(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.)

Re18: Plan of Attack

Retraice^1

Our plan to test the 11 hypotheses begins with `objective observables' and numbers.

Air date: Monday, 7th Mar. 2022, 4:40 PM Eastern/US.

Recap

The hypotheses are answers to the question `What's going on out there?' (What's GOOT). They're based on (filtered down by) the idea that some things will be in the history books (`current history') and most things won't (stuff we don't care about^2).

We gave examples in Re17^3 : covid, Jan 6th, Ukraine 2022.

And then things got interesting

It's worth asking how much `current history' these events will ultimately amount to, especially if the wild predictions of Kurzweil and others^4 come to pass. The pace of change, however measured, makes all the difference here. A sufficiently rapid rate (speed), or rate of increase (acceleration) of change in the future will leave our era vanishingly little space in the book of history.

The hypotheses, again

H-1) Space H-2) Technology H-3) Death H-4) China H-5) US Civil War H-6) Environment H-7) Betterment H-8) Intelligence Differences (GOFID^5) H-9) Darkness (especially good guys') H-10) Wealth H-11) Wild cards

The questions that follow

Where did they come from?

The `chatter' (daily news, daily conversations) is a good way of staying in touch with the present, or `reality now'. And books (and the discussion of books) is a good way of detecting the things that might qualify as `current history'. If the books correspond to current history, the chatter corresponds to pages of those books (including the many deleted pages).

So what? What do we do with them?

Once we have hypotheses, we (at least) need a way of testing them.

A pile of numbers

Keep firmly in mind:

A hypothesis is not a prediction, but it can make predictions.

And, the way we're thinking about it now:

A hypothesis is in principle reducible to `objective observables', or `a pile of numbers'.

Definitions

Let's use these rough definitions: * objective: about things in the shared external world (a breeze, a tree, a person); The gold-standard of objectivity is the S.I. units (second, metre, kilogram, ampere, kelvin, mole, candela), which are constructed using `defining constants' with the aim of removing all disagreement between persons about fundamental aspects of the world in order to enable productive cooperation between those persons.^6 In principle, we could use these units to physically identify something (a breeze, a tree, a person) so that everyone would agree about what it is. In principle! * subjective: about things in someone's internal world of experience (a belief in air, seeing a tree move, thinking about it); * observable: sense-able by multiple humans (a tree blowing in the wind, a person standing watching, the absence of a visible object striking the tree); We can take observation to the limit, and say that nothing is `observable' except by the five sense organs (eyes, ears, nose, mouth and skin). But we'd have to add a sixth, `the mind's eye'^7 , to account for sensing one's own thoughts, feelings, etc. The sixth sense, though, would only observe subjective things, while the first five would observe objective things. Although a case can be made that a thought like 2 + 2 = 4 is objectively observable to any mind. And all this talk about sensing is to say nothing about whether a person is conscious of the sensation. But we can safely ignore all sensation that isn't conscious when talking about `observable' things, since unconsciously observing a thing breaks the meaning of `observe'. * unobservable: not directly sense-able by multiple humans (the molecules hitting tree branches, the experiences of a person, memories of previous breezes); * quantitative: about `how much' or `how many' things (the number of dinitrogen molecules in a breeze, the duration of it in seconds, the force experienced by the tree in newtons); * qualitative: about the `who / what / where / when / why / which / whether' of things (the definition of a dinitrogen molecule, the person who saw the breeze, the momentary time and direction of the breeze, the reason we use the word `breeze', the spatial boundaries of the atmosphere that we consider `this breeze' and when it started and ended, whether the breeze is objective / subjective / observable / unobservable).

Even with these semi-rigid definitions, it's hard to be systematic. A thing can be quantifiable, though better considered qualitative than quantitative. I.e. while it is often possible to quantify something, it is not always good to do so. And, as the saying goes, sometimes quantity has a quality all its own. We'll use (and improve on) these terms to analyze the aspects of a thing for the purposes of testing hypotheses, not expecting to settle philosophical debates about language and reality.

Ignoring quality

Trying to consider quality and quantity at the same time is hard. It might require a genius intellect to juggle so many aspects of a thing, and then who would be the audience for these hard-to-have thoughts? If we force our hypotheses to be only the objective observables, and focus on the quantitative aspects, we end up with a manageable pile of numbers. We can consider these numbers to be the essence of the hypothesis itself, assuming the qualitative can be safely ignored (this is a big assumption, and might prove false).

Ignoring quality is also relative, not absolute. Quality, as we've defined it, can't be strictly ignored, because the numbers must be `of' something not quantitative, i.e. something qualitative. Our pile of numbers is really a pile of counted or measured things.

An example--China

Take, for example, China (H-4): Graham Allison says^8 the U.S. and China are `destined for war' unless they avoid `Thucydides's trap', i.e. stumbling into war based on an established power fearing an up-and-comer, despite both parties desiring peace.^9 He's not shooting from the hip; he's looking at qualitative things (e.g. China's `century of humiliation'^10), naturally, but also quantitative things (e.g. GDP, imports, exports, reserves^11). If we start from the objective observable things, and especially quantitative things, maybe we'll avoid a lot of confusion and disagreement, though presumably at the expense of something that will have to be added back later.

Predictions

The pile of numbers might reveal patterns. Patterns allow us to interpolate and extrapolate--the equivalent of making predictions. We can then go check to see if the prediction matches reality. If a prediction agrees with an observation of reality then the hypothesis gets stronger--it becomes less and less likely that the hypothesis is wrong, more and more likely that it's right.

A note on induction

This whole business about the hypothesis getting stronger as more evidence agrees with it--this is not as straightforward as it seems. There are deep philosophical questions about inductive inference.^12 For now, let's pretend that there aren't, and bet that common sense will eventually be confirmed by science and philosophy.

Can and should

Suppose you test a hypothesis and become very confident in it. What can you do? If you've discovered a huge asteroid or a roving black hole about to hit the Earth, what can you do? But for most hypotheses, there will be a range of options available.

The next step is to narrow the list down to what you should do. Some guidance on this task can be found in Frankfurt (1988) and Retraice (2020/11/10).

Note

It took a long time to get to the point of having a specific, constructive, objective, meaningful way forward on the question `What's GOOT?' If Re17/Re18 have seemed a bit overloaded, or frantic, it has to do with that.

_

References

Allison, G. (2018). Destined for War: Can America and China Escape Thucydides's Trap?. Mariner Books. ISBN: 978-1328915382. Searches: https://www.amazon.com/s?k=9781328915382 https://www.google.com/search?q=isbn+9781328915382 https://lccn.loc.gov/2017005351

BIPM (2019). The International System of Units (SI). International Bureau of Weights and Measures, 9th ed. ISBN: 978-9282222720. https://www.bipm.org/utils/common/pdf/si-brochure/SI-Brochure-9.pdf Retrieved 22nd Apr. 2020.

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

Frankfurt, H. G. (1988). The Importance of What We Care About. Cambridge. ISBN: 978-0521336116. Searches: https://www.amazon.com/s?k=978-0521336116 https://www.google.com/search?q=isbn+978-0521336116 https://lccn.loc.gov/87026941

Good, I. J. (1965). Speculations concerning the first ultraintelligent machine. Advances in Computers, 6, 31-88. https://exhibits.stanford.edu/feigenbaum/catalog/gz727rg3869 Retrieved 27th Oct. 2020.

Goodman, N. (1983). Fact, Fiction, and Forecast. Harvard University Press, 4th revised ed. ISBN: 0674290712. Searches: https://www.amazon.com/s?k=0674290712 https://www.google.com/search?q=isbn+0674290712 https://lccn.loc.gov/82015764

Horwich, P. (1982). Probability and Evidence. Cambridge. First published 1982; first paperback 2011; this Cambridge Philosophy Classics edition 2016. ISBN: 978-1316507018. Searches: https://www.amazon.com/s?k=978-1316507018 https://www.google.com/search?q=isbn+978-1316507018 https://lccn.loc.gov/2015049717

Keynes, J. M. (1920). A Treatise on Probability: The Connection Between Philosophy and the History of Science. Wildside Press. ISBN: 978-1434406965. Searches: https://www.amazon.com/s?k=9781434406965 https://www.google.com/search?q=isbn+9781434406965 https://lccn.loc.gov/2004041359

Kurzweil, R. (1990). The Age of Intelligent Machines. MIT Press. ISBN: 0262111217. Searches: https://www.amazon.com/s?k=0262111217 https://www.google.com/search?q=isbn+0262111217 https://lccn.loc.gov/89013606

Kurzweil, R. (1999). The Age of Spiritual Machines: When Computers Exceed Human Intelligence. Penguin Books. ISBN: 0140282025. Searches: https://www.amazon.com/s?k=0140282025 https://www.google.com/search?q=isbn+0140282025 https://lccn.loc.gov/98038804

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

Okasha, S. (2002). Philosophy of Science: A Very Short Introduction. Oxford University Press. ISBN: 0192802836. Searches: https://www.amazon.com/s?k=0192802836 https://www.google.com/search?q=isbn+0192802836 https://lccn.loc.gov/2002510456

Polya, G. (1954). Mathematics and Plausible Reasoning [Two Volumes in One]. Martino Fine Books. ISBN: 978-1614275572. Originally published 1954. This ed. 2014. Searches: https://www.amazon.com/s?k=9781614275572 https://www.google.com/search?q=isbn+9781614275572 https://lccn.loc.gov/53006388

Reichenbach, H. (1951). The Rise of Scientific Philosophy. University of California Press. ISBN: 0520010558. Searches: https://www.amazon.com/s?k=0520010558 https://www.google.com/search?q=isbn+0520010558 https://lccn.loc.gov/51009723

Retraice (2020/11/10). Re13: The Care Factor. retraice.com. https://www.retraice.com/segments/re13 Retrieved 10th Nov. 2020.

Retraice (2022/03/07). Re17: Hypotheses to Eleven. retraice.com. https://www.retraice.com/segments/re17 Retrieved 17th Mar. 2022.

Russell, B. (1948). Human Knowledge: Its Scope and Limits. Routledge. First published in 1948. This edition 1992. ISBN: 0415083028. Searches: https://archive.org/search.php?query=Human%20Knowledge%3A%20Its%20Scope%20and%20Limits https://www.amazon.com/s?k=0415083028 https://www.google.com/search?q=isbn+0415083028 https://lccn.loc.gov/94209784

Sacks, O. (2010). The Mind's Eye. Vintage. ISBN: 978-0307473028. Searches: https://www.amazon.com/s?k=9780307473028 https://www.google.com/search?q=isbn+9780307473028 https://lccn.loc.gov/2010012791

Sainsbury, R. M. (2009). Paradoxes. Cambridge University Press, 3rd ed. ISBN: 978-0521720793. Searches: https://www.amazon.com/s?k=9780521720793 https://www.google.com/search?q=isbn+9780521720793 https://lccn.loc.gov/2009464288

Skyrms, B. (1966). Choice and Chance: An Introduction to Inductive Logic. Dickenson. No ISBN. Searches: https://www.amazon.com/s?k=choice+and+chance+skyrms https://www.google.com/search?q=choice+and+chance+skyrms https://lccn.loc.gov/66023586

Footnotes

^1 https://www.retraice.com/retraice

^2 Again, it comes down to `care'. See Frankfurt (1988) and Retraice (2020/11/10). Although, strictly speaking, we (as individuals) care about plenty of things that won't end up in history books. For now, let's say that `we' refers to our civilization as a whole, which cannot care about individuals, for the most part. This is true in the same way that you cannot care much about all strangers within 200 miles of you, though in principle you might want to.

^3 Retraice (2022/03/07)

^4 Kurzweil (1990); Kurzweil (1999); Kurzweil (2005); Brockman (2019); Brockman (2015); Good (1965).

^5 Good-ol'-fashioned human intelligence differences, not to do with AI, animals, or other kinds of intelligence.

^6 BIPM (2019) p. 122.

^7 Cf. Sacks (2010) pp. 219-230.

^8 Allison (2018).

^9 Allison (2018) p. 29.

^10 Allison (2018) p. 161.

^11 All in dollars, Allison (2018) p. 6.

^12 Russell (1948) p. 418 ff.; Okasha (2002) chpt 2; Reichenbach (1951) pp. 176-190; Skyrms (1966) chpts. 2-4; Sainsbury (2009) chpt. 5; Goodman (1983) p. 72 ff.; Horwich (1982) chpt. 4; Keynes (1920) part III; Polya (1954) pp. v-vi, chpts. I and XI.