Below, we share key excerpts from SFI External Prof W. Brian Arthur's (@Stanford, @PARCinc) latest, available at arxiv.org/abs/2104.01868, which we recommend for its elucidation of key blind spots in economic thinking & how to address them...
"Different means 'see' differently—often they reveal different versions of the same object. #MRI looks at body parts and reveals soft tissue structure; #CT scanning looks at the same body parts and reveals bone structure. There is no 'correct' version of internal body parts."
"#Mathematics is powerful in #economics—and necessary—but I don’t believe that it is suited to describing all that is interesting in an economy. In fact I don’t believe that there is any privileged way to view the economy. There are useful ways and less useful ones."
"Nouns are the water economics swims in. Of course in the real economy there are actions."
"#Biology would be hard to imagine without actions—events triggering events, events inhibiting events. So why then is #economics noun-based? One good reason is that any field, as it becomes theoretical, tends to marshal its thinking into concepts..."
"To use algebraic #equations a field of interest must be reduced to #nouns. This is why #biology, which can’t easily be reduced to nouns, is only partially mathematizable."
"For its first 750 years [#algebra] was an art exercised in wordy form by merchant adepts...in the late 1500s symbols arrived, and natural philosophy took notice. Symbolic notations added a further aura of mystery. But whatever the mystique, algebra remained storytelling."
"Because algebraic #mathematics allows only quantifiable nouns & disbars #verbs, it acts as a sieve. What it can’t express it can’t contain, so #processes & actions fall through the sieve & are unexpressed. This noun-restriction causes distortions to the story #economics tells."
"Structural change happens when new industries or new technologies change the character of the economy or its parts, as happened when the agrarian economy gave way to manufacturing. Theory can’t pick up a change in character if its objects of interest don’t change in character."
"Noun-based economics links nouns to nouns via equations. It is easier to analyze these if they hold still, much as it is easier to study a butterfly if we nail it to a board. We purchase understanding by assuming stasis. But all too often the system hangs lifeless, unchanging."
"Once you have an equation system with its x’s, y’s and z’s, it is hard for the system to endogenously generate new variables. So novel products, novel strategies, novel ways to use the system, if they are not already declared as variables ready to exist, can’t easily emerge."
"Many economic problems aren't well defined. The players don’t quite know what situation they are dealing with or who their competitors will be or what strategies will be on hand. They're subject to fundamental uncertainty, so they can’t well-define the 'problem' they're facing."
'Economist W. Brian Arthur recently published a paper called 'Economics in Nouns and Verbs' arguing for more agent-based economic modeling. It’s worth reading in full, but here’s an excerpt...'
ICYMI, this week's SFI Seminar by Fractal Faculty Stuart Firestein (@Columbia) on "what started out ass a very simple-seeming problem [re: #olfaction] and turned out to be very complicated":
"Everything we know about the world comes through these little holes in our head and the skin covering our body, processed through tissue specialized to interpret it."
"The thing to notice about [sight and hearing] is that they're [processing] fairly low-dimensional stimuli."
"Even a simple smell is composed of a VARIETY of molecules, and these are high-dimensional from a chemical point of view. And it's also a somewhat discontinuous stimulus. How do we get from this bunch of molecules to this unitary perception of something like a rose?"
"A key feature of this is talk is that we make sense of what each other are saying IN PART by what they say, but ALSO by what we expect of them."
"Language transmits info against a background of expectations – syntactic, semantic, and this larger cultural spectrum. It's not just the choices of make but [how] we set ourselves up to make later choices."
"I think what really drives [the popularity of the #multiverse in #scifi] is regret... There's a line in @allatoncemovie where #MichelleYeoh is told she's the worst version of herself."
"I don't think we should resist melting brains. I think we should just bite the bullet."
"When you measure the spin of an electron, or the position...what happened to all of the other things you could have seen? Everett's idea is that they're all real. They all become real in that measurement."
- SFI Fractal Faculty @seanmcarroll at @guardian theguardian.com/science/audio/…
"At the level of the equations there is zero ambiguity, but the metaphors break down. The two universes it splits into aren't as big as the original universe. The thickness of the two new universes adds up to the thickness of the original universe."
"One way to represent the kind of #compositionality we want to do is with this kind of breakdown...eventually a kind of representation of a sentence. On the other hand, vector space models of #meaning or set-theoretical models put into a space have been very successful..."
"Humans are prone to giving machines ambiguous or mistaken instructions, and we want them to do what we mean, not what we say. To solve this problem we must find ways to align AI with human preferences, goals & values."
- @MelMitchell1 at @QuantaMagazine: quantamagazine.org/what-does-it-m…
“All that is needed to assure catastrophe is a highly competent machine combined with humans who have an imperfect ability to specify human preferences completely and correctly.”
"It’s a familiar trope in #ScienceFiction — humanity threatened by out-of-control machines who have misinterpreted human desires. Now a not-insubstantial segment of the #AI research community is concerned about this kind of scenario playing out in real life."
- @MelMitchell1