The following article (sent by K.M. – thank you!) is very very short, but the implications could go on for millennia if one stops and thinks about it. And I’m blogging about it because those implications concern a wild and wacky scenario that I’ve been kicking around in my head for a few years now, and this story gives that scenario a bit more credence. Up until now, the only confirmation of that wild and wacky scenario has been the occasional stock market “flash crash”. If you’ve hung around this website for a long time, you’ll be aware of my thoughts on algorithmic trading and flash crashes: they reflect markets wildly disconnected from actual human market activity. I know that being a traditionalist I’m supposed to love capitalism and private property and all that stuff, but I don’t, at least not the kind of crony finance crapitalism that makes money by trading paper with computer algorithms, and not making things and selling them.
But anyway, I’ve yammered on enough… it’s time to get to the very very short story:
Note the following details:
On Sunday we reported that Zillow Group’s AI-powered house flipping operation was a dismal failure – with 93% of homes in their Phoenix, Arizona portfolio (the company’s second largest) currently listed at less than what the real estate company had paid, as revealed by an Insider investigation.
In Phoenix, 36.5% of properties currently for sale were listed below their purchase price, while the remainder of the 93% started higher, only to have price reductions.
Launched in 2017, Zillow’s iBuying arm uses a wide array of real-estate data with the goal of quickly and efficiently acquiring properties to flip for a profit. The program has vacuumed up properties across the country to flip, only to be met with fierce competition from services such as Redfin, Offerpad and Opendoor. (Underlined emphasis added)
Summing all this up, we have the following:
(1) a real estate company (in this case Zillow), thought it would be a really good idea to gather all sorts of real estate data; and,
(2) have a sophisticated computer program crunch all that data and tell said company’s buyers what houses to buy; and,
(3) make some improvements to said houses and “flip” them, i.e., sell them for a profit over and above the purchase price plus the cost of the improvements.
So colour me suspicious.
Suspicion Number One:
If you’re familiar with former Assistant Secretary of Housing and Urban Development (mortgage division) Catherine Austin Fitts’ story, this will sound very familiar. After leaving HUD, she founded her own company called Hamilton. She put together a software program that could track money flows county by county. The crooks and criminals in fedgoobernment did not like that, contrived to steal the software, and cooked up charges against Fitts, and brought her to trial… and lost, costing her a fortune to litigate, ending her company. But where’s her software? Well, to my ears, Zillow’s effort sounds a bit like what she and her team at Hamilton had invented. If you’re familiar with the Inslaw-PROMIS software story, we all know what happens to software the government wants to steal: it ends up all over the place in dozens of modifications with a trail of possession that it would take a software program (like PROMIS) to trace.
Now I mention Suspicion Number One because it’s only the backdrop to my main point, and Suspicion Number Two:
For some time – as I observed in the opening paragraph of this blog – I’ve been wondering if there isn’t a very simple explanation to all the craziness we’re witnessing in the world. What if our so-called technocratic “experts” were simply doing what computer programs – AI’s? – were telling them to do? What if virtually every policy and/or decision was being gamed out on super-computers and the technocrats were simply the human agents executing those “decisions”? At the beginning of the planscamdemic, for example, we were told all sorts of dire stuff would happen… as the result of “computer models”. We’re constantly preached to about “climate change,” itself a concept coming mostly out of computer models. So what happens when those models are flawed, and moreover, plugged into an artificial intelligence which is capable of modifying its own program as circumstances dictate? I rather suspect that if the original program itself is the product of inherently flawed humans, that a flawed “core” will still remain flawed and as the modifications to its own programming grow, that the effects of the core flaw will only grow, perhaps exponentially. And while we’re at it, let’s plug in Elon Musk’s warning of a few years ago: what if, in inventing artificial intelligence, we open the gateway for some sort of “hyper-dimensional entity” to take over that system, unbeknownst to its human inventors?
The result would be Zillow: chaos, as decisions are not being made any more in a genuinely human way, and a market not reflective of real human market concerns and activities, but a virtual one… divorced from reality.
But in Zillow’s case, they got it wrong. I doubt, however, that the lesson will be learned. The real danger is that the technocrats view even themselves as machines. All it requires is simply the right programming, and we’ll get it right.
See you on the flip side…
Born and raised in Sioux Falls, South Dakota, Joseph P. Farrell has a doctorate in patristics from the University of Oxford, and pursues research in physics, alternative history and science, and “strange stuff”. His book The Giza DeathStar was published in the spring of 2002, and was his first venture into “alternative history and science”. Following a paradigm of researching the relationship between alternative history and science, Farrell has followed with a stunning series of books, each conceived to stand alone, but each also conceived in a pre-arranged sequence.
Connect with Joseph and follow his work at Giza Death Star.