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(The below text version of the notes is for search purposes and convenience. See the PDF version for proper formatting such as bold, italics, etc., and graphics where applicable. Copyright: 2022 Retraice, Inc.)
Re50: What About AI Though? (WAAIT)
Retraice^1
Remembering the big thing that's bigger than all the other big things.
Air date: Monday, 14th Nov. 2022, 11:00 PM Eastern/US.
AI, at parties, in three dimensions
Paying attention to AI leads to two basic results: the sense that `AI is in everything', and then an over-emphasis on some particular aspect of AI, a collapse into specialization.^2 And if it is `in everything', is AI `at parties', maybe in the music, or in the courtship?^3 If it is, it would make things more predictable, which businesses and governments like (for purposes of optimizing themselves toward their goals), and which humans like (for the same reasons, but only to a point).
`What about AI?' has a sort of acid-test way of stripping any topic down to the essential parts that are relevant to a hyper-rational phenomenon (e.g. AI itself).^4
Answers to the question can be broken down into three dimensions:
1. better, worse (value);
+ Life can be so good,^5 and so bad.^6 How does AI affect these two ends of the spectrum? Side note: If we can look after small groups, we can look after all humans. (Right? Should be, anyway.) + We need AI to see and do what we can't: o We can't do all the math, we can't operate all the machinery. o We are all mostly unaware of what's going on, around us and out there. We can't see it. o AI is good at `seeing' in ways that we aren't.^7
2. now, later (time): AI has affected the past, present, and will affect the future.
3. here, there (space): AI affects things close and far.
What is AI, again?
* physically: + algorithms (more refined; precise and improving on imprecise); - Turing machine, computer-science-based limits? + hardware (better, more pervasive; sensors, processors); - cybernetics, control-theory-based limits? + inventors (highly incentivized engineers);^8 + controllers (whoever can play the old power games best).^9 * prediction machines;^10 * mind-environment changers;^11 * automators;^12 * autonomous actors;^13 * pattern detectors;^14 * Ideas from previous Retraice segments:^15 + Re6: Interfaces between goals and environments. + Re7: Artifacts that absorb goals, and become animate. + Re8: Creatures: we should worry about reproduction, communication, control, energy sources, `looking for' things, at least as much as we worry about intelligence.^16 + Re9: They can already see us, better than we see ourselves.^17 + Re10: Guessing (intelligence), checking (tests), fighting (battlefields). + Re11: Travelers (intensionality?), intelligent things that can go places in time a space. + Re22: "Computers, which are chain-reaction controllers, and which make AI handling of information possible, and which are inherently vulnerable to hacking, are causing some humans to know others better than they know themselves, and thereby to control them, though computer-controlled machinery could take control if the motivation to control, which humans have, were to occur, naturally or by design, in the chain-reactions."
__
References
Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Review Press. ISBN: 978-1633695672. Searches: https://www.amazon.com/s?k=978-1633695672 https://www.google.com/search?q=isbn+978-1633695672 https://lccn.loc.gov/2017049211
Brockman, J. (Ed.) (2015). What to Think About Machines That Think: Today's Leading Thinkers on the Age of Machine Intelligence. Harper Perennial. ISBN: 978-0062425652. Searches: https://www.amazon.com/s?k=978-0062425652 https://www.google.com/search?q=isbn+978-0062425652 https://lccn.loc.gov/2016303054
Brockman, J. (Ed.) (2019). Possible Minds: Twenty-Five Ways of Looking at AI. Penguin. ISBN: 978-0525557999. Searches: https://www.amazon.com/s?k=978-0525557999 https://www.google.com/search?q=isbn+978-0525557999 https://lccn.loc.gov/2018032888
Crawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press. ISBN: 978-0300209570. Searches: https://www.amazon.com/s?k=9780300209570 https://www.google.com/search?q=isbn+9780300209570 https://lccn.loc.gov/2020947842
Dennett, D. C. (1996). Darwin's Dangerous Idea: Evolution And The Meanings Of Life. Simon & Schuster. ISBN: 068482471X. Searches: https://www.amazon.com/s?k=068482471X https://www.google.com/search?q=isbn+068482471X https://lccn.loc.gov/94049158
Dietterich, T. G. (2015). How to prevent an intelligence explosion. (pp. 380-383). In Brockman (2015).
Dyson, G. (2019). The third law. (pp. 31-40). In Brockman (2019).
Gerrish, S. (2018). How Smart Machines Think. The MIT Press. ISBN: 978-0262038409. Searches: https://www.amazon.com/s?k=9780262038409 https://www.google.com/search?q=isbn+9780262038409 https://lccn.loc.gov/2017059862
Greene, R. (1998). The 48 Laws Of Power. Penguin. ISBN: 978-0140280197. Searches: https://www.amazon.com/s?k=9780140280197 https://www.google.com/search?q=isbn+9780140280197 https://lccn.loc.gov/98041387
Hoffman, D. (2019). The Case Against Reality: Why Evolution Hid the Truth from Our Eyes. W. W. Norton & Company. ISBN: 978-0393254693. Searches: https://www.amazon.com/s?k=978-0393254693 https://www.google.com/search?q=isbn+978-0393254693 https://lccn.loc.gov/2019006962
Kissinger, H. A., Schmidt, E., & Huttenlocher, D. (2021). The Age of AI. Little, Brown and Company. ISBN: 978-0316273800. Searches: https://www.amazon.com/s?k=9780316273800 https://www.google.com/search?q=isbn+9780316273800 https://lccn.loc.gov/2021943914
Kurzweil, R. (2005). The Singularity Is Near: When Humans Transcend Biology. Penguin. ISBN: 978-0143037880. Searches: https://www.amazon.com/s?k=978-0143037880 https://www.google.com/search?q=isbn+978-0143037880 https://lccn.loc.gov/2004061231
Pinker, S. (2011). The Better Angels of Our Nature: Why Violence Has Declined. Penguin Publishing Group. ISBN: 978-0143122012. Searches: https://www.amazon.com/s?k=978-0143122012 https://www.google.com/search?q=isbn+978-0143122012 https://lccn.loc.gov/2011015201
Retraice (2020/09/08). Re2: Tell the People, Tell Foes. retraice.com. https://www.retraice.com/segments/re2 Retrieved 22nd Sep. 2020.
Retraice (2020/10/25). Re6: Interface. retraice.com. https://www.retraice.com/segments/re6 Retrieved 26th Oct. 2020.
Retraice (2020/10/26). Re7: Artifactual Goals. retraice.com. https://www.retraice.com/segments/re7 Retrieved 27th Oct. 2020.
Retraice (2020/10/28). Re8: Strange Machines. retraice.com. https://www.retraice.com/segments/re8 Retrieved 29th Oct. 2020.
Retraice (2020/10/31). Re9: They Can See You. retraice.com. https://www.retraice.com/segments/re9 Retrieved 31st Oct. 2020.
Retraice (2020/11/02). Re10: Living to Guess Another Day. retraice.com. https://www.retraice.com/segments/re10 Retrieved 2nd Nov. 2020.
Retraice (2020/11/04). Re11: Travel. retraice.com. https://www.retraice.com/segments/re11 Retrieved 4th Nov. 2020.
Retraice (2022/10/19). Re22: Computer Control. retraice.com. https://www.retraice.com/segments/re22 Retrieved 19th Oct. 2022.
Russell, S. (2019). Human Compatible: Artificial Intelligence and the Problem of Control. Viking. ISBN: 978-0525558613. Searches: https://www.amazon.com/s?k=978-0525558613 https://www.google.com/search?q=isbn+978-0525558613 https://lccn.loc.gov/2019029688
Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson, 4th ed. ISBN: 978-0134610993. Searches: https://www.amazon.com/s?k=978-0134610993 https://www.google.com/search?q=isbn+978-0134610993 https://lccn.loc.gov/2019047498
Smallberg, G. (2015). No shared theory of mind. (pp. 297-299). In Brockman (2015).
Weizenbaum, J. (1976). Computer Power and Human Reason: From Judgment to Calculation. W. H. Freeman and Company. ISBN: 0716704633. Also available at: https://archive.org/details/computerpowerhum0000weiz
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.
Footnotes
^1 https://www.retraice.com/retraice
^2 Men tend to focus as hunters, women tend to scan as gathers; a majority of those involved in thinking about AI as such are men (it seems), hence the collapse into focused specialization. This is obviously just an impression, and only intended as a possible explanation for the specialization over-emphasis tendency. A counterargument would be that it's the economics of modern life that forces specialization, not sex differences. Both can be true, and probably are. Note: Renaissance men and women are not generalists; they're in the middle between specialists and generalists. Generalists have the discipline (really, lack thereof) that leads them to move on before knowing too much about any particular subject.
^3 It occurred to us after the livestream that, since young people interact so much more via their phones, AI is indeed already `at' parties and `in' the courtship there.
^4 Cf. Dennett on Darwinism as `universal acid', Dennett (1996) chpt. 3; see also Hoffman (2019) pp. 56-57.
^5 Consider the optimists: Pinker (2011); Kurzweil (2005).
^6 Imagine Joseph Stalin but with the technological means of modern China.
^7 Kissinger et al. (2021) pp. 13-17.
^8 Cf. Yudkowsky (2013) pp. 20-21 on the effect of having "faster engineers", i.e. "the hypothetical scenario where the researchers are running on computers."
^9 Retraice (2020/09/08) p. 3 on control. Cf. Greene (1998) and below.
^10 Agrawal et al. (2018).
^11 Russell (2019) pp. 8-9. Humans are also `mind-environment changers' in a sense, if we think of power games and manipulation. Greene (1998).
^12 Crawford (2021) chpt. 2.
^13 Retraice (2020/10/28); Russell & Norvig (2020) p. 1001.
^14 Gerrish (2018) pp. 129-131.
^15 Retraice (2020/10/25); Retraice (2020/10/26); Retraice (2020/10/28); Retraice (2020/10/31); Retraice (2020/11/02); Retraice (2020/11/04); Retraice (2022/10/19).
^16 See Retraice (2020/10/28) and: Dyson (2019) p. 40; Smallberg (2015) p. 299; Dietterich (2015) p. 382. On control, see also Retraice (2020/09/08) p. 3, and Weizenbaum (1976) pp. 124-126.
^17 Cf. Retraice (2022/10/19) on "causing some humans to know others better than they know themselves."
By Retraice, Inc.(The below text version of the notes is for search purposes and convenience. See the PDF version for proper formatting such as bold, italics, etc., and graphics where applicable. Copyright: 2022 Retraice, Inc.)
Re50: What About AI Though? (WAAIT)
Retraice^1
Remembering the big thing that's bigger than all the other big things.
Air date: Monday, 14th Nov. 2022, 11:00 PM Eastern/US.
AI, at parties, in three dimensions
Paying attention to AI leads to two basic results: the sense that `AI is in everything', and then an over-emphasis on some particular aspect of AI, a collapse into specialization.^2 And if it is `in everything', is AI `at parties', maybe in the music, or in the courtship?^3 If it is, it would make things more predictable, which businesses and governments like (for purposes of optimizing themselves toward their goals), and which humans like (for the same reasons, but only to a point).
`What about AI?' has a sort of acid-test way of stripping any topic down to the essential parts that are relevant to a hyper-rational phenomenon (e.g. AI itself).^4
Answers to the question can be broken down into three dimensions:
1. better, worse (value);
+ Life can be so good,^5 and so bad.^6 How does AI affect these two ends of the spectrum? Side note: If we can look after small groups, we can look after all humans. (Right? Should be, anyway.) + We need AI to see and do what we can't: o We can't do all the math, we can't operate all the machinery. o We are all mostly unaware of what's going on, around us and out there. We can't see it. o AI is good at `seeing' in ways that we aren't.^7
2. now, later (time): AI has affected the past, present, and will affect the future.
3. here, there (space): AI affects things close and far.
What is AI, again?
* physically: + algorithms (more refined; precise and improving on imprecise); - Turing machine, computer-science-based limits? + hardware (better, more pervasive; sensors, processors); - cybernetics, control-theory-based limits? + inventors (highly incentivized engineers);^8 + controllers (whoever can play the old power games best).^9 * prediction machines;^10 * mind-environment changers;^11 * automators;^12 * autonomous actors;^13 * pattern detectors;^14 * Ideas from previous Retraice segments:^15 + Re6: Interfaces between goals and environments. + Re7: Artifacts that absorb goals, and become animate. + Re8: Creatures: we should worry about reproduction, communication, control, energy sources, `looking for' things, at least as much as we worry about intelligence.^16 + Re9: They can already see us, better than we see ourselves.^17 + Re10: Guessing (intelligence), checking (tests), fighting (battlefields). + Re11: Travelers (intensionality?), intelligent things that can go places in time a space. + Re22: "Computers, which are chain-reaction controllers, and which make AI handling of information possible, and which are inherently vulnerable to hacking, are causing some humans to know others better than they know themselves, and thereby to control them, though computer-controlled machinery could take control if the motivation to control, which humans have, were to occur, naturally or by design, in the chain-reactions."
__
References
Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Review Press. ISBN: 978-1633695672. Searches: https://www.amazon.com/s?k=978-1633695672 https://www.google.com/search?q=isbn+978-1633695672 https://lccn.loc.gov/2017049211
Brockman, J. (Ed.) (2015). What to Think About Machines That Think: Today's Leading Thinkers on the Age of Machine Intelligence. Harper Perennial. ISBN: 978-0062425652. Searches: https://www.amazon.com/s?k=978-0062425652 https://www.google.com/search?q=isbn+978-0062425652 https://lccn.loc.gov/2016303054
Brockman, J. (Ed.) (2019). Possible Minds: Twenty-Five Ways of Looking at AI. Penguin. ISBN: 978-0525557999. Searches: https://www.amazon.com/s?k=978-0525557999 https://www.google.com/search?q=isbn+978-0525557999 https://lccn.loc.gov/2018032888
Crawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press. ISBN: 978-0300209570. Searches: https://www.amazon.com/s?k=9780300209570 https://www.google.com/search?q=isbn+9780300209570 https://lccn.loc.gov/2020947842
Dennett, D. C. (1996). Darwin's Dangerous Idea: Evolution And The Meanings Of Life. Simon & Schuster. ISBN: 068482471X. Searches: https://www.amazon.com/s?k=068482471X https://www.google.com/search?q=isbn+068482471X https://lccn.loc.gov/94049158
Dietterich, T. G. (2015). How to prevent an intelligence explosion. (pp. 380-383). In Brockman (2015).
Dyson, G. (2019). The third law. (pp. 31-40). In Brockman (2019).
Gerrish, S. (2018). How Smart Machines Think. The MIT Press. ISBN: 978-0262038409. Searches: https://www.amazon.com/s?k=9780262038409 https://www.google.com/search?q=isbn+9780262038409 https://lccn.loc.gov/2017059862
Greene, R. (1998). The 48 Laws Of Power. Penguin. ISBN: 978-0140280197. Searches: https://www.amazon.com/s?k=9780140280197 https://www.google.com/search?q=isbn+9780140280197 https://lccn.loc.gov/98041387
Hoffman, D. (2019). The Case Against Reality: Why Evolution Hid the Truth from Our Eyes. W. W. Norton & Company. ISBN: 978-0393254693. Searches: https://www.amazon.com/s?k=978-0393254693 https://www.google.com/search?q=isbn+978-0393254693 https://lccn.loc.gov/2019006962
Kissinger, H. A., Schmidt, E., & Huttenlocher, D. (2021). The Age of AI. Little, Brown and Company. ISBN: 978-0316273800. Searches: https://www.amazon.com/s?k=9780316273800 https://www.google.com/search?q=isbn+9780316273800 https://lccn.loc.gov/2021943914
Kurzweil, R. (2005). The Singularity Is Near: When Humans Transcend Biology. Penguin. ISBN: 978-0143037880. Searches: https://www.amazon.com/s?k=978-0143037880 https://www.google.com/search?q=isbn+978-0143037880 https://lccn.loc.gov/2004061231
Pinker, S. (2011). The Better Angels of Our Nature: Why Violence Has Declined. Penguin Publishing Group. ISBN: 978-0143122012. Searches: https://www.amazon.com/s?k=978-0143122012 https://www.google.com/search?q=isbn+978-0143122012 https://lccn.loc.gov/2011015201
Retraice (2020/09/08). Re2: Tell the People, Tell Foes. retraice.com. https://www.retraice.com/segments/re2 Retrieved 22nd Sep. 2020.
Retraice (2020/10/25). Re6: Interface. retraice.com. https://www.retraice.com/segments/re6 Retrieved 26th Oct. 2020.
Retraice (2020/10/26). Re7: Artifactual Goals. retraice.com. https://www.retraice.com/segments/re7 Retrieved 27th Oct. 2020.
Retraice (2020/10/28). Re8: Strange Machines. retraice.com. https://www.retraice.com/segments/re8 Retrieved 29th Oct. 2020.
Retraice (2020/10/31). Re9: They Can See You. retraice.com. https://www.retraice.com/segments/re9 Retrieved 31st Oct. 2020.
Retraice (2020/11/02). Re10: Living to Guess Another Day. retraice.com. https://www.retraice.com/segments/re10 Retrieved 2nd Nov. 2020.
Retraice (2020/11/04). Re11: Travel. retraice.com. https://www.retraice.com/segments/re11 Retrieved 4th Nov. 2020.
Retraice (2022/10/19). Re22: Computer Control. retraice.com. https://www.retraice.com/segments/re22 Retrieved 19th Oct. 2022.
Russell, S. (2019). Human Compatible: Artificial Intelligence and the Problem of Control. Viking. ISBN: 978-0525558613. Searches: https://www.amazon.com/s?k=978-0525558613 https://www.google.com/search?q=isbn+978-0525558613 https://lccn.loc.gov/2019029688
Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson, 4th ed. ISBN: 978-0134610993. Searches: https://www.amazon.com/s?k=978-0134610993 https://www.google.com/search?q=isbn+978-0134610993 https://lccn.loc.gov/2019047498
Smallberg, G. (2015). No shared theory of mind. (pp. 297-299). In Brockman (2015).
Weizenbaum, J. (1976). Computer Power and Human Reason: From Judgment to Calculation. W. H. Freeman and Company. ISBN: 0716704633. Also available at: https://archive.org/details/computerpowerhum0000weiz
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.
Footnotes
^1 https://www.retraice.com/retraice
^2 Men tend to focus as hunters, women tend to scan as gathers; a majority of those involved in thinking about AI as such are men (it seems), hence the collapse into focused specialization. This is obviously just an impression, and only intended as a possible explanation for the specialization over-emphasis tendency. A counterargument would be that it's the economics of modern life that forces specialization, not sex differences. Both can be true, and probably are. Note: Renaissance men and women are not generalists; they're in the middle between specialists and generalists. Generalists have the discipline (really, lack thereof) that leads them to move on before knowing too much about any particular subject.
^3 It occurred to us after the livestream that, since young people interact so much more via their phones, AI is indeed already `at' parties and `in' the courtship there.
^4 Cf. Dennett on Darwinism as `universal acid', Dennett (1996) chpt. 3; see also Hoffman (2019) pp. 56-57.
^5 Consider the optimists: Pinker (2011); Kurzweil (2005).
^6 Imagine Joseph Stalin but with the technological means of modern China.
^7 Kissinger et al. (2021) pp. 13-17.
^8 Cf. Yudkowsky (2013) pp. 20-21 on the effect of having "faster engineers", i.e. "the hypothetical scenario where the researchers are running on computers."
^9 Retraice (2020/09/08) p. 3 on control. Cf. Greene (1998) and below.
^10 Agrawal et al. (2018).
^11 Russell (2019) pp. 8-9. Humans are also `mind-environment changers' in a sense, if we think of power games and manipulation. Greene (1998).
^12 Crawford (2021) chpt. 2.
^13 Retraice (2020/10/28); Russell & Norvig (2020) p. 1001.
^14 Gerrish (2018) pp. 129-131.
^15 Retraice (2020/10/25); Retraice (2020/10/26); Retraice (2020/10/28); Retraice (2020/10/31); Retraice (2020/11/02); Retraice (2020/11/04); Retraice (2022/10/19).
^16 See Retraice (2020/10/28) and: Dyson (2019) p. 40; Smallberg (2015) p. 299; Dietterich (2015) p. 382. On control, see also Retraice (2020/09/08) p. 3, and Weizenbaum (1976) pp. 124-126.
^17 Cf. Retraice (2022/10/19) on "causing some humans to know others better than they know themselves."