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To my cherished subscribers: apologies for the low number of posts in August – I took a longer break than expected to wrap up a few projects. Coming up over the weekend for your delectation: a dive into the strange politics of the Ethereum Merge.
An investigation this week by ProPublica into “likely the biggest Instagram verification scheme revealed to date”:
Since at least 2021, at least hundreds of people — including jewelers, crypto entrepreneurs, OnlyFans models and reality show TV stars — were clients of a scheme to get improperly verified as musicians on Instagram, according to the investigation’s findings and information from Meta […] The scheme, which likely generated millions in revenue for its operators, illustrates how easily major social, search and music platforms can be exploited to create fake personas with real-world consequences, such as monetizing a verified account.
I think account verification has generated one of the most interesting status and incentive systems of the social media era, and one that major platforms still don’t seem to have any idea of how to deal with.
The original mission of account verification when it was first launched on Twitter in 2009 was pretty simple: if you see a blue check, you know you’re looking at an authentic account. It did not promise any particular status beyond the confirmation you were looking at Justin Timberlake’s real Twitter output, and not that of some scurrilous impostor trading on his celebrity.
That didn’t last long. As a wider class of posters began being verified — including relatively obscure people like writers at digital publications and minor local celebrities — it became thought of more as a marker of status and credibility, like a priestly class for the digital age. Twitter did a lot to solidify that perception, such as by emphasising blue check replies in threads or more aggressively recommending them to new users, making it even more desirable. It developed a number of other signifiers along with it, thanks to the numerical dominance of media and politics personalities among the ranks of the verified. Calling someone a “blue check” on Twitter conjures a particular image — usually some kind of aloof metropolitan elitist occupying a high-status lanyard class profession, utterly divorced from the interests of the unverified masses.
The weird incentives created by this system have wider reverberations. Twitter users might remember the armada of blue ticks who would hold court in Trump’s replies during the presidency, becoming micro-celebrities in their own right from posting variations on “You are a disgrace, sir!” under his posts, and benefiting from the exposure boost. The 2020 Twitter hack — and plenty of smaller ones between — used stolen verified accounts to run crypto scams. I’ve had a blue check on Twitter for about five years, and can probably credit plenty of follower growth and opportunities to the subtle and unearned ways the platform boosts or foregrounds my posts.
The first time the company really acknowledged that a perverse value system had emerged was when it verified white nationalist Jason Kessler not long after the 2017 Unite the Right rally in Charlottesville, which many people read as an endorsement of his views. That led to a pause in the verification system, as pontification from people like Jack Dorsey on whether maybe verification could be opened up to everyone.
Five years later, the system still works like an exclusive status club, with more stringently defined criteria for authenticity and notability. For whatever reason, having approximately half a million accounts operating as a network aristocracy at Twitter’s discretion is a political equilibrium the company is happy to maintain. (Given blue ticks tend to be Twitter power users, I assume they have sway in maintaining the system as is. Just like the Ancien Régime before the French Revolution. Disgusting.)
The same dynamics play out on other social platforms that later adopted Twitter’s tick, like Instagram, Facebook and TikTok. Content from blue tick accounts is highlighted or foregrounded in various ways by the platform, bolstered by social signals that have developed over the years. So it’s obviously inevitable that people are willing to jump through a lot of hoops to acquire verification, even if that means doing it through less than legitimate means. On the mild end there’s an expansive SEO content universe offering tips and tricks on how to maximise your chance of being verified, and then you have the outright scams like those covered in the ProPublica investigation.
I don’t know how you actually fix this problem, but it does seem like a problem worth fixing. The web3 people are experimenting with digital assets and NFTs as new markers of authenticity, with as yet very limited success. Rather than create a decentralised community status system, Twitter’s hexagonal NFT avatars mostly serve as a general signifier that the person in question is ‘into NFTs’ (derogatory). Reddit’s experiments with blockchain avatars are pissing off its own userbase, with a number of large subreddits threatening to ban anyone who comes into their territory using one.
Oh well. I have my tick already, my spot on the Ark is reserved. The rest of you can rot!
The dark arts
A couple of months ago when I was dicking around with various new AI image generation models like DALL·E 2, I said it was likely this sector was going to accelerate at explosive pace, and material and ethical questions about everything from copyright to labour were going to become relevant very quickly.
Well, it’s moving even quicker than I expected. The latest text-to-image model is Stable Diffusion, which was released to the public last week. Unlike DALL·E 2, Stable Diffusion has been released in its entirety, meaning that as well as using it in a browser here, you can also download and run it on your own computer, assuming you have decent graphics card capable of producing good results.
The model also includes a function named ‘img2img’, which uses the same diffusion technique to add or fill in detail to an image. (You can play around with it here.) The subreddit for Stable Diffusion is full of people experimenting with it by using the model to turn crude drawings and prompts into more interesting art. This example from u/argaman123 has been doing the rounds:
Because the model is open-source, people are rapidly building tools and plugins to introduce generative workflows into apps like Photoshop, creating a whole new constellation of uses for neural net art. Developer Andy Baio also released a tool showing “12 million image/caption pairs out of over 2 billion” that Stable Diffusion was trained on, giving a sense of how the sausage was made.
There’s an interesting thread here from someone who did some experimentation with Stable Diffusion, DALL-E 2 and Midjourney to find out which was better at particular tasks or types of images, and what sort of ‘flavour’ each introduce:
Because Stable Diffusion’s public release is open, it’s also possible to remove what little guardrails exist on it. If you attempt to generate something violent or sexual in DALL·E 2 it will rebuff you, whereas Stable Diffusion can’t. This, predictably, has led to an instant, thriving market for strange porn:
This is all being done in defiance of Stability AI’s weekslong warnings to not use its model for anything sexual. As AI-generated hentai nudes started appearing on forums and social media earlier this month, the company wrote in a Twitter announcement (and to the discredit of cool moms everywhere): “Don’t generate anything you'd be ashamed to show your mother.”
The images include everything from hentai, to computer-generated celebrity nudes, to naked images of people who don’t really exist. Some of the results almost look convincing, while other results are horrific, generating impossible bodies with errant limbs and distorted faces.
Okay, one more to get the juices flowing. A guy won a state art fair competition by submitting art generated with Midjourney:
This tweet pointed to me to a fun FOI disclosure of the documents relating to when Australian Classification Board’s decision to ban the 2004 video game Manhunt after waving it through initially. Australia did not have an R18+ classification for games, so anything deemed more extreme thant might be captured by an MA15+ rating was summarily banned. (Agitating for an 18+ rating to be introduced represented the high water mark of political engagement for wide swathes of Australia’s gaming community.)
The enclosed documents are amusing not only for the feeble attempt by the local Take-Two Interactive boss to argue the notoriously sleazy and violent title contained some sort of positive moral value (“While it may not be clear from the initial levels, Manhunt is at heart a traditional tale of good versus evil”) but also the great hand-written notes by the attending censors at the time:
On Gen Z using TikTok as a search engine to find everything from news and culture to recipes and hyperlocal recommendations. I find this particularly interesting, because TikTok’s search and metadata functions are borderline unusable, and built mostly for surfacing highly engaged content. But it’s another datapoint on Google no longer being the first point of call for a huge range of online search activity.
Interesting thread and associated newsletter about the widening divergence between critic and user scores on blockbuster movies. There’s a few theories offered as to why — like critics getting sick of Marvel movies while fans still like them, or targeted campaigns by certain fandoms. I think there’s a generally more hostile anti-critic vibe out there too these days. Like a militant wing of the ‘let people enjoy things’ movement.
Thought this was a good interview with Ethereum co-founder Vitalik Buterin, who is a much smarter and more critical thinker about crypto political structures than most people trying to build them on his platform. The lengthy section on intentional crypto communities is particularly interesting.
Also, the attempts at forming local crypto communities intentionally so far have sucked. The problem I see is basically that they all use some form of "low taxes" as a primary pitch, and while low taxes are a lovely benefit from the point of view of an individual, they are a terrible filter if your goal is to attract people who are actually interesting. The kinds of communities you get when low taxes are the primary reason to come are just really boring and lame.
Things don’t get ‘released' now, they drop, and that includes basically every kind of consumer good or cultural product you can imagine. An Interesting bit on how social media and e-commerce have led to a wider tectonic shift in language.
This history of the TSA in the US is good, and opens with an absolutely insane anecdote.
Interesting piece on the challenges of refrigeration in Africa, and why building reliable ‘cold chains’ on the continent is so tough.
“How the internet turned dadcore staple, ‘fish fear me,’ into viral fashion”.
The prompt here was “A distant futuristic city full of tall buildings inside a huge transparent glass dome, In the middle of a barren desert full of large dunes, Sun rays, Artstation, Dark sky full of stars with a shiny sun, Massive scale, Fog, Highly detailed, Cinematic, Colorful". Obviously that prompt is doing a lot of work here, but the sketch set out the composition.
I’ve been knocked back for Twitter verification a few times, even though I’ve met the criteria for “journalist” for over five years now. It’s all a bit odd and arbitrary!