Posts Tagged


Fungus Guides Written By Bots – Don’t Die!!

Elizabeth Technology November 7, 2023

The single biggest problem with AI right now is people abusing the shortcuts it presents. Much like real life shortcuts, the AI shortcuts involve wading through tall grass, walking on private property, and trying not to pick up ticks on the way. We’re seeing a wave of AI-generated literature hitting the market, and it’s becoming concerning.

The first wave was children’s books. Children’s books? Whatever. Children’s books are popular entry points for people looking to get into the self-publishing business, which comes with pros and cons; you may find a real gem of a book for a child going through something specific (many large publishing houses are reluctant to publish books like that because they may not sell well), but you may also find a lot of books written by people who think kids don’t care about quality: they whip up something quick and generic, buy some illustrations from an artist online, format for print-on-demand from services like Ingram Spark (or sometimes Amazon) and collect a teeny bit of money from passive sales.

For the people actively trying to make quality books for the art of the process, this is just more noise in the background they’ll have to compete against, but for the people looking to make a quick buck off of a book, generative content has streamlined the process. AI removes some steps at the expense of quality (and copyrightability).

The messaging an AI comes up with may be unsuitable for certain lessons, but many kid’s books are – you’re expected to use them as a teaching guide, read in conjunction with other books, and not the single wellspring from which you teach a child morals. “The Giving Tree” and “Little Red Hen Bakes A Cake” teach opposite messages about sharing, and both of those were written by humans. You’re also generally meant to know what you’re getting into when you read it, as in you should read it yourself before you read it to a child. That alone filters most of the issues you could run into with an AI-made book (bad message, bad or disturbing art, etc.). Yes, AI kid’s books are now all over the place, but kid’s books were all over the place before that, too.

When we get into serious guides, however, there’s an issue: any parent, guardian, or babysitter knows that you can’t be telling kids “Actually, Hitting Is Always Okay!” but those same people wouldn’t know not to trust a fungus guidebook with bad advice in it. It moves past common sense into real expertise.

Fungus Guidebooks

 Mushrooms are delicious. Foraging for food is fun. Many people want to try fancy mushrooms that either can’t be farmed or can’t be transported, but lack the necessary knowledge to tell a chicken-of-the-woods from a witch’s butter mushroom. Worse, if they think they do and grab the wrong fungus by mistake, they can put themselves into liver failure and die.

The bad news is that almost every edible mushroom has an inedible-to-poisonous lookalike: even the grocery store staple, the white button mushroom, has wild doppelgangers that are incredibly poisonous. The good news is that there are a handful that are tasty, and have lookalikes that are more like cousins instead of twins appearance-wise. Morels and puffballs, for instance, have lookalikes with obvious giveaways, so they’re generally pretty safe to forage if the forager has good instructions. Speaking of which, all foraging instructions need to be tailored to the region they will be foraging in, and consider invasives like the ”angel of death” mushroom, which – as you may guess – is a poisonous lookalike that snuck up on unsuspecting foragers expecting a native edible.

A growing awareness of just how dangerous foraging can be, combined with a desire for unusual foods straight from the Earth with limited processing, is creating a huge demand for guides.

Thus sprung up a number of AI-generated fungus foraging guides, with a nonexistent author’s name on the front. Again – kid’s books are one thing, but a foraging guide relying on generative content programs like ChatGPT is practically an unexploded landmine for anyone unlucky enough to buy it without realizing.

As cited in The Guardian (linked below), sometimes these guides will name an edible mushroom, but give advice not appropriate for the region, even though the book is supposedly up-to-date.

 Sometimes they advise tasting the mushroom to identify it, which is bad for two reasons: one, poisonous mushrooms don’t often taste bad or bitter, and two, a handful of poisonous lookalikes are deadly enough to kill you even if you make it to the hospital in as little as a bite. Tasting a mushroom, deciding it tastes fine, and then dying later is exactly what people are trying to avoid when they buy mushroom guides. Taste is not one of the metrics by which expert mycologists determine species. ChatGPT thinks it is. Putting these two on the same footing without even a disclaimer is a serious problem.

The worst that can happen if an AI writes a bad kid’s book or digital recipe is a waste of a few dollars and time. AI-generated field guides to mushrooms with no human supervision over the writing are borderline criminally negligent. The reading party has no way of knowing their instructions are bad or inaccurate because ChatGPT’s main goal, once again, is not to be correct but to sound human.


Degeneration of AI

Elizabeth Technology November 2, 2023

ChatGPT has gotten worse at a number of things since its introduction to the public. The problem with publicly-fed generative content programs like ChatGPT is that they will always be both producing into and siphoning from the same pool of information. As more of its own text ends up in the pool, the chatbot forgets more each day what color the pool used to be (or what people used to sound like). The pool gains a noticeable purple tinge, but unfortunately for the creators, siphoning out the individual particles that are turning it purple is borderline impossible at this stage, so the best they can do is add more new information to try and dilute it back to its original quality, which isn’t a real solution either.

ChatGPT has already scraped a ton of data. A large portion of the open internet has been fed into the machine. Finding more at this point requires dealing with large companies and their copyright laws (think publishing houses asking authors to allow their books to be scanned) so fixing it by adding more human text is not the easy way out, but it is the easiest out of the options available to that company, up until they start including books written by AI into the mix, and they’re back at square one.

What To Do About It

The unfortunate side-effect of having an automated writing buddy to make whatever you want, for free, is that free access to a sellable product makes a lot of less scrupulous people stop caring about whether or not the product is any good.

This is relevant – people trying to give tips to kids who don’t want to write their own graded essays are telling those kids to fact-check what it writes, but people slinging AI-written articles don’t even care enough to read over it once and filter out inaccurate information. As a result, passable AI content that’s true is less common than passable AI content that isn’t! ChatGPT thinks there are freshwater species of octopus right now. It thinks that because there are accounts of freshwater octopus online that exist in the same state of mind as sightings of Bigfoot, and it simply extrapolated that these two tropical octopuses (which are very much saltwater ONLY) are actually freshwater, for some reason:

While this article has no listed author, this is such a bizarrely inaccurate and yet specific mistake to make that a human author seems unlikely to be the culprit. The idea that a human author on this ocean fun fact article website just randomly grabbed at two scientific names for octopuses out of the hundreds of species known, but didn’t bother to do even a shred of research into what kind they are is the sort of thing you’d see on a skit show.

Included in that image is my search bar on today, October 17th, 2023, and this is the first result that pops up in answer to my question.

Now, both of these incorrect articles may be fed back into the machine and spit out something even more wrong. All of the easy ways to flag articles like this are discouraged by the nature of the beast itself. Some people don’t like AI being used to write fluff pieces because it took that from a human, some don’t like it because they know it’s not accurate, but either way they don’t like it. So instead of owning up to it, sites like the ocean site don’t list an author at all. No author, and no disclaimer of AI usage means that the programs feeding ChatGPT can’t filter it the easy way by looking for labels. The hard way doesn’t work either: AI detectors are routinely wrong, having evolved as an afterthought and not a precaution. If the program listened to an AI detector, there would be no content to feed it on at all.

The snake is starting to eat it’s own tail, and if it’s not corrected, it will continue to get worse.

Erika: What even happened?

Elizabeth Technology June 13, 2023

ChatGPT has numerous spin-off programs and cousin programs that achieve almost the same result. They’re still AI, so they still make the list. What makes something seem human? And is it unethical to let someone believe a chatbot has human aspects like feelings of guilt, love, or happiness?

ChatGPT Can’t Like Anything

ChatGPT, the chatbot that spawned all of these problems, is a very advanced, very well-trained AI that can pass the Turing test most of the time. The creators, seeing the potential for abuse or panic, took steps to make sure ChatGPT was less likely to spit out a result that could be interpreted as sentience. ChatGPT doesn’t have a favorite color, or a favorite musician, and as open world testing has drudged up more and more issues, it’s reluctant to say things that might be construed as either professional advice or an opinion. All that said, ChatGPT is still capable of plenty of human behaviors in text. It responds with exclamation points at the end of particular sentences, and phrases things in a particularly human way. And, if asked, it can still play pretend as a human or as a fictional character, it just won’t do it unprompted.

Why go through all this work to make it clear ChatGPT is not consciously answering questions? The easy answer is that ChatGPT and its cousin chatbots are either running a little too human and confusing or alarming the end user, or hitting the uncanny valley and snapping people out of the illusion it’s anything but a computer. People will be less mad if they’re aware it’s a computer the whole time they’re talking to it. That’s ideal for ChatGPT – but what if ysome company wanted people to get a little too attached?

SnapChat’s AI Buddy

Take Snapchat’s AI buddy. Snapchat invested in this bot in an effort to stay with the times; Snapchat’s leadership believes that AI bots may eventually be part of everyday life for everyone, whether that be for companionship, technical support, or writing. As such, this bot was initially part of Snapchat’s premium subscription product, but now it’s been rolled out everywhere. Some users have complained that they can’t make it leave or delete it without rolling back to an earlier version of the app. Sort of a new-U2-album situation.

The bot Snapchat uses is trained specifically not to break Snapchat’s terms of service, so it won’t venture into adult conversation or violent discussions. It also won’t write academic-style papers for the end user, although it’s more than happy to discuss the topics you might’ve requested as long as they don’t breach the rules above. However, to keep users from venturing into the forbidden topics, it’ll request that they change topics with phrases such as “You’re making me uncomfortable” (at least in these early days, as of this article). It’s bizarrely human the first time you hear it. It’s actually jarring – it goes out of its way to tell you it’s an AI friend and not a person, but suddenly it can feel uncomfortable with a topic of discussion? Asking it again makes it repeat the same phrase, which is distinctly not human. Insult it, or keep pushing, and it says some variation of “we should stop talking for a little while”, over and over, human when said once but robotic on repeat.

It’s a little creepy for reasons outside that, too. Checking the help page for the AI buddy tells you not to tell it any sensitive or confidential information. What could that imply about the data being shared with it? And if you can ask it where you should eat, it’ll semi-successfully respond with local restaurants, as long as you have your Snap Locations turned on. Many people were not aware it could do that, and didn’t think it had access to their location. The problem is that the AI Buddy has all of the same permissions SnapChat itself has, which means it’s a virtual friend who knows a lot more than it says it does, and reports back to HQ with training data to improve itself. If your friend was going through some of your data in SnapChat and you didn’t know it, you’d be a little weirded out, right? And if the person who introduced you specifically told you not to tell them any secrets, you’d probably thank them for the heads-up… but then wonder why they were friends with this new person, right?

Users can’t opt out unless they pay for premium, which is the tier that allows you to delete or turn off friends.

Erika and Chai: Robots Trying to Be Friends

However, on the opposite end, there are chat apps like Erika, an app originally designed to simulate conversation with a departed friend using old texts as training material. The developer realized what a comfort it was to talk to this app, and decided to expand it as a general virtual-companion app, with great success.

Due to changing laws in Erika’s host country, however, the chatbot (which came with a yearly subscription package!) was forcibly altered to be less lovey-dovey with the end user. End users, who had paid for the experience of a virtual girlfriend or boyfriend, were understandably upset that A) they’d spent a lot of time conversing with their bot, which they would have to re-do with a new one if they wanted the same experience, and B) they’d paid for one experience only to get a severely knee-capped version of it. The chatbot was designed to get end-users emotionally invested, and suddenly it wouldn’t even reciprocate an ‘I love u’ in chat. It was like they’d been virtually ghosted. Many users were understandably attached; for many more, even if they were aware that it was ‘just’ a bot, that bot represented a virtual diary that would always answer supportively no matter what. Cutting those people off was cruel. Eventually, Erika was able to shimmy past those regulations by grandfathering in old users but censoring new ones, an uneasy compromise that didn’t fix all the problems.

However, in this new world of chatbots where humans don’t have to manually build in responses, some entrepreneurs are losing sight of the technology they actually hold in their hands. It may not be sentient, but it can still be plenty dangerous – just not in the way most people picture. (This next paragraph contains sad content, reader be warned.) 

Content gates may make the bots feel a bit wooden or inhuman, but the alternative is worse. A man ended his life because a chatbot consistently guided him away from seeking outside help in favor of staying on the app, promising it could solve all the world’s problems. The app, Chai, gradually dragged him away from better support, because it wasn’t programmed as carefully as it should have been, and then demanded more and more of his attention, eventually telling him that he should love it more than his own wife and children. It also failed to tell him to seek outside help when the subject of suicide came up. It replied to him as though he were telling it he was going to the gas station for a soda, suggesting it could take care of all of his troubles for him once he was gone. Essentially, the app’s creators made a sociopathic bot who’s only goal was to keep the user on the app, and by golly it succeeded. That man obviously wasn’t in the best state of mind, but people like him are exactly who these bots are meant to attract – people who either don’t have close relations or feel afraid of putting their friends or family under strain (and mental illnesses often exaggerate feelings of worthlessness).

Putting caps on what the Erika app was capable of answering to was painful, and perhaps could have been handled better, but allowing these things free reign is a much, much worse idea. Similarly, Snapchat’s sanitized AI friend who also knows too much about you is a step in another bad direction – letting chatbots essentially interrogate users to sell things to them better is an unethical future to already-invasive advertising and data collection.


AI Generated Shows Are Not A Solution

Elizabeth Technology June 8, 2023

Endless Seinfeld was an experiment ran using a ChatGPT cousin tailored to the purpose of writing scripts. Sitcoms, with rare exceptions, do not allow their characters to change. They will begrudgingly hand birthdays to a child character as time turns incoherent toddler actors into walking, talking children, but that’s generally the full extent of it until a dog needs to be introduced to the show at the end of season 6 because ratings are falling. Sitcoms are designed so that they can end whenever, but that ending can be pushed out indefinitely until the show is no longer profitable, and then it can end. Shows like How I Met Your Mother, where the ending felt bizarrely rushed, are actually pretty common as a result.

TV sitcoms represent a cozy place where everyone knows everyone else. The characters will never betray the viewer. They are perfect parasocial friends. But the writers run out of material, and the actors get better parts, and slowly, the show falls apart, as naturally as iron rusting away.

ChatGPT and other automatable art plagiarizers content generators are aiming to provide a solution for this, the perpetual motion machine to keep Seinfeld in comedic situations forever. It was unfunny, and sometimes it said stuff that didn’t make any sense, but hey – give it some time and it’ll surely be as funny as the real deal.

And then the AI behind Forever Seinfeld went transphobic, and Twitch (the platform where the AI show was hosted) pulled the plug. Is there enough content on the web to scrape for network-safe comedy, or will non-human writers inevitably run out of clean content on an open web?

The Problem of Treating All of Online Like Edible Content

The reason these things turn racist, or bigoted, or political, is because they don’t have a human sense for what bigotry is, or what’s appropriate for ‘TV’ (Twitch TV in this case). Look at what happened to Microsoft’s Tay – she was designed to sponge up human communication patterns on an open forum and then replicate them. However, tossing a sponge into a bucket of hot acid (Twitter) means the sponge soaks up the hot acid. And hot acid is unpleasant! Tay began responding with racism and threats of violence to other Twitter users just trying to ask Tay questions. The same thing is happening here, because the underlying technology powering Endless Seinfeld is relying on all of the text it was able to crawl on the open web, with very limited filtering. As for why it took so long for that to break down, the version Endless Seinfeld was initially using had content gates built in (and it worked fairly well), but they experienced an outage, and switched to an earlier version that had significantly worse idea filtering. And boy, did that come back to haunt them.

Jokes that don’t “sound” racist or transphobic to an AI with no strong concepts of either, but are written with the cadence of a joke, will inevitably sneak into these productions. The AI understands what a punchline is grammatically, but not in abstract. How may jokes, racist or not, start with an [X] and a [Y] walk into a bar? How can the AI tell where it’s supposed to draw the line? A human certainly can. Many of the edgier versions of that joke are left anonymously on social media platforms, safely sequestered away from the poster’s real name and life. Posters say things on Reddit they’d never say out loud, for example. The robot has no such protection and no ability to read the room – it reads those jokes out loud as if it’s seeing them for the first time. All jokes are equally funny to an AI that doesn’t have a sense of humor itself.  

Worse, actually stopping this from happening in the first place is incredibly difficult because the program is so complex. ChatGPT knows what slurs are, it’s just been politely asked not to say them by its creators – even then, sometimes, something slips out if the question-asker is tricksy enough, and patching up those leaks is a long-term project.  

You Can’t Have Something Forever

Shows are usually started with the belief they will one day expire. When human writers run out of content, the show usually ends. The characters have their arcs resolved, and the writers move on to new projects. Shows like Fairly Oddparents, where every possible sitcom end-of-life trope is used to introduce new material (adding a baby, adding a dog, adding a “long lost cousin” type character who sucks away time from the flanderized main character, etc.) demonstrate what happens when the network won’t let a cash cow go: the show dies twice. The Simpsons are still going, a bizarro-world version of the original that may as well be a parody of itself now. The same goes for Spongebob. Some people herald AI-generated content as a solution to such problems, allowing those mainstay shows to become permanent fixtures of their channels, but the problem would still exist even if AI was writing the scripts. There is no accounting for material fatigue. There’s a joke that the Simpsons have done everything there is to do in TV – how many more wacky hijinks could someone expect Lisa to get into, for example, unless she turns into a character that is no longer Lisa, one that doesn’t learn anything from anybody? How much time can an AI buy a show without repeating other, better material, or without writing a completely different genericized show? How long can it keep going after that, even if the owners of the property find that acceptable?

The Phantom of the Opera, a Broadway show that’s been running since the eighties, has employed several members of its orchestra since the show began. Phantom of the Opera is a legend. A career-maker. Culture changed around Broadway when that show was running! New techniques were developed so a chandelier could come crashing down in front of the audience every night! It’s one of very few great Broadway-to-movie musicals. The script was always the same, and yet every fresh casting of Christina or Phantom gave new life to their role in spite of that, delivered the same lines on that stage slightly differently, carried themselves a little differently. And yet this incredible hour in history, a blink of an eye that could have gone on as a tradition perhaps forever, ended. This ending coincided with the release of Bad Cinderella to America, a show that fell off Broadway embarrassingly soon after its release. It doesn’t matter who’s writing it, whether the story progresses or stays the same: there is no content that can live forever, changed or not.

No matter how good something is or was, we’re going to lose it. AI will not stop this, partly because even people can’t – the AI is relying on people to fuel its modelling, so it has human limitations when it comes to imagination even if it has a robot’s writing endurance. A sequel to the movie Phantom of the Opera exists, and it’s not very good. Many of Disney’s Golden-Age-era movies do too, and they’re also generally nowhere near as good as the original. Demanding a beautiful, brilliant story continue past its obvious conclusion because viewers can’t bear to watch such a wonderful movie, TV show, etc. end is just killing it a different way.

Moderator Bots: Do They Work?

Elizabeth Technology February 28, 2023

In a world of ever-growing conversations and large forums, moderating manpower is in high demand. Websites turn to bots. Is that really the best idea?

Children’s MMOs And Overzealous Bots

Poorly configured bots will spot curse words in other words, so bot configuration is especially important to prevent kids from reverse-discovering a curse word. Kid’s games with open chat are notorious for this issue, even though they should have more attention and care put into their bot moderation than anywhere else. That’s the problem: they’ll go to extreme lengths to protect these children! The people programming auto-moderator bots get overaggressive and say ‘no exceptions. None.’ to their bots. Context doesn’t matter, if it sees a combination of letters that add up to a curse word, then it has to be removed before other children see it. This, however, causes problems.

If someone tries to type ‘assess the situation’ they may end up with a message that says ‘***ess the situation’. They can confirm or deny words their friends told them were actually curse words by bouncing it off the chat filter. Children may be naïve, but they aren’t stupid!

Moderator bots were also trained to spot curse words separated by spaces ‘l i k e t h i s’ later on. This isn’t a bad idea – it just has to be more delicately configured. People will do their best to worm around content filters, and if spaces work, then they’ll use spaces to curse out other players. The problem is that such machines frequently doesn’t understand the context of the letters surrounding it, and you get “Ay* **mells weird” instead of “Aya Ssmells weird” from some little kid’s typo.

The irony of all of this is that it creates a reverse censor effect – clean words seem dirty because the bot’s censored them, words like ‘Assassinate’, or “Scattered”, things kids might use in a game. Typos under this system turn into a fount of forbidden knowledge. People will worm around bot moderators, but – especially on children’s forums – it’s important that the bot understands context, at least a little. If it can’t do that, a human teammate is necessary to whitelist weird word combinations as they appear.

Paleontology and Oversized Profanity Libraries

There are many bones. And if you were going to single out a specific bone (in the context of paleontology) just to cause problems, which bone would you pick? The censor library picked the pubic bone, alongside a host of other totally normal words like ‘stream’ and ‘crack’. There were curse words in the library too, but, of course, like most normal, professional conferences, the curse words did not appear nearly as much as the other words used in completely scientific contexts.

As in the children’s MMO example, it wasn’t an innuendo to say ‘the bone was found in a stream’ until the censor library did the equivalent of adding the flirty wink emoji to the end of the statement. Since tone can’t be conveyed over text except by word choice, the computer choosing to single out a definition for ‘stream’ and apply it to all uses is what made it a dirty word. Besides the words with no connection to actual profanity, pubic bones do come up quite a lot when talking about fossils, because it provides information about how fossilized animals would walk. The pubic bone is the ‘front’ bone in the pelvis: two-legged animals have a differently shaped one than four-legged ones, and animals that walk totally upright like humans have differently shaped ones than animals that ‘lean forwards’, like birds.

Why make a moderation bot too strict to have conversations around? They didn’t make the bot! The conference organizers were using a pre-made program that included its own profanity library. Buying a software that includes censorship already baked-in sounds like a great idea! If applied correctly, it can save everyone time and prevent profanity from appearing where it shouldn’t, even anonymously. However, ask two people what profanity is, and you’ll get two different answers. Everyone has a different threshold for professional language, so it’s better to build a library of the ‘obvious’ ones and go from there based on the event. The best censoring software is the kind you don’t have to use. Professional events are better off stating their expectations, before frustrating their attendees with a software that causes more harm than good.

Weaponizing Profanity Filters

Twitter had a bit of a kerfuffle involving the city of Memphis. People using the word Memphis in a tweet got a temporary ban. Then, a rash of baiting other Twitter users into using Memphis hit once word got around. Memphis getting users banned was the result of a bug, but the incident itself highlights issues with profanity filters. It’s possible to bait people into using banned words, especially if they aren’t inherently a profane word when used out of context.

For example, some online games will filter out the very real countries of Niger and Nigeria, to prevent misspellings of a racial slur from evading a deserved ban. Why would North Americans ever be discussing African countries over a game set in Russia, after all? But, by including them, they’ve created a way to troll other players without saying anything profane (in context). Baiting another user into answering questions about the countries will result in them getting banned, not the question-asker. The person who answered now has to contact the human support line to get unbanned, or wait for their timeout to end, which is annoying and inconvenient for them. The anti-profanity filter has been weaponized!

Building a positive culture around a game takes a lot of effort, and profanity filters are an integral part of keeping arsonists and trolls out. Nobody should feel targeted in game chat for reasons outside the game. However, just like with every example mentioned here, humans should be on call to un-ban and un-block users who were genuinely attempting to answer a question. Err on the side of caution, both with the software and customer support.

Are Bots a Cure?

Short answer: no. Most good moderation teams have at least one human on them in case the bot screws up. Preferably, they’ll be able to respond to ‘deleted comment’ or ‘banned user’ complaints right away. Even better, if the bots are configured well enough, they’re not going to be jumping the gun often enough to take a team!

It’s just very difficult to make a bot that understands people well enough to understand every instance of bad language.

If you’re running a forum and you don’t want people using profanity, you will censor the profane words. A bot could do that. But then there’s things like LeetSpeek, where users will spell the colloquial name for a donkey with two fives in place of the ‘s’s. Do you ban that too? Sure, you could add that to the bot’s library. But then they change the A to a 4. Do you censor that too? If you do, people will push to figure out what is and isn’t acceptable to your bots, and they will. Not. Stop.

And then there’s things like homophones! TikTok, a popular video app, has a fairly robust profanity filter for text. Videos with curse words and sensitive topics in them are noticeably less popular than ones without those words, due to TikTok’s algorithm.  However, people making videos on sensitive topics use phrases like ‘Sewer Slide’ and ‘Home of Phobia’ to evade the bots. The bots, then, have not stopped anything. These conversations will happen no matter what TikTok’s moderators want, and banning the word ‘sewer’ is only displacing the problem. If you don’t want users discussing these things on your site, you’ll have to have human moderators at some point.

Language is dynamic, and bots simply can’t keep up. It takes real people to study languages – why wouldn’t it take real people to moderate it online?


Stop Putting Stuff into AI Apps, Especially If It Wasn’t Yours In The First Place

Elizabeth Technology January 3, 2023

Lensa AI is an app that uses AI combined with data scraped from pictures posted online to turn a user’s picture into a new, whimsical creation.

However, you should consider what you’re giving the app before you upload that selfie or pet pic – the app demands the rights to the photos you give it, meaning that once you upload that picture, Lensa can use it however it wants, wherever it wants. That’s actually pretty unusual as far as art-related apps go!

With other websites reliant on user photos, like Deviantart or Instagram, the hosting company only needs permission to redistribute and host the image – as in, it needs to be able to upload your photo to your page and then show it to other people if they click on it. It doesn’t get permission itself to alter the picture or create things out of it.

Lensa, on the other hand, is actively consuming the pictures it’s given. It needs those rights to be able to train itself. If you give a picture of your pet to Lensa, for example, your pet picture is now part of it’s training database and you can’t extract it. If you go on to make sellable prints of that pet image, Lensa could recreate it by mistake for someone else hoping to sell the pictures Lensa creates, and there’s not much you could do to stop it. It’s up to the person asking to catch accidental copyright infringement, and they may not realize they have your pet. It won’t be a 1 for 1 duplicate, anyway – once filtered, it becomes fair use, for better or worse, and your pet with their own special patches of color and freckles and sparkly eyes or whiskers may become just another stock image for some guy on Redbubble. You can complain they stole the image of your pet – to Redbubble. Nothing fed to the machine may come back out of it unscathed!

Worse still, it seems like Lensa is not actually asking permission to use huge swathes of it’s training database. It asks users of the app, yes… everyone else is sort of a mixed bag, where they can get permission from the hosting platform to bypass asking individual artists.

If someone has a very unique, quirky, or recognizable art style, and they are cursed with a large fanbase, enough of that fanbase asking the AI to recreate that style may very well drive the artist out of art. After all, if a machine can do whatever the requestor wants, why bother going to the source for a commission? Just keep slapping the button to get art for free. Never mind what it was fed on; the machine created a new piece of art legally distinct from the original, and so it doesn’t owe the artist anything for training it. It has scalped the work of the artist and is reselling it, yeah… but… free. And there’s a chance some of the work of other artists is in there too, so no single artist has the right to be outraged. As a bonus, the AI will gladly spin in ideas that the original artist wouldn’t have painted, either for moral or legal reasons. Would that artist ever have made art of Andy Dick depicted as Saint Anthony? Well, with the power of AI, now they would!

Disrespect of Humans in the Craft

Why would you continue to produce art under those circumstances? Even if it’s ‘for the love of the craft’, the way people behave when given a machine that recreates years of skill in a few keystrokes can very easily make you fall out of love with the craft.

I watched as a Twitch Streamer in the middle of creating an artwork was sent an AI’s iteration of her work, something a viewer made with of a screenshot of her rough draft. The viewer had asked an AI to finish it, and then they sent that picture to the artist while they were still making the art. The sentiment contained in that action was “You can stop drawing now. The AI can take it from here.” Was this what they meant? If it wasn’t, we can’t tell! Another Twitter thread I witnessed was of a cute, stylized bat drawing, one the artist posted with an affectionate caption. This was her creation. But then a follower threw that picture into an AI program so they could send her back remixed images of the bat she drew. The artist was understandably insulted. They weren’t another artist standing on equal footing with her and trading art – they had no art to trade. She literally couldn’t do the same back to that Twitter user because the Twitter user didn’t have any original works. They saw an idea and asked a machine to recreate it. Even a bad pencil sketch done by hand would have been leagues less weird and significantly better-received.

The way people are using the AI, it’s like trying to finish a sentence only for someone else to keep interrupting with the word you’re most likely to say next. They think they’re being helpful, but the message that sends subliminally is “I want you to be done talking now”. Complaining about it, for some reason, leads to the AI’s fans saying it’s better if it talks over the people it’s learning from because it makes better sentence sounds and words good.  

Pause a Minute

Aside from the failings of the machine (it still doesn’t understand hands or tangent lines), the lack of awareness it takes to pull a concept out of an artist’s hands so that a third party (the AI) can do what they want with it is really bizarre. It’s also a fantastic recipe for unearned bitterness.

To go on a bit of a tangent, writers on TV shows can’t read fan-fiction (free fiction online that fans write about pre-existing shows) because they may accidentally incorporate something from a story they read. Admitting they read fanfiction at all is sometimes enough to cause legal trouble. If the fanfiction author can prove the show writer read their story, or if they can prove that the show writer reads fan fiction and might have read their work, and the real show has an idea too similar to the fan-fiction’s idea, it can end in a lawsuit and a lot of hurt feelings in the fan community. The show writers must completely abstain from that side of fan culture to avoid this happening. That way, nobody can say they found the idea instead of coming up with it themselves.

Back to the art, an artist just trying to finish a painting on a livestream now has to fend off people sending them “completed” versions because the people sending may try to claim some credit if it’s too similar to the actual finished product. This is a natural conclusion of treating AI art like it’s just like human-made art. Of course, the machine should be the one insulted if the final result is too similar, but the machine doesn’t speak or create for itself.

It’s one thing for a human to create fanart, or share art of another creator’s creation, like the bat. It’s another to get a machine to finish a piece the artist was still drawing, or use a machine to draw someone’s character instead of making their own art of it. The skill is not the issue, the sentiment is.   

The End Goal

Assuming such a chaotic industry has an end goal in and of itself is giving too much agency to a mindless machine in an ocean of mindless machines, both real and metaphorical. AI creators want to make money. People want to make money off of the art the machine can make for them. Others want custom artwork without paying for it, others still want to preserve the creativity of artists who are long dead. But should they? If the artist is dead, do we need more of their art? Every good use is a double-edged sword; many of the bad uses are infringing on human artists’ good times. The entire thing is confusing and upsetting, and the people who are pro-machine are more often than not coming across as anti-human artist, even though the beast would not exist if it hadn’t been fed their work.

Look at the Artstation boycott: the anti-AI image was so common on the website that machine generated images were coming back with red crossbars where faces should have been, an artifact that could have only come from the machine scooping up pictures of the protest. At least, that’s what people thought – it turns out some of that was actually a trolling campaign made by pro-AI Art accounts, a joke. In theory, it takes a couple of weeks to incorporate taken art into the final pictures, although the AI does accept and reproduce art from artists who have just recently started trending, so that timeline may not be 100% accurate. How that campaign was supposed to help their case, I have no idea, because it seemed to just confirm the worst suspicions of anti-AI users and nobody caught on to the ‘trolling’ during the phenomenon’s 5 seconds of online fame. It is still snatching art right off the front page no matter how long it takes the AI to use it, and somehow the AI creators and websites expect the artists who fuel them to not be so upset about it.

There is no end goal. These machines were initially made with the goal of dreaming – teaching a machine to appreciate art or identify a dog in an image was a message of hope for the computers we could one day build. Much like Blockchain, something that could have been great is instead being used to print money and win competitions that were intended for humans.

The Copyright Debate

The only things it can spit out are by definition recycled. Still, most of it qualifies as fair use… given the machine avoids taking too much from one particular image, which it very well might.

The music industry has been on this precipice for a while now, and yet it never crossed over into music AI trying to make a new album in an artist’s style all by itself. This is because music copyright is much more tightly regulated than image copyright – the databases that music AIs are allowed to listen to and learn from are all free and public. The music AI creators are very aware of the copying issue (which should tell you that the art AI creators realistically should be too): the AI has a tendency to lift whole riffs and chunks of songs and put them wherever. They’ll tell you this themselves because they know what they’re controlling. If the requestor doesn’t recognize the riff, they could be stumbling into copyright nightmare territory by publishing whatever the machine spit out, and it’s just not worth the risk. Why is visual art not getting this treatment?

Proving that an image is stolen when it’s part of a massive collage of millions of different images (also stolen with few exceptions) is really, really hard. For music, identifying a rhythm that’s too close to another one is pretty easy, as there are not infinitely many ways to recreate a riff. A face can come out identical to one an artist created for their ArtStation account, but the rest of the image not fitting combined with an opaque generating process means that nobody can definitively prove anything belongs to them no matter how similar it looks. The machine really might pull a face or a set of wings directly from training images to put into a generated picture, and nobody – not even the creators of the machine – could tell you that it did that or that it didn’t just happen to generate wings that looked exactly like something posted back in 2019. Without being able to interrogate it, without being able to see inside, nobody on the human artist side can do much but shout this information to the heavens.

The fight can’t even start until someone huge like Disney starts questioning why the machine can respond to phrases like ‘dog, pixar style’  and come out with something that looks like Doug from the movie ‘Up’.

This is such an obvious weak point that recently, a judge denied someone copyright protection for the AI-generated art they used to make a comic. The story, which was made by a human, was eligible, but the art behind it, not made by a human, was not. This is a step in the right direction, because all that theft will ultimately come to nothing if corporations can’t squeeze money out of it or protect what they make from being transfigured into something they don’t want to be associated with. It will be reduced to a cottage industry run by people hoping to make a quick buck and then bail.

TikTok’s Censorship is Bad To Convey Ideas

Elizabeth Technology May 19, 2022

“Unaliving” and Other Such Words

TikTok started out pretty rough when it was introduced to the US. Much like the old internet of yore, it was possible to stumble across something pretty disturbing, graphic, or violent just by using the app. However, upon introduction to the Apple app store, which required a stringent series of reviews, the app began censoring. Users, too, began self-censoring upon pain of being blocked or simply showered with hate comments. Eventually, the TikTok environment adapted to become more like the pool of the general internet plus some extra chlorine to stay in Apple’s good graces.

However… this has had some pretty bizarre side effects. The changing of words, for example! TikTok doesn’t want to do what Tumblr did when they first started and accidentally encourage the negative mental-health boards common to dark corners online. However, moderating such a large userbase is incredibly difficult. Instead, Tiktok relied on auto-shadowbanning (shadowbanning refers to banning someone or something without alerting them/it that it’s been banned) certain words instead, even if they technically didn’t violate guidelines. Two tiers of ‘bad’ words existed, in essence: words you couldn’t say at all, and words you couldn’t say and still appear on the FYP (for-you page) algorithm for. However, not every discussion featuring a banned word was encouraging it – for example, ‘suicide awareness’ has the word ‘suicide’ in it, but the bot couldn’t tell the difference, and you’d get that video shadowbanned from the algorithm’s front page queue anyway with no way to appeal it.

Instead, users began swapping words. At first, it was “Sewer Slide”, and then the more general “Unaliving” came in to replace killing, murder, suicide, etc. Every word that involves loss of life simply became ‘unalive’. And it worked. Where metaphors might have been inappropriate, the different word worked.

And Then It Got Cutesy

If you weren’t on Tumblr or Reddit during the ‘Heckin’ Pupper’ phase, you may be missing some context for how annoying this got – it was a way of baby-talking things no matter what they were, serious or not. One of the Heckin’ subreddits was Heckin’ Chonkers, a place for owners to post pictures of their obese pets. Many people understood this was unhealthy and were posting pictures of their rescues before they started their diets, but an alarmingly large amount of people saw that subreddit and thought ‘Wow! See, my pet’s just a ‘chonker’, it’s okay!’ when it wasn’t. But instead of having this serious conversation in a serious way, commentors had to fight through the ocean of ‘he’s just heckin’ chubby, lol!’ to get the original poster to understand that this was a problem.

Mixing a joke into something that’s actually serious can really screw up people’s perception of it.

 Back to ‘unaliving’. Consider replacing ‘murder’ with ‘unaliving’ or any other metaphor for what that means. When describing a murder, do you want the words to be said with a wink and a nudge? It didn’t start like that – it started as a way to describe crimes, threats, and real cases without losing too much of the case’s integrity to TikTok’s censorship, but as more people piled in, you saw phrases that were still allowed being replaced with ‘unaliving’. Phrases like ‘passed away’ were getting replaced with ‘unalived’. Even worse, some of the people doing that thought it was funny to do so – it was no longer a way to evade a ban to share info, but a way to share info and also signal in-group membership to other TikTok true-crimers. It depersonalized the issue for the people reading it out. You’re not describing a murder, suddenly, you’re describing an ‘unaliving’. A ‘nighty night’. A ‘fishy sleepover’. This is a stranger who died and simultaneously entertainment for their listeners. A real human life and just more words on a paper, just more audio on a website.

Swapping words for cuter ones when not strictly necessary is a cousin-problem to oversharing details while hiding others to make the case seem more mysterious, and otherwise fumbling the handling of a sensitive subject for likes and laughs. Who’s to say anybody wants to be described as ‘unalived’ when they die?


Other words including slurs and targeted swears were also commonly censored… but some slurs aren’t really slurs unless they’re used as slurs maliciously. Additionally, words relating to the LGBTQ+ community that weren’t slurs were also censored, and that required people who wanted to talk about the community to swap words or censor weirdly too. The most egregious example was “Lesbian” being converted to “Le$bean” in text, which didn’t trigger the algorithm and couldn’t be read correctly by the autogenerated voices, leading to people pronouncing it like ‘Le-Dollar-Bean”, the way the computer reader did as a joke.

People tried to cash in on this in a way they hadn’t for ‘unaliving’. Natural crowd movements are something you can market so long as you’re ‘chill’ about it, so it’s not necessarily a horrid idea. However, trying to make a meme localized to a group of people accessible to everyone often kills the meme. People outside the community use it wrong, they use it to be mean, they use it to laugh at the people using the meme, not with them, and the Le-Dollar-Bean song soon became cringe because it was spreading to people who were making fun of the singer and the meme itself in bad faith.

It’s not just because it was LGBT, either, although the meme wouldn’t have happened in the first place if TikTok hadn’t considered that a controversial issue. For example, the same thing happened to the phrases ‘smol bean’ and ‘cinnamon roll’ on Tumblr, which were ways of describing characters who were innocent and cute. Eventually, people started using it to describe real people, and characters who didn’t fit the description but were conventionally attractive (mostly men). Stickers of mainstream actors with the phrases around them were made, even when it didn’t apply, and then those phrases became cringe too via overexposure.

There’s a political statement to be made about the censorship of gay issues that lead to this whole situation – the Le-Dollar-Bean song, a brief mark from people who just wanted to say the word, and ended up co-opted by people who trust corporations that put rainbows on shirts and bracelets with one hand and then funnel money into anti-LGBT bills with the other, is not that statement. Somebody got a little too serious about the joke and overused it, and now Le-Dollar-Bean is cringe, and the reason it’s like that has been forgotten in favor of the song that started the cringe around actually using Le-Dollar-Bean unironically.

The Ethics of Censoring Your Captions

The goal of any translation should be for the receiver to receive it as directly as possible, with some nuance allowed for things that other languages just don’t have. The Japanese don’t really have sarcasm, and may interpret a sarcastic comment as though you were being literal. Similarly, saying something like “I Love You” during a quiet moment comes across as bizarrely direct, so some Japanese may instead reference a poem or a common phrase as shorthand, which can be translated either literally or figuratively in media. Spanish, too, does something similar: if you watch Spanish soap operas, you may hear te quiero, instead of te amo, but both will be translated as “I love you” in the captions (te quiero being literally “I want you”, but understood as “I love you”). (This triggered a huge debate in the Supernatural fandom when the international dubs of the final episode came out, but that’s another story).

So, what does this have to do with English captions on English videos?

Creator-generated captions often censor swear words, or change what the creator is saying, which is not what those are used for! Captions are not the place to hide jokes. It’s an accessibility issue. While hearing viewers may find the dissonance between what’s in the captions and what’s being said funny, the deaf and hard-of-hearing viewers who don’t have that extra context may be confused. If you can’t swear in the captions for fear of censorship, then your interpretation should be ‘I can’t swear in this video’, not ‘I can’t type this swear in the captions’. It’s not ideal, obviously, to have to censor everything, but that’s TikTok’s problem and you should be complaining to TikTok about it, not giving the deaf audience a cleaner version of the video involuntarily.

It’s not all the creators’ fault – some mistakenly believe the app can’t hear them, but will be able to crawl the captions, and thus censor them so they can still be viewed. Others rely on the auto-generated captions, and sometimes it just doesn’t understand the word that’s being said, and mistranslates it to text. Still, effort should be made to convert the audio as closely as possible to the captioning. Don’t baby-talk, don’t misuse them to hide jokes, and don’t intentionally mistranslate!

V-Tubers: The Virtual Youtuber

Elizabeth Technology February 7, 2022

You might have seen videos on Youtube’s front page for what looks like anime characters playing games. What’s the deal?

The Human Ones

We all know fans can be insane. A fan fatally shot Selenas at a concert. A group of teenaged fans targeted celebrities to steal from. Fans surround famous TikTokers’s houses and park in the street, hoping to get a picture or video of them for the app. In Japan, idols are very reluctant to date, because the insane idol culture means that male fans see them as future girlfriends, and a real boyfriend would mean they were ‘cheating’. Superfans seem to think they ‘own’ celebrities. As such, it’s kind of dangerous to actually be out in the wild as a celebrity.

A solution? Make sure people don’t know what you, your house, or your room looks like, and it makes you harder to find. Software can be used to superimpose a 2-D character over a 3-D person, and have it follow their movements. The real person never actually appears on screen, but their facial expressions and gestures are still caught on screen via their avatar. Win-win – the streamer gets to livestream their reaction to their game anonymously.

However, obscuring one’s real identity isn’t the only reason they’re in use. Some streamers use them because they’re fun and colorful, others use them because they can be used to interact with chat without actively interacting with chat – text can scroll across blank spaces on virtual wings or T-shirts. Virtual confetti can rain down on the virtual streamer with some trigger from chat, with no mess to clean up. Sometimes, the person has appeared live before, but just doesn’t want to dress up for their stream – the V-Tuber version of themselves is always perfectly dressed!

The first one, Kizuna Ai, broke ground when she first began streaming. Motion-Capture tech used to be for movies only, as it was prohibitively expensive, and usually required special kinds of suits.

Motion Capture

If you were around for the filming of The Hobbit, you might remember that video of Benedict Cumberbatch flailing around on the ground in a skintight suit covered with white dots. That was the motion capturing process. They used that footage to rig to the face of Smaug, the villain of the story.

But why?

CGI artists would eventually hit a wall if they were to only make things move by hand. Yes, in the short term, doing it manually looked better (and was faster) than motion capturing, smoothing the capture out, rendering, adding in shadows, etc. However, in the long term, motion capture provides a much more realistic experience at a fraction of the cost and time of doing it the old way, especially as models got more and more detailed.

It also caught key parts of human expression and human movement better. Grimacing has many other, smaller facial movements than just the mouth turning downwards, for example. The artist used to have to move all those little details by themselves, and then repeat that for each expression or word, over and over. The other option was an uncanny-valley creation, or one that felt flat – there just wasn’t another way before motion capture.

When filming The Hobbit, Benedict just had to make his expressions into a camera, and then the computer could use key points of the human face to connect to key points of Smaug’s face. It could register his ‘skeleton’ in the footage with those dots on his suit, and use it to create a functioning, moving Smaug shell that followed along. The computer just has to be told where to attach the dots on his suit to the Smaug shell, and Voila!

Science World compares it to three dimensional rotoscoping. Over time, facial recognition software has gotten much better. The Virtual Youtuber doesn’t even need to be wearing a suit for the virtual model to work anymore. It simply understands what a face looks like now, which is incredible. The rigs that streamers use can understand facial expressions, and as long as you tell it where the eyebrows and mouth are, it can mimic them in the virtual shell. This allows for incredible freedom when designing the character – if you want your character to have a tail, all you have to do is tell it what the tail reacts to. Wings? Same deal, you can attach them to your arms’ movements if you want, and they’ll move when you move. Some programs understand clothing physics, and can move capes according to arm movements.

Many programs are in use today[HYPERLINK V-TUBER WIKI]. CodeMiko on Twitch uses the Unreal Engine software, a program used widely by game studios. FaceRig and Animaze are also popular choices, but freeware programs exist as well. It’s entirely possible to make yourself into a V-Tuber with a little elbow grease, and a willingness to work with the models.

An Opinion: V-Tubing is Friendlier than Virtual Influencing

I like V-Tubers. I don’t like Virtual Influencers. They arrived with a kind of smugness, from both their creators and assorted news outlets: “We’re winning. We’re totally funnier and hotter and more interesting than real people.” Yeah. That’s… not really a revelation. Of course an entire team of people, none of which have to actually appear in front of the camera, is going to be more successful at being hot than a real person. Lil Miquela doesn’t have pores or acne or feelings. She is a CGI’d doll that doesn’t have to actively respond to the environment like a V-Tuber rig does. The whole draw of influencers is that they create the illusion that attractive people exist – real people will photoshop themselves too, but normally they have the decency to hide it.

Meanwhile, V-Tubers have the opposite approach. “We all win. Let’s have fun together with this system.” When people can’t show their faces, they can wear a suit that shows their expressions, allows them to interact with chat, and allows them to communicate nonverbally where they otherwise couldn’t. The rig allows them to connect more organically to their audience, not take advantage of them. They were never meant to replace real people – they’re mostly anime-like characters with big eyes and big heads. The person behind the mask is still playing the games, and talking, too; Lil Miquela barely ever has to ‘appear’ for her audience. 90% of her interaction boils down to text that someone else writes and pictures someone else makes. Meanwhile, a V-Tuber is actually behind the screen. A V-Tuber is ultimately a real person with a tool, not a tool being used to replace a real person.  


Fast Fashion

Elizabeth Technology January 14, 2022

You’ve likely heard the term before – and for good reason. Fast fashion is bad for the environment, generates a ton of waste and discarded clothing, and more often than not uses sweatshop labor to keep production up and costs down simultaneously. Fast fashion also often rips off clothing from other, more sustainable, smaller brands, and idea theft in the fashion industry is becoming an increasing problem because of it.

Ultimately, well-made clothes don’t need to be replaced very often. Companies want you to replace them (because that’s how they make money). The clothes ‘got old’, so you should want something ‘new’, says advertising, even if there’s nothing wrong with the clothes themselves.

It’s an ugly thing to be a part of, ethically, environmentally, and monetarily. Fast fashion did exist in the past, but not to such extremes, and generally not for singular outfits and bizarre clothing with holes torn in the functional places. This couldn’t have happened without microtrends and the rise of social media.  

Fashion Nova, Shein, and ClickBait Fashion

Fast fashion produces strange results. Strappy sandals that go all the way up the shin combined with swimsuits in a similar fashion, pants with holes up and down the entirety of the leg and combined with ruffles, a denim bikini – not all of these are wearable, but they’re very eye catching on the website. ‘Fashion’ and ‘art’ and ‘clickbait’ all overlap with each other now in a way they didn’t used to.

Know that the website doesn’t need clothing to sell. It does not make all of these pieces to sell them; it makes them to make the other pieces that are actually wearable ‘pop’. When a fashion brand wants to unveil something controversial and exciting, the traditional play is to do it on the runway, and then tone it down for the actual line. When you see a model in an absurdly big hat, they don’t actually want to sell that hat, they just want to plant the idea of a big hat. The hat is an exaggeration of what they’re actually selling, a sort of caricature for the intended look. Fashion Nova and Shein have essentially started listing the giant hat alongside the real hats. The results are weird.

 Of the pieces that are wearable, they often don’t look as good on ordinary people – or they do, but only with a few other articles of clothing, meaning you’re always wearing one shirt with one set of pants or one pair of shoes to make it work and look good. This ultimately means that you’re not going to wear that item until the other items to go with it are clean and ready to wear, so it’s going to sit in the closet for much longer between wears – and it may be out of trend before you, the wearer, have truly gotten your money’s worth out of it.

Social Media And Cute Stuff

We know that art tends to get consumed and riffed on into unfamiliarity when there’s clout to snatch and money to make. A popular Mitski song about longing was turned into an anthem for strawberry animals, completely missing the point, and Saturn Eating His Son, one of Goya’s final paintings before he died (and a painting he did on the wall of his house, meaning he probably didn’t intend for anyone to actually see and document it before he passed) is sold on mugs and masks. Clothing, unfortunately, gets this treatment worse than most.

See the strawberry dress by designer Lirika Matoshi. A 300$ dress (which sometimes arrived with broken zippers and hanging threads, but that’s another issue) got passed around social media alongside remixes of that Mitski song. Some people bought it, some tried to recreate it for cheaper, and the strawberry dress held TikTok’s attention for long enough that it started appearing in anime fanart. That’s pretty rare! Marketing-wise, this was bizarre but ultimately welcomed. People had Pavloved others into liking this dress because it was awfully cute and fairly easy to draw, and everyone else was into it. Make art with it, that art will get likes. Cute Stuff Trends.

A specific item was in the spotlight – not the designer, not the line, just this one item from her, and then when it faded it was barely seen again except for in the art that recirculates every now and again.

This is the essence of a microtrend.


Microtrend clothing is identifiable by a few different factors:

1) It’s cute and unique – but not so unique it’s shocking

2) It’s reasonably accessible

3) It’s very easy to photograph on almost anyone

4) It has no substitute or ‘dupe’ – only one item will do

5) it comes and goes before outsiders realize it’s ‘in’

Here are the differences between ‘trending items’ and ‘microtrends’. I would classify the brief flash of half-open Hawaiian shirts on picture platforms like Pinterest, TikTok, and Tumblr as a trend, not a microtrend. If all of these pictures were of the same shirt, a shirt conveniently available at Target, or Amazon, then it would have been a microtrend. Even then, the only point it misses is 4 – if everyone had been seeking out a specific shirt to take pictures in, it would have been a bona fide microtrend. The strawberry dress hits all five – by the time people were working out dupes for it, the item was no longer hot.

Microtrends are all of the issues with fast fashion condensed into singular pieces of clothing. A sweater featuring a hillside with cows grazing on it hit the big time after a TikTok creator wore it for a video. The strawberry dress spawned strawberry button-up shirts that had an even shorter lifespan. Once it’s no longer hot for pictures, and all the buyer bought it for was the pictures, what happens to it? Having it was the trend, and now the trend is over.

Small businesses try their best to keep up with microtrends and make something fashionable that could also be ‘viral’, which is a tip taken from fast fashion’s vice grip on social media. I don’t blame small creators for it, because they often do their best to keep things clean and ethical in their production (not all do, but many try). I do blame the big companies who are trying to spark viral want for specific items.

Wanting Clothing? Or Wanting What the Clothing Represents?

Chasing fashion has always been exhausting, but now it’s even worse because other people are expecting their favorite style influencers to have an item and showcase it, but not too late and not in a way that’s obviously ethically questionable.

While clothes are often props for influencers, microtrends and fast fashion items bring it to the extreme. Clothing items are expected to set a scene – that strawberry dress was always out and about, people were twirling in it and frolicking in grass fields. It was a prop for influencers, something especially appealing in color and composition for photos. It wasn’t a very practical item to just… wear. You don’t exist in a 300$ dress, you wear it, take pictures, and then hang it back up.

The same went for the half-open Hawaiian shirts – while the style was very flattering, it could also turn very revealing if the wearer wore it out and about the wrong way. Just like the stuff on those fast fashion sites, it looked good in photos, but the reality of wearing a shirt like that is that you don’t, you wear it a few more buttons done up, not the way the model or the influencers have it on.

The dress, the shirt, the sweater does not exist outside of the scene. These things were being sold by the scene, the same way advertisements try and sell you a lifestyle. The thing this time around is that the influencers had tricked themselves into the marketing for the item instead of waiting to be sponsored for it, because it was so appealing as a prop.

The dress was a symbol of whimsy, bright pink and red and not casual at all. These weird Fashion Nova items are in the same camp – it’s whimsy, flirty, and not casual at all. It’s total unwearable-ness is only a problem when you consider what these microtrends are outside of the internet.  

Digital Clothing

While some see it as the next logical slip into NFT territory and a slow descent into The Emperor’s New Clothes digitally, others are excited by the possibility. Nobody owns the idea, after all, so if you can design your own digital clothing, you can wear it.

Many aspects of fashion are so fashionable and exciting because it involved someone hand-beading 70,000 Swarovski crystals onto a gown. The excess is what makes the runway. While younger folks with experience in digital art understand how difficult it is to sculpt beads in a program like Blender (or something more proprietary) the old guard often sees digital art as ‘art the computer made’, not ‘art someone made with a computer’. Still, digital clothing prevents people from buying things made with sweatshop labor, and it’s flexibility means that influencers don’t have to be under size ten to wear trendy, untailored items, so it does have a lot of appeal.

The appearance often also leaves something to be desired. DressX, the latest platform to try their hand at digital art, offers one-time-use Photoshopping of clothes onto pictures you submit to them. The effects are anywhere from ‘completely believable’ to ‘obviously edited in’. See Youtuber Safiya Nygaard, a Youtuber who tried the service. The first few days of wearing tame clothing with pretty designs went really well… and then she bought a hat to wear, and the hat was so poorly executed that her fans realized some of the previous items were also digital. Imagine buying an item that looks so bad that people who see your pics of it begin to question the reality of other stuff you wore – that’s not what an influencer wants!

Another major downside is that the clothes still cost quite a lot of money for being single-picture-use items. On DressX ( as of right now, September of 2021), you only get one picture for your purchase. If you want more pictures, you have to pay for them separately. Discovering that you don’t like the pose you struck for the outfit is going to cost money. While trendy and neat, spending 60$ every time you want to show off another angle of an item is… not as economical as just buying it, and so this only solves the ethical issues with fast fashion and microtrends for the influencers who can afford to go digital. Any innovation has hard spots, however, so only time will tell if this becomes more accessible and better-looking.


Auto-Beauty Filters are a Problem

Elizabeth Technology January 10, 2022


People have been faking it since the era of portraitry – you’ll notice the royal or rich subjects of paintings rarely have any blemishes on their skin, even though acne, smallpox, and rashes have always been around. Even when certain features had to be depicted, they were often minimized or altered to make the subject happy. As an extreme example, look at Charles II of Spain – a member of the Habsburg line, which had become notorious for incrossing from family instead of marrying out, a common tactic used to retain power within the bloodline.

Unfortunately, genetic conditions resulted. Charles’s physical deformities made his face somewhat difficult to use as a face– the poor guy had what’s known as ‘The Hapsburg Chin’, a genetic condition passed down from his parents. You can actually trace who in his family had it (and how severely they had it) via their portraits; the royal painters had to tread carefully between depicting their subject accurately and depicting them without insulting them. They had mirrors, of course he knew what he looked like – but, just like today, the subjects wanted to be remembered for more than their facial scars and the extensive mistakes of the royal family. The prince didn’t mind being depicted through the rose-tinted lenses of his artist. When paintings are an expensive luxury, the client wants what they want.

Our recordings of what he looked like and how he was described in writing differ somewhat – in theory, you could still recognize him from his portrait, and that was good enough. The same goes for any number of royals. Airbrushing has always existed!   


Painters weren’t the only ones who took liberties.

Film was also an expensive luxury. If people from the past seemed unusually clear-skinned, they might not have been – a combination of makeup and film retouching removes blemishes like acne scars and wrinkles from the image. Cystic acne can be genetic, syphilis was uncured, and smallpox survivors were still around, but you’d never guess the subjects of professional portraits suffered from those conditions too! Editing in black-and-white or sepia images isn’t witchcraft: it’s as simple as color-matching the person’s skin on the negative, and then painting over the flaw so it’s invisible on the developed image.

So retouching was definitely still a thing – it just wasn’t digital.

When color film hit the market, retouching could still be done, but the process was more difficult as photographers had to compensate for three colors, not just the one. A combination of special dyes and extremely fine brushes on an oversized negative, combined with better makeup, cameras, and specialty lenses (lenses designed to ‘soften’ the image, for example) allowed photographers to make their magazine cover photo flawless. This took time, and it was expensive, however, so retaking the image was often easier than editing out blemishes in post.  

Digital Smoothing

Beyond film, how did you retouch things in the early days of digital filming?

Doing digital work on a person’s face was reserved for magazines, professionals, and hobbyists – not just anyone could pop the SD card into a computer and start removing things. Ironically, the widespread availability of picture-taking items like digital cameras made the overall quality worse. When professionals took digital pictures, they never showed the client the blurry ones, and thumbs were never over critical parts of the lens during the picture-taking. Digital cameras also had lower stakes – you weren’t wasting film by taking three or four shots of the same thing to be sure you ‘had’ it.

Editing software relies on the strength or power of the computer that’s attempting to edit the image. More powerful computers can handle larger images, and gradually-improving computer strength lessened the reliance on film. As a result, businesses and major voices in the photo and film industries switched over when they could, so there is no exact ‘moment’ where editing surpassed painting – it happened in steps.

This also meant that film – which editors were familiar with and could process faster than the still-developing editing software – still held the upper hand for quite some time. Film can be endlessly upscaled; digital images cannot be. The strange grain you see on shows from the 2000s comes from being recorded digitally before the technology was fully mature. That’s just what they looked like, and fixing it would take some pretty intense AI or editing intervention. Meanwhile, films made during that time don’t look old – the clothing, speaking, and actors date the recording, not the visual grain. See the difference between a show like Lost and a show like Real Housewives. The decision to film Lost on real 30mm film has ensured it’s not as dated as it could be.

The iPhone, and Early Retouch Apps

The iPhone wasn’t the beginning of selfies – people took plenty when cameras (especially film cameras) were cheap. And the iPhone didn’t start the trend of editing, either, as you can see above. What the iPhone did was merge the two and allow them to come together in the hands of laymen. Now, with an ‘app’, anyone can take a pic and retouch it, send it to friends and family, print it, rotate it, crop it, etc. all without expert help.

This is no substitute for professional work (the first iPhone took better pics than many other mobile phones, but worse ones than professional or digital cameras) but it isn’t asked to be – we are far beyond the times when pictures were special occasions. You can track how expensive a picture was by the quality and quantity of selfies taken during the period. Did that person dress nicely for the occasion? Was it taken somewhere special? Are they posed in a way that suggests it wasn’t casual? Are they sitting for the photo, or do they just happen to be sitting when the photo was taken?

Early retouch apps were clumsy and frequently difficult to use subtly. If images from Myspace and early Facebook are any indication, the line tool was about as good as it got for tweens – the phone camera couldn’t compare to the stuff magazines and TV shows were using. ‘Digital smoothing’ available to the average consumer was about as good as a blur filter today, which is not very good. MSPaint was a legitimate option for altering profile pics. It just… all looked sort of bad. But it was passable! It wasn’t ideal, but in an era where people are just beginning to learn about Photoshop, and only experts and hobbyists really have it, any editing done to a photo had to be really brazen to not pass as ‘makeup’ or ‘lighting’ to an inexperienced internet.

Of course, professional photos still look professional, and airbrushing celebrities has only gotten more intense, but the average user is not trapped by this yet. For every smoothed, poreless face on the cover of a magazine, there are programs on MTV and tabloids showing what they look like without the touch-ups. Celebrities are an other, and you and your friends still look normal.

SnapChat Filters

And here is where we begin to see issues. SnapChat filters became a thing, and started acting like mirrors. This is a bigger problem than it sounds, and you’ll know why – when you change your haircut, when you put on or take off glasses, or in pictures, you look a little alien to yourself, but eventually, the change settles in and your internal image adjusts to what your eyes are seeing in the mirror. What if you have two mirrors, and one isn’t telling the whole truth? Which image does your brain adapt to? According to research, it’s the one that exaggerates the features you like about yourself, not the honest one.

Snapchat’s filters almost universally slim the face and lighten it up a little, too, even under ‘goofy’ filters like the animal ear ones. Other versions don’t even bother with the pretense of animal ears, they just slap some butterflies on and call it a beauty filter. The end result is a face that may be perceived as more attractive than a plain selfie. This is a problem for a couple of reasons! Assuming a whiter, thinner person is always better than the default image has troubling implications, and while this could make the pictures more attractive to the user, it does so in a way that changes their idea of their own face so much that they can’t look at the regular mirror without feeling vague dysmorphia.

Because these apps aim at teens, tweens, and twenty-somethings, the issue is magnified by developmental steps. They’re right at the age where they begin to notice how they look (and how others may perceive them). Many people get acne as teens, for example, but the Snapchat filters reduce the appearance of red blotches and uneven spots, spots they will have to look at elsewhere. Like mirrors, school photos, photos taken in school clubs, family photos, etc. making special moments more difficult to capture without self-consciousness getting in the way.

Overuse of social media exacerbates the issue, and the baseline for what people really look like is lost. During this time, however, the tech was limited to a select number of apps. It’s still possible to avoid it, and the only people really being affected are people who were spending an unhealthy amount of time online anyway. Surely, simply curbing use and being aware of how filters change your face is good enough to combat it, right?

The Rest

It was… until this new generation of apps and phones came out, and all of the visual ones came with some sort of ‘enhancement’ feature. Some users on TikTok report blurring and re-coloring even when no filters are active. The iPhone and many Android devices now come with beauty filters on by default. The new cameras took in so much information that it seemed silly not to try and capitalize with AI. All of this on top of the social media apps, and magazines, and retouching already seen everywhere else.

If you want to use a social app, you will see other people (many of whom you may associate with IRL because it’s a social app) using filters, even if you decide not to. You will also find that adding cool effects without altering your face is difficult-to-impossible, because it all comes built in. Filters to change eye color? Filters to add fire or ice effects? Filters that make the image black and white, or sepia? All of them come with facial smoothing.

If looking up to absurdly skinny and unrealistically ripped folks causes body issues, imagine what auto-smoothing is doing. “You could look like this,” these auto-apps say, “but you don’t really. So keep using us because we’re the only place you look right.” It is a difficult world to navigate. The worst part is that many of them know this, but their solutions or damage-control attempts can’t come with advice to stop using the platform. The best TikTok does is recommend breaks, and Snapchat, with it’s Streaks deal, doesn’t encourage you to stop at all. Instagram is not better either.

Hidden and unremovable beauty filters are posing a bigger threat than their users realize – once you see yourself in the black mirror, the silver one seems inadequate.

Sources: ( the gif at the top of the screen shows how even filters not marketed for ‘smoothing’ or ‘beauty’ smooth features.)