said that:] Darwin was reluctant to publish because he didn't want to take on the fight against religious authorities. He was pushed to do so by a letter from Alfred Wallace, who had independently developed the same ideas.20
[Update! Upon checking the above claim, we found that recent scholarship has belied the idea: Darwin, it is now thought, was not afraid, he was just busy being thorough with the evolution work, and working on other things, and occasionally in bad health.21]
Science is so recent, but babies aren't
On the idea that scientists are like babies, see Gopnik et. al.22
5 Recap
Is there intelligence without an environment? Is checking 'smart', or 'intelligent'? Which is intelligent: fight, flight, both, neither? We don't know.
References
Barlow, H. B. (2004). Guessing and intelligence. (pp. 382–384). In Gregory (2004).
BBC Two (2014). Brian Cox visits the world's biggest vacuum — Human Universe - BBC. Uploaded 24th Oct. 2014. https://youtu.be/E43-CfukEgs Retrieved 2nd Nov. 2020.
Copi, I. M. (1972). Introduction to Logic. Macmillan, 4th ed. No ISBN. Webpages: https://www.amazon.com/Introduction-Logic-Irving-M-Copi/dp/B000J54UWU https://books.google.com/books/about/Introduction_to_Logic.html?id=sxbszAEACAAJ https://lccn.loc.gov/70171565
Deary, I. J. (2001). Intelligence: A Very Short Introduction. Oxford. ISBN: 978-0192893215. Searches: https://www.amazon.com/s?k=978-0192893215 https://www.google.com/search?q=isbn+978-0192893215 https://lccn.loc.gov/2001269139
Feynman, R. (1974). Cargo cult science. Engineering and Science, 7(37), 10–13. http://calteches.library.caltech.edu/3043/1/CargoCult.pdf Retrieved 20th Mar. 2019.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. ISBN 978-0262035613. Ebook available at: https://www.deeplearningbook.org/ Searches: https://www.amazon.com/s?k=978-0262035613 https://www.google.com/search?q=isbn+978-0262035613 https://lccn.loc.gov/2016022992
Gopnik, A., Meltzoff, A. N., & Kuhl, P. K. (1999). The Scientist in the Crib: What Early Learning Tells Us About the Mind. Perennial / HarperCollins. ISBN: 0688159885. Searches: https://www.amazon.com/s?k=0688159885 https://www.google.com/search?q=isbn+0688159885 https://lccn.loc.gov/99024247
Gregory, R. L. (Ed.) (2004). The Oxford Companion to the Mind. Oxford University Press, 2nd ed. ISBN: 0198662246. Searches: https://www.amazon.com/s?k=0198662246 https://www.google.com/search?q=isbn+0198662246 https://lccn.loc.gov/2004275127
Hart-Davis, A. (Ed.) (2009). Science: The Definitive Visual Guide. DK. ISBN 978-0756689018. Searches: https://www.amazon.com/s?k=978-0756689018 https://www.google.com/search?q=isbn+978-0756689018
Legg, S., & Hutter, M. (2007). Universal intelligence: A definition of machine intelligence. Minds & Machines, 17(4), 391–444. December 2007. https://arxiv.org/abs/0712.3329 Retrieved ca. 10 Mar. 2019.
Macphail, E. M. (1982). Brain and Intelligence in Vertebrates. Oxford. Book pending receipt by Retraice. ISBN 978-0198545514. Searches: https://www.amazon.com/s?k=978-0198545514 https://www.google.com/search?q=isbn+978-0198545514 https://lccn.loc.gov/82166301
Margin (2020/10/26). Ma7: Reading and Writing. retraice.com. https://www.retraice.com/segments/ma7 Retrieved 27th Oct. 2020.
Retraice (2020/09/07). Re1: Three Kinds of Intelligence. retraice.com. https://www.retraice.com/segments/re1 Retrieved 22nd Sep. 2020.
Retraice (2020/10/28). Re8: Strange Machines. retraice.com. https://www.retraice.com/segments/re8 Retrieved 29th Oct. 2020.
Shettleworth, S. J. (2010). Cognition, Evolution, and Behavior. Oxford, 2nd ed. ISBN: 978-0195319842. Searches: https://www.amazon.com/s?k=978-0195319842 https://www.google.com/search?q=isbn+978-0195319842 https://lccn.loc.gov/2009017840
van Wyhe, J. (2007). Mind the gap: did Darwin avoid publishing his theory for many years? Notes Rec. R. Soc., 61, 177–205. https://royalsocietypublishing.org/doi/10.1098/rsnr.2006.0171 Retrieved 2nd Nov. 2020.
Yudkowsky, E. (2013). Intelligence explosion microeconomics. Machine Intelligence Research Institute. Technical report 2013-1. https://intelligence.org/files/IEM.pdf Retrieved ca. 9th Dec. 2018.
1https://www.retraice.com/retraice
2Yudkowsky (2013) p. 9. See also Retraice (2020/10/28).
3For a video of the phenomenon in question, see BBC Two (2014).
4Feynman (1974) p. 11.
5Barlow (2004) p. 384.
6Barlow (2004) p. 382. Cf. Margin (2020/10/26) on detecting.
7Barlow (2004) p. 383.
8Macphail (1982).
9Barlow (2004) p. 383.
10Shettleworth (2010) p. 38, pp. 188-189, pp. 231-232.
11Barlow (2004) p. 384.
12Barlow (2004) p. 383.
13See Legg & Hutter (2007), for example.
14Deary (2001) p. 102 ff.
15The analogy is borrowed from Copi (1972) pp. 3-4.
16Feynman (1974) pp. 11-12. These key points were mistakenly not mentioned during the livestream, but will be amended during segment Re11.
17Goodfellow et al. (2016) p. 1.
18Cf. Retraice (2020/09/07) on UFOs, where we take the subject more seriously than does Feynman, though still with caution.
19Others have not been able to track down the scientist 'Young' based on Feynman's description. For example: https://www.realclearscience.com/blog/2014/02/the_rat_experiment_you_dont_know_about_but_should.html and https://en.wikipedia.org/wiki/Talk:Cargo_cult_science
20Hart-Davis (2009) p. 198.
21van Wyhe (2007).
22Gopnik et al. (1999) p. 155 ff.
