The social network formerly known as Twitter, now known as X, has been through some things — including a rocky change of ownership 2 years ago. At the time, the person who owns Twitter on paper was known to be tech billionaire and then-world’s richest man Elon Musk — but it was not fully known who was included in the full shadowy list of Twitter investors.
Thanks apparently to some terrible lawyering, the full list of Twitter investors via parent company X Corp has been unsealed during discovery for a legal case against Musk relating to non-payment of severance for employees he laid off after buying the company. In addition to the known in 2022 list below, we can now augment the Twitter investors list with more detail:
Joe Lonsdale — cofounder of Palantir with shadowy tech billionaire Peter Thiel, the primary financial backer of Trump’s VP pick JD Vance
Saudi Prince Alwaleed bin Talal
Jack Dorsey — one of the original founders of Twitter
Larry Ellison
Ross Gerber
Doug Leone
Michael Moritz
Changpeng Zhao
Security analyst and intelligence professional Eric Garland notes that beyond the notable billionaires on the list, the investor sheet can be largely read as “fronts for the dictatorships of Russia, China, Saudi Arabia, and others.” Tech pioneer turned investigative journalist Dave Troy’s take on the Twitter investor list reveal is that it shows “this platform is an instrument of information warfare.”
BREAKING: The full list of investors in X Corp has been unsealed. See them for yourselves. Some investors Include ownership stakes from Saudi Arabia and a slew of VC funds. pic.twitter.com/HIhLYxqBIJ
They were inspired by hippies, but Orwell would fear them. The giants of Silicon Valley started out trying to outsmart The Man, and in the process became him. And so, surveillance capitalism got born. Such is the story of corruption since time immemorial.
This surveillance capitalism dictionary of surveillance is a work in progress! Check back for further updates!
Term
Definition
algorithm
A set of instructions that programmers give to computers to run software and make decisions.
artificial intelligence (AI)
Bayes' Theorem
bioinformatics
A technical and computational subfield of genetics, concerned with the information and data encoded by our genes and genetic codes.
child machine
Alan Turing's concept for developing an "adult brain" by creating a child brain and giving it an education
CHINOOK
checkers program that becomes the first time an AI wins an official world championship in a game of skill, in 1994
click-wrap
collateral behavioral data
common carrier
A sort of hybrid public interest served by corporate promise of meeting a high bar of neutrality -- a historical precedent setby the early Bell system monopoly, and an issue of public-private strife today with the advent of the internet.
contracts of adhesion
cookies
Small packets of data deposited by the vast majority of websites you visit, that store information in the browser as a way to extract intelligence about their users and visitors.
corpus
In Natural Language Processing, a compendium of words used to "train" the AI to understand patterns in new texts.
decision trees
Deep Blue
Chess program that beats world chess champion Garry Kasparov in 1997
deep learning
evolutionary algorithms
Facebook
facial recognition
Flash Crash of 2010
sudden drop of over $1 trillion in the E-Mini S&P 500 futures contract market via runaway feedback loop within a set of algorithmic traders
FLOPS
floating-point operations per second
Free Basics
Facebook's plan, via Internet.org, to provide limited free internet services in rural India (and elsewhere in the developing world).Controversy centers on the “limited” nature of the offering, which gives Facebook the power to select or reject individual websites and resources for inclusion.
genetic algorithms
GOFAI
"Good Old-Fashioned Artificial Intelligence"
HLMI
human-level machine intelligence: defined as being able to carry out most human professions at least as well as a typical human
interoperability
Kolmogorov complexity
language translation
linear regression
machine learning
Markov chains
monopoly
NAFTA
natural language processing (NLP)
A technology for processing and analyzing words
neofeudalism
net neutrality
Legal and regulatory concept maintaining that Internet Service Providers must act as common carriers, allowing businesses and citizens to interoperate with the physical infrastructure of the communications network equally, without being subject to biased or exclusionary activities on the part of the network.
neural networks
netizens
"Online Eraser" law (CA)
patrimonial capitalism
Pegasus
phonemes
predatory lending
predictive analytics
privacy
private eminent domain
probability
prosody
qualia
r > g
Piketty's insight
randomness
random walk
recommender systems
recursion
recursive learning
right to be forgotten
When it became EU law in 2014, this groundbreaking legislation gave citizens the power to demand search engines remove pointers to content about them. It was the growing of a data rights movement in Europe that led later to GDPR.
SciKit
simulation
smart speakers
speech recognition
spyware
statistical modeling
strong vs. weak AI
"weak AI" refers to algorithms designed to master a specific narrow domain of knowledge or problem-solving, vs. achieving a more general intelligence (strong AI)
supermajority
supervised learning
surplus data
TensorFlow
Tianhe-2
The world's fastest supercomputer, developed in China, until it was surpassed in June 2016 by the also Chinese Sunway TaihuLight
Terms of Service
Twitter
unsupervised learning
Watson
IBM AI that defeats the two all-time greatest human Jeopardy! champions in 2010
surveillance won’t be obvious and overt like in Orwell’s classic totalitarian novel 1984 — it’ll be covert and subtle (“more like a spider’s web”)
social networks use persuasion architecture — the same cloying design aesthetic that puts gum at the eye level of children in the grocery aisle
Example:
AI modeling of potential Las Vegas ticket buyers
The machine learning algorithms can classify people into two buckets, “likely to buy tickets to Vegas” and “unlikely to” based on exposure to lots and lots of data patterns. Problem being, it’s a black box and no one — not even the computer scientists — know how it works or what it’s doing exactly.
So the AI may have discovered that bipolar individuals just about to go into mania are more susceptible to buying tickets to Vegas — and that is the segment of the population they are targeting: a vulnerable set of people prone to overspending and gambling addictions. The ethical implications of unleashing this on the world — and routinely using and optimizing it relentlessly — are staggering.
Profiting from extremism
“You’re never hardcore enough for YouTube” — YouTube gives you content recommendations that are increasingly polarized and polarizing, because it turns out that preying on your reptilian brain makes you keep clicking around in the YouTube hamster wheel.
The amorality of AI — “algorithms don’t care if they’re selling shoes, or politics.” Our social, political, and cultural flows are being organized by these persuasion architectures — organized for profit; not for the collective good, not for public interests, not subject to our political will anymore. These powerful surveillance capitalism tools are running mostly unchecked, with little oversight and with few people minding the ethics of the stores of essentially a cadre of Silicon Valley billionaires.
Intent doesn’t matter — good intentions aren’t enough; it’s the structure and business models that matter. Facebook isn’t a half trillion dollar con: its value is in its highly effective persuasion power, which is highly troubling and concerning in a supposedly democratic society. Mark Zuckerberg may even ultimately mean well (…debatable), but it doesn’t excuse the railroading over numerous obviously negative externalities resulting from the unchecked power of Facebook in not only the U.S., but in countries around the world including highly volatile domains.
Extremism benefits demagogues — Oppressive regimes both come to power by and benefit from political extremism; from whipping up citizens into a frenzy, often against each other as much as against perceived external or internal enemies. Our data and attention are now for sale to the highest bidding authoritarians and demagogues around the world — enabling them to use AI against us in election after election and PR campaign after PR campaign. We gave foreign dictators even greater powers to influence and persuade us in ways that benefit them at the expense of our own self-interest.
When usability pioneers have All the Feels about the nature of our creeping technological dystopia, how we got here, and what we might need to do to right the ship, it’s wise to pay attention. Don Norman’s preaching resonated with my choir, and they’ve asked me to sing a summary song of our people in bulleted list format:
What seemed like a virtuous thing at the time — building the internet with an ethos of trust and openness — has led to a travesty via lack of security, because no one took bad actors into account.
Google, Facebook, et al didn’t have the advertising business model in mind a priori, but sort of stumbled into it and got carried away giving advertisers what they wanted — more information about users — without really taking into consideration the boundary violations of appropriating people’s information. (see Shoshana Zuboff’s definitive new book on Surveillance Capitalism for a lot more on this topic)
Tech companies have mined the psychological sciences for techniques that — especially at scale — border on mass manipulation of fundamental human drives to be informed and to belong. Beyond the creepy Orwellian slant of information appropriation and emotional manipulation, the loss of productivity and mental focus from years of constant interruptions takes a toll on society at large.
We sign an interminable series of EULAs, ToS’s and other lengthy legalese-ridden agreements just to access the now basic utilities that enable our lives. Experts refer to these as “contracts of adhesion” or “click-wrap,” as a way of connoting the “obvious lack of meaningful consent.” (Zuboff)
The “bubble effect” — the internet allows one to surround oneself completely with like-minded opinions and avoid ever being exposed to alternative points of view. This has existential implications for being able to inhabit a shared reality, as well as a deleterious effect on public discourse, civility, and the democratic process itself.
The extreme commercialization of almost all of our information sources is problematic, especially in the age of the “Milton Friedman-ification” of the economic world and the skewing of values away from communities and individuals, towards a myopic view of shareholder value and all the attendant perverse incentives that accompany this philosophical business shift over the past 50 years. He notes that the original public-spiritedness of new communication technologies has historically been co-opted by corporate lobbyists via regulatory capture — a subject Tim Wu explores in-depth in his excellent 2011 book, “The Master Switch: The Rise and Fall of Information Empires.“
Is it all bleak, Don?! His answer is clear: “yes, maybe, no.” He demurs on positing a definitive answer to all of these issues, but he doesn’t really mince words about a “hunch” that it may in fact involve burning it all down and starting over again.
Pointing to evolution, Norman notes that we cannot eke radical innovation out of incremental changes — and that when radical change does happen it is often imposed unexpectedly from the outside in the form of catastrophic events. Perhaps if we can’t manage to Marie Kondo our way to a more joyful internet, we’ll have to pray for Armageddon soon…?! 😱
