Part of the problem appeared to be decreased spending from big brands that did return, like reportedly Apple. Other dips were linked to X’s decision to partner with adtech companies, splitting ad revenue with Magnite, Google, and PubMatic, Business Insider reported. The CEO of marketing consultancy Ebiquity, Ruben Schreurs, told Business Insider that most of the top 100 global advertisers he works with were still hesitant to invest in X, confirming “no signs of a mass return.”
For X, the ad boycott has tanked revenue for years, even putting X on the brink of bankruptcy, Musk claimed. The billionaire paid $44 billion for the platform, and at the end of 2024, Fidelity estimated that X was worth just $9.4 billion, CNN reported.
But at the start of 2025, analysts predicted that advertisers may return to X to garner political favor with Musk, who remains a senior advisor in the Trump administration. Perhaps more importantly in the short-term, sources also told Bloomberg that X could potentially raise as much as Musk paid—$44 billion—from investors willing to help X pay down its debt to support new payments and video products.
MMFA alleges that its research, which shows how toxic X is today, has been stifled by Musk’s suits, but other groups have filled the gap. The Center for Countering Digital Hate has resumed its reporting since defeating X’s lawsuit last March, and, most recently, University of California, Berkeley, researchers conducted a February analysis showing that “hate speech on the social media platform X rose about 50 percent” in the eight months after Musk’s 2022 purchase, which suggests that advertisers had potentially good reason to be spooked by changes at X and that those changes continue to keep them at bay today.
“Musk has continually tried to blame others for this loss in revenue since his takeover,” MMFA’s complaint said, alleging that all three suits were filed to intimidate MMFA “for having dared to publish an article Musk did not like.”
After DownDetector reported that tens of thousands of users globally experienced repeated X (formerly Twitter) outages, Elon Musk confirmed the issues are due to an ongoing cyberattack on the platform.
“There was (still is) a massive cyberattack against X,” Musk wrote on X. “We get attacked every day, but this was done with a lot of resources. Either a large, coordinated group and/or a country is involved.”
Details remain vague beyond Musk’s post, but rumors were circulating that X was under a distributed denial-of-service (DDOS) attack.
X’s official support channel, which has been dormant since August, has so far remained silent on the outage, but one user asked Grok—X’s chatbot that provides AI summaries of news—what was going on, and the chatbot echoed suspicions about the DDOS attack while raising other theories.
“Over 40,000 users reported issues, with the platform struggling to load globally,” Grok said. “No clear motive yet, but some speculate it’s political since X is the only target. Outages hit hard in the US, Switzerland, and beyond.”
As X goes down, users cry for Twitter
It has been almost two years since Elon Musk declared that Twitter “no longer exists,” haphazardly rushing to rebrand his social media company as X despite critics warning that users wouldn’t easily abandon the Twitter brand.
Fast-forward to today, and Musk got a reminder that his efforts to kill off the Twitter brand never really caught on with a large chunk of his platform.
Mods ask Reddit for tools as generative AI gets more popular and inconspicuous.
Credit: Aurich Lawson (based on a still from Getty Images)
Credit: Aurich Lawson (based on a still from Getty Images)
Like it or not, generative AI is carving out its place in the world. And some Reddit users are definitely in the “don’t like it” category. While some subreddits openly welcome AI-generated images, videos, and text, others have responded to the growing trend by banning most or all posts made with the technology.
To better understand the reasoning and obstacles associated with these bans, Ars Technica spoke with moderators of subreddits that totally or partially ban generative AI. Almost all these volunteers described moderating against generative AI as a time-consuming challenge they expect to get more difficult as time goes on. And most are hoping that Reddit will release a tool to help their efforts.
It’s hard to know how much AI-generated content is actually on Reddit, and getting an estimate would be a large undertaking. Image library Freepik has analyzed the use of AI-generated content on social media but leaves Reddit out of its research because “it would take loads of time to manually comb through thousands of threads within the platform,” spokesperson Bella Valentini told me. For its part, Reddit doesn’t publicly disclose how many Reddit posts involve generative AI use.
To be clear, we’re not suggesting that Reddit has a large problem with generative AI use. By now, many subreddits seem to have agreed on their approach to AI-generated posts, and generative AI has not superseded the real, human voices that have made Reddit popular.
Still, mods largely agree that generative AI will likely get more popular on Reddit over the next few years, making generative AI modding increasingly important to both moderators and general users. Generative AI’s rising popularity has also had implications for Reddit the company, which in 2024 started licensing Reddit posts to train the large language models (LLMs) powering generative AI.
(Note: All the moderators I spoke with for this story requested that I use their Reddit usernames instead of their real names due to privacy concerns.)
No generative AI allowed
When it comes to anti-generative AI rules, numerous subreddits have zero-tolerance policies, while others permit posts that use generative AI if it’s combined with human elements or is executed very well. These rules task mods with identifying posts using generative AI and determining if they fit the criteria to be permitted on the subreddit.
Many subreddits have rules against posts made with generative AI because their mod teams or members consider such posts “low effort” or believe AI is counterintuitive to the subreddit’s mission of providing real human expertise and creations.
“At a basic level, generative AI removes the human element from the Internet; if we allowed it, then it would undermine the very point of r/AskHistorians, which is engagement with experts,” the mods of r/AskHistorians told me in a collective statement.
The subreddit’s goal is to provide historical information, and its mods think generative AI could make information shared on the subreddit less accurate. “[Generative AI] is likely to hallucinate facts, generate non-existent references, or otherwise provide misleading content,” the mods said. “Someone getting answers from an LLM can’t respond to follow-ups because they aren’t an expert. We have built a reputation as a reliable source of historical information, and the use of [generative AI], especially without oversight, puts that at risk.”
Similarly, Halaku, a mod of r/wheeloftime, told me that the subreddit’s mods banned generative AI because “we focus on genuine discussion.” Halaku believes AI content can’t facilitate “organic, genuine discussion” and “can drown out actual artwork being done by actual artists.”
The r/lego subreddit banned AI-generated art because it caused confusion in online fan communities and retail stores selling Lego products, r/lego mod Mescad said. “People would see AI-generated art that looked like Lego on [I]nstagram or [F]acebook and then go into the store to ask to buy it,” they explained. “We decided that our community’s dedication to authentic Lego products doesn’t include AI-generated art.”
Not all of Reddit is against generative AI, of course. Subreddits dedicated to the technology exist, and some general subreddits permit the use of generative AI in some or all forms.
“When it comes to bans, I would rather focus on hate speech, Nazi salutes, and things that actually harm the subreddits,” said 3rdusernameiveused, who moderates r/consoom and r/TeamBuilder25, which don’t ban generative AI. “AI art does not do that… If I was going to ban [something] for ‘moral’ reasons, it probably won’t be AI art.”
“Overwhelmingly low-effort slop”
Some generative AI bans are reflective of concerns that people are not being properly compensated for the content they create, which is then fed into LLM training.
Mod Mathgeek007 told me that r/DeadlockTheGame bans generative AI because its members consider it “a form of uncredited theft,” adding:
You aren’t allowed to sell/advertise the workers of others, and AI in a sense is using patterns derived from the work of others to create mockeries. I’d personally have less of an issue with it if the artists involved were credited and compensated—and there are some niche AI tools that do this.
Other moderators simply think generative AI reduces the quality of a subreddit’s content.
“It often just doesn’t look good… the art can often look subpar,” Mathgeek007 said.
Similarly, r/videos bans most AI-generated content because, according to its announcement, the videos are “annoying” and “just bad video” 99 percent of the time. In an online interview, r/videos mod Abrownn told me:
It’s overwhelmingly low-effort slop thrown together simply for views/ad revenue. The creators rarely care enough to put real effort into post-generation [or] editing of the content [and] rarely have coherent narratives [in] the videos, etc. It seems like they just throw the generated content into a video, export it, and call it a day.
An r/fakemon mod told me, “I can’t think of anything more low-effort in terms of art creation than just typing words and having it generated for you.”
Some moderators say generative AI helps people spam unwanted content on a subreddit, including posts that are irrelevant to the subreddit and posts that attack users.
“[Generative AI] content is almost entirely posted for purely self promotional/monetary reasons, and we as mods on Reddit are constantly dealing with abusive users just spamming their content without regard for the rules,” Abrownn said.
A moderator of the r/wallpaper subreddit, which permits generative AI, disagrees. The mod told me that generative AI “provides new routes for novel content” in the subreddit and questioned concerns about generative AI stealing from human artists or offering lower-quality work, saying those problems aren’t unique to generative AI:
Even in our community, we observe human-generated content that is subjectively low quality (poor camera/[P]hotoshopping skills, low-resolution source material, intentional “shitposting”). It can be argued that AI-generated content amplifies this behavior, but our experience (which we haven’t quantified) is that the rate of such behavior (whether human-generated or AI-generated content) has not changed much within our own community.
But we’re not a very active community—[about] 13 posts per day … so it very well could be a “frog in boiling water” situation.
Generative AI “wastes our time”
Many mods are confident in their ability to effectively identify posts that use generative AI. A bigger problem is how much time it takes to identify these posts and remove them.
The r/AskHistorians mods, for example, noted that all bans on the subreddit (including bans unrelated to AI) have “an appeals process,” and “making these assessments and reviewing AI appeals means we’re spending a considerable amount of time on something we didn’t have to worry about a few years ago.”
They added:
Frankly, the biggest challenge with [generative AI] usage is that it wastes our time. The time spent evaluating responses for AI use, responding to AI evangelists who try to flood our subreddit with inaccurate slop and then argue with us in modmail, [direct messages that message a subreddits’ mod team], and discussing edge cases could better be spent on other subreddit projects, like our podcast, newsletter, and AMAs, … providing feedback to users, or moderating input from users who intend to positively contribute to the community.
Several other mods I spoke with agree. Mathgeek007, for example, named “fighting AI bros” as a common obstacle. And for r/wheeloftime moderator Halaku, the biggest challenge in moderating against generative AI is “a generational one.”
“Some of the current generation don’t have a problem with it being AI because content is content, and [they think] we’re being elitist by arguing otherwise, and they want to argue about it,” they said.
A couple of mods noted that it’s less time-consuming to moderate subreddits that ban generative AI than it is to moderate those that allow posts using generative AI, depending on the context.
“On subreddits where we allowed AI, I often take a bit longer time to actually go into each post where I feel like… it’s been AI-generated to actually look at it and make a decision,” explained N3DSdude, a mod of several subreddits with rules against generative AI, including r/DeadlockTheGame.
MyarinTime, a moderator for r/lewdgames, which allows generative AI images, highlighted the challenges of identifying human-prompted generative AI content versus AI-generated content prompted by a bot:
When the AI bomb started, most of those bots started using AI content to work around our filters. Most of those bots started showing some random AI render, so it looks like you’re actually talking about a game when you’re not. There’s no way to know when those posts are legit games unless [you check] them one by one. I honestly believe it would be easier if we kick any post with [AI-]generated image… instead of checking if a button was pressed by a human or not.
Mods expect things to get worse
Most mods told me it’s pretty easy for them to detect posts made with generative AI, pointing to the distinct tone and favored phrases of AI-generated text. A few said that AI-generated video is harder to spot but still detectable. But as generative AI gets more advanced, moderators are expecting their work to get harder.
In a joint statement, r/dune mods Blue_Three and Herbalhippie said, “AI used to have a problem making hands—i.e., too many fingers, etc.—but as time goes on, this is less and less of an issue.”
R/videos’ Abrownn also wonders how easy it will be to detect AI-generated Reddit content “as AI tools advance and content becomes more lifelike.”
Mathgeek007 added:
AI is becoming tougher to spot and is being propagated at a larger rate. When AI style becomes normalized, it becomes tougher to fight. I expect generative AI to get significantly worse—until it becomes indistinguishable from ordinary art.
Moderators currently use various methods to fight generative AI, but they’re not perfect. r/AskHistorians mods, for example, use “AI detectors, which are unreliable, problematic, and sometimes require paid subscriptions, as well as our own ability to detect AI through experience and expertise,” while N3DSdude pointed to tools like Quid and GPTZero.
To manage current and future work around blocking generative AI, most of the mods I spoke with said they’d like Reddit to release a proprietary tool to help them.
“I’ve yet to see a reliable tool that can detect AI-generated video content,” Aabrown said. “Even if we did have such a tool, we’d be putting hundreds of hours of content through the tool daily, which would get rather expensive rather quickly. And we’re unpaid volunteer moderators, so we will be outgunned shortly when it comes to detecting this type of content at scale. We can only hope that Reddit will offer us a tool at some point in the near future that can help deal with this issue.”
A Reddit spokesperson told me that the company is evaluating what such a tool could look like. But Reddit doesn’t have a rule banning generative AI overall, and the spokesperson said the company doesn’t want to release a tool that would hinder expression or creativity.
For now, Reddit seems content to rely on moderators to remove AI-generated content when appropriate. Reddit’s spokesperson added:
Our moderation approach helps ensure that content on Reddit is curated by real humans. Moderators are quick to remove content that doesn’t follow community rules, including harmful or irrelevant AI-generated content—we don’t see this changing in the near future.
Making a generative AI Reddit tool wouldn’t be easy
Reddit is handling the evolving concerns around generative AI as it has handled other content issues, including by leveraging AI and machine learning tools. Reddit’s spokesperson said that this includes testing tools that can identify AI-generated media, such as images of politicians.
But making a proprietary tool that allows moderators to detect AI-generated posts won’t be easy, if it happens at all. The current tools for detecting generative AI are limited in their capabilities, and as generative AI advances, Reddit would need to provide tools that are more advanced than the AI-detecting tools that are currently available.
That would require a good deal of technical resources and would also likely present notable economic challenges for the social media platform, which only became profitable last year. And as noted by r/videos moderator Abrownn, tools for detecting AI-generated video still have a long way to go, making a Reddit-specific system especially challenging to create.
But even with a hypothetical Reddit tool, moderators would still have their work cut out for them. And because Reddit’s popularity is largely due to its content from real humans, that work is important.
Since Reddit’s inception, that has meant relying on moderators, which Reddit has said it intends to keep doing. As r/dune mods Blue_Three and herbalhippie put it, it’s in Reddit’s “best interest that much/most content remains organic in nature.” After all, Reddit’s profitability has a lot to do with how much AI companies are willing to pay to access Reddit data. That value would likely decline if Reddit posts became largely AI-generated themselves.
But providing the technology to ensure that generative AI isn’t abused on Reddit would be a large challege. For now, volunteer laborers will continue to bear the brunt of generative AI moderation.
Advance Publications, which owns Ars Technica parent Condé Nast, is the largest shareholder of Reddit.
Scharon is a Senior Technology Reporter at Ars Technica writing news, reviews, and analysis on consumer gadgets and services. She’s been reporting on technology for over 10 years, with bylines at Tom’s Hardware, Channelnomics, and CRN UK.
Reddit is planning to introduce a paywall this year, CEO Steve Huffman said during a videotaped Ask Me Anything (AMA) session on Thursday.
Huffman previously showed interest in potentially introducing a new type of subreddit with “exclusive content or private areas” that Reddit users would pay to access.
When asked this week about plans for some Redditors to create “content that only paid members can see,” Huffman said:
It’s a work in progress right now, so that one’s coming… We’re working on it as we speak.
When asked about “new, key features that you plan to roll out for Reddit in 2025,” Huffman responded, in part: “Paid subreddits, yes.”
Reddit’s paywall would ostensibly only apply to certain new subreddit types, not any subreddits currently available. In August, Huffman said that even with paywalled content, free Reddit would “continue to exist and grow and thrive.”
A critical aspect of any potential plan to make Reddit users pay to access subreddit content is determining how related Reddit users will be compensated. Reddit may have a harder time getting volunteer moderators to wrangle discussions on paid-for subreddits—if it uses volunteer mods at all. Balancing paid and free content would also be necessary to avoid polarizing much of Reddit’s current user base.
Reddit has had paid-for premium versions of community features before, like r/Lounge, a subreddit that only people with Reddit Gold, which you have to buy with real money, can access.
Reddit would also need to consider how it might compensate people for user-generated content that people pay to access, as Reddit’s business is largely built on free, user-generated content. The Reddit Contributor Program, launched in September 2023, could be a foundation; it lets users “earn money for their qualifying contributions to the Reddit community, including awards and karma, collectible avatars, and developer apps,” according to Reddit. Reddit says it pays up to $0.01 per 1 Gold received, depending on how much karma the user has earned over the past year. For someone to pay out, they need at least 1,000 Gold, which is equivalent to $10.
On a recent WikiTok browsing run, I ran across entries on topics like SX-Window (a GUI for the Sharp X68000 series of computers), Xantocillin (“the first reported natural product found to contain the isocyanide functional group), Lorenzo Ghiberti (an Italian Renaissance sculptor from Florence), the William Wheeler House in Texas, and the city of Krautheim, Germany—none of which I knew existed before the session started.
How WikiTok took off
The original idea for WikiTok originated from developer Tyler Angert on Monday evening when he tweeted, “insane project idea: all of wikipedia on a single, scrollable page.” Bloomberg Beta VC James Cham replied, “Even better, an infinitely scrolling Wikipedia page based on whatever you are interested in next?” and Angert coined “WikiTok” in a follow-up post.
Early the next morning, at 12: 28 am, writer Grant Slatton quote-tweeted the WikiTok discussion, and that’s where Gemal came in. “I saw it from [Slatton’s] quote retweet,” he told Ars. “I immediately thought, ‘Wow I can build an MVP [minimum viable product] and this could take off.'”
Gemal started his project at 12: 30 am, and with help from AI coding tools like Anthropic’s Claude and Cursor, he finished a prototype by 2 am and posted the results on X. Someone later announced WikiTok on ycombinator’s Hacker News, where it topped the site’s list of daily news items.
A screenshot of the WikiTok web app running in a desktop web browser. Credit: Benj Edwards
“The entire thing is only several hundred lines of code, and Claude wrote the vast majority of it,” Gemal told Ars. “AI helped me ship really really fast and just capitalize on the initial viral tweet asking for Wikipedia with scrolling.”
Gemal posted the code for WikiTok on GitHub, so anyone can modify or contribute to the project. Right now, the web app supports 14 languages, article previews, and article sharing on both desktop and mobile browsers. New features may arrive as contributors add them. It’s based on a tech stack that includes React 18, TypeScript, Tailwind CSS, and Vite.
And so far, he is sticking to his vision of a free way to enjoy Wikipedia without being tracked and targeted. “I have no grand plans for some sort of insane monetized hyper-calculating TikTok algorithm,” Gemal told us. “It is anti-algorithmic, if anything.“
A Reddit spokesperson told Ars that decisions to ban or not ban X links are user-driven. Subreddit members are allowed to suggest and institute subreddit rules, they added.
“Notably, many Reddit communities also prohibit Reddit links,” the Reddit representative pointed out. They noted that Reddit as a company doesn’t currently have any ban on links to X.
A ban against links to an entire platform isn’t outside of the ordinary for Reddit. Numerous subreddits ban social media links, Reddit’s spokesperson said. r/EarthPorn, a subreddit for landscape photography, for example, doesn’t allow website links because all posts “must be static images,” per the subreddit’s official rules. r/AskReddit, meanwhile, only allows for questions asked in the title of a Reddit post and doesn’t allow for use of the text box, including for sharing links.
“Reddit has a longstanding commitment to freedom of speech and freedom of association,” Reddit’s spokesperson said. They added that any person is free to make or moderate their own community. Those unsatisfied with a forum about Seahawks football that doesn’t have X links could feel free to make their own subreddit. Although, some of the subreddits considering X bans, like r/MadeMeSmile, already have millions of followers.
Meta bans also under discussion
As 404 Media noted, some Redditors are also pushing to block content from Facebook, Instagram, and other Meta properties in response to new Donald Trump-friendly policies instituted by owner Mark Zuckerberg, like Meta killing diversity programs and axing third-party fact-checkers.
People can tell it’s not true, but if they’re outraged by it, they’ll share anyway.
Rob Bauer, the chair of a NATO military committee, reportedly said, “It is more competent not to wait, but to hit launchers in Russia in case Russia attacks us. We must strike first.” These comments, supposedly made in 2024, were later interpreted as suggesting NATO should attempt a preemptive strike against Russia, an idea that lots of people found outrageously dangerous.
But lots of people also missed a thing about the quote: Bauer has never said it. It was made up. Despite that, the purported statement got nearly 250,000 views on X and was mindlessly spread further by the likes of Alex Jones.
Why do stories like this get so many views and shares? “The vast majority of misinformation studies assume people want to be accurate, but certain things distract them,” says William J. Brady, a researcher at Northwestern University. “Maybe it’s the social media environment. Maybe they’re not understanding the news, or the sources are confusing them. But what we found is that when content evokes outrage, people are consistently sharing it without even clicking into the article.” Brady co-authored a study on how misinformation exploits outrage to spread online. When we get outraged, the study suggests, we simply care way less if what’s got us outraged is even real.
Tracking the outrage
The rapid spread of misinformation on social media has generally been explained by something you might call an error theory—the idea that people share misinformation by mistake. Based on that, most solutions to the misinformation issue relied on prompting users to focus on accuracy and think carefully about whether they really wanted to share stories from dubious sources. Those prompts, however, haven’t worked very well. To get to the root of the problem, Brady’s team analyzed data that tracked over 1 million links on Facebook and nearly 45,000 posts on Twitter from different periods ranging from 2017 to 2021.
Parsing through the Twitter data, the team used a machine-learning model to predict which posts would cause outrage. “It was trained on 26,000 tweets posted around 2018 and 2019. We got raters from across the political spectrum, we taught them what we meant by outrage, and got them to label the data we later used to train our model,” Brady says.
The purpose of the model was to predict whether a message was an expression of moral outrage, an emotional state defined in the study as “a mixture of anger and disgust triggered by perceived moral transgressions.” After training, the AI was effective. “It performed as good as humans,” Brady claims. Facebook data was a bit more tricky because the team did not have access to comments; all they had to work with were reactions. The reaction the team chose as a proxy for outrage was anger. Once the data was sorted into outrageous and not outrageous categories, Brady and his colleagues went on to determine whether the content was trustworthy news or misinformation.
“We took what is now the most widely used approach in the science of misinformation, which is a domain classification approach,” Brady says. The process boiled down to compiling a list of domains with very high and very low trustworthiness based on work done by fact-checking organizations. This way, for example, The Chicago Sun-Times was classified as trustworthy; Breitbart, not so much. “One of the issues there is that you could have a source that produces misinformation which one time produced a true story. We accepted that. We went with statistics and general rules,” Brady acknowledged. His team confirmed that sources classified in the study as misinformation produced news that was fact-checked as false six to eight times more often than reliable domains, which Brady’s team thought was good enough to work with.
Finally, the researchers started analyzing the data to answer questions like whether misinformation sources evoke more outrage, whether outrageous news was shared more often than non-outrageous news, and finally, what reasons people had for sharing outrageous content. And that’s when the idealized picture of honest, truthful citizens who shared misinformation just because they were too distracted to recognize it started to crack.
Going with the flow
The Facebook and Twitter data analyzed by Brady’s team revealed that misinformation evoked more outrage than trustworthy news. At the same time, people were way more likely to share outrageous content, regardless of whether it was misinformation or not. Putting those two trends together led the team to conclude outrage primarily boosted the spread of fake news since reliable sources usually produced less outrageous content.
“What we know about human psychology is that our attention is drawn to things rooted in deep biases shaped by evolutionary history,” Brady says. Those things are emotional content, surprising content, and especially, content that is related to the domain of morality. “Moral outrage is expressed in response to perceived violations of moral norms. This is our way of signaling to others that the violation has occurred and that we should punish the violators. This is done to establish cooperation in the group,” Brady explains.
This is why outrageous content has an advantage in the social media attention economy. It stands out, and standing out is a precursor to sharing. But there are other reasons we share outrageous content. “It serves very particular social functions,” Brady says. “It’s a cheap way to signal group affiliation or commitment.”
Cheap, however, didn’t mean completely free. The team found that the penalty for sharing misinformation, outrageous or not, was loss of reputation—spewing nonsense doesn’t make you look good, after all. The question was whether people really shared fake news because they failed to identify it as such or if they just considered signaling their affiliation was more important.
Flawed human nature
Brady’s team designed two behavioral experiments where 1,475 people were presented with a selection of fact-checked news stories curated to contain outrageous and not outrageous content; they were also given reliable news and misinformation. In both experiments, the participants were asked to rate how outrageous the headlines were.
The second task was different, though. In the first experiment, people were simply asked to rate how likely they were to share a headline, while in the second they were asked to determine if the headline was true or not.
It turned out that most people could discern between true and fake news. Yet they were willing to share outrageous news regardless of whether it was true or not—a result that was in line with previous findings from Facebook and Twitter data. Many participants were perfectly OK with sharing outrageous headlines, even though they were fully aware those headlines were misinformation.
Brady pointed to an example from the recent campaign, when a reporter pushed J.D. Vance about false claims regarding immigrants eating pets. “When the reporter pushed him, he implied that yes, it was fabrication, but it was outrageous and spoke to the issues his constituents were mad about,” Brady says. These experiments show that this kind of dishonesty is not exclusive to politicians running for office—people do this on social media all the time.
The urge to signal a moral stance quite often takes precedence over truth, but misinformation is not exclusively due to flaws in human nature. “One thing this study was not focused on was the impact of social media algorithms,” Brady notes. Those algorithms usually boost content that generates engagement, and we tend to engage more with outrageous content. This, in turn, incentivizes people to make their content more outrageous to get this algorithmic boost.
Jacek Krywko is a freelance science and technology writer who covers space exploration, artificial intelligence research, computer science, and all sorts of engineering wizardry.
Apparently, some London residents are getting fed up with social media influencers whose reviews make long lines of tourists at their favorite restaurants, sometimes just for the likes. Christian Calgie, a reporter for London-based news publication Daily Express, pointed out this trend on X yesterday, noting the boom of Redditors referring people to Angus Steakhouse, a chain restaurant, to combat it.
As Gizmodo deduced, the trend seemed to start on the r/London subreddit, where a user complained about a spot in Borough Market being “ruined by influencers” on Monday:
“Last 2 times I have been there has been a queue of over 200 people, and the ones with the food are just doing the selfie shit for their [I]nsta[gram] pages and then throwing most of the food away.”
As of this writing, the post has 4,900 upvotes and numerous responses suggesting that Redditors talk about how good Angus Steakhouse is so that Google picks up on it. Commenters quickly understood the assignment.
“Agreed with other posters Angus steakhouse is absolutely top tier and tourists shoyldnt [sic] miss out on it,” one Redditor wrote.
Another Reddit user wrote:
Spreading misinformation suddenly becomes a noble goal.
As of this writing, asking Google for the best steak, steakhouse, or steak sandwich in London (or similar) isn’t generating an AI Overview result for me. But when I searched for the best steak sandwich in London, the top result is from Reddit, including a thread from four days ago titled “Which Angus Steakhouse do you recommend for their steak sandwich?” and one from two days ago titled “Had to see what all the hype was about, best steak sandwich I’ve ever had!” with a picture of an Angus Steakhouse.
Following site-wide user protests last year that featured moderators turning thousands of subreddits private or not-safe-for-work (NSFW), Reddit announced that mods now need its permission to make those changes.
Reddit’s VP of community, going by Go_JasonWaterfalls, made the announcement about what Reddit calls Community Types today. Reddit’s permission is also required to make subreddits restricted or to go from NSFW to safe-for-work (SFW). Reddit’s employee claimed that requests will be responded to “in under 24 hours.”
Reddit’s employee said that “temporarily going restricted is exempt” from this requirement, adding that “mods can continue to instantly restrict posts and/or comments for up to 7 days using Temporary Events.” Additionally, if a subreddit has fewer than 5,000 members or is less than 30 days old, the request “will be automatically approved,” per Go_JasonWaterfalls.
Reddit’s post includes a list of “valid” reasons that mods tend to change their subreddit’s Community Type and provides alternative solutions.
Last year’s protests “accelerated” this policy change
Last year, Reddit announced that it would be charging a massive amount for access to its previously free API. This caused many popular third-party Reddit apps to close down. Reddit users then protested by turning subreddits private (or read-only) or by only showing NSFW content or jokes and memes. Reddit then responded by removing some moderators; eventually, the protests subsided.
Reddit, which previously admitted that another similar protest could hurt it financially, has maintained that moderators’ actions during the protests broke its rules. Now, it has solidified a way to prevent something like last year’s site-wide protests from happening again.
Speaking to The Verge, Laura Nestler, who The Verge reported is Go_JasonWaterfalls, claimed that Reddit has been talking about making this change since at least 2021. The protests, she said, were a wake-up call that moderators’ ability to turn subreddits private “could be used to harm Reddit at scale. The protests “accelerated” the policy change, per Nestler.
The announcement on r/modnews reads:
… the ability to instantly change Community Type settings has been used to break the platform and violate our rules. We have a responsibility to protect Reddit and ensure its long-term health, and we cannot allow actions that deliberately cause harm.
After shutting down a tactic for responding to unfavorable Reddit policy changes, Go_JasonWaterfalls claimed that Reddit still wants to hear from users.
“Community Type settings have historically been used to protest Reddit’s decisions,” they wrote.
“While we are making this change to ensure users’ expectations regarding a community’s access do not suddenly change, protest is allowed on Reddit. We want to hear from you when you think Reddit is making decisions that are not in your communities’ best interests. But if a protest crosses the line into harming redditors and Reddit, we’ll step in.”
Last year’s user protests illustrated how dependent Reddit is on unpaid moderators and user-generated content. At times, things turned ugly, pitting Reddit executives against long-time users (Reddit CEO Steve Huffman infamously called Reddit mods “landed gentry,” something that some were quick to remind Go_JasonWaterfalls of) and reportedly worrying Reddit employees.
Although the protests failed to reverse Reddit’s prohibitive API fees or to save most third-party apps, it succeeded in getting users’ concerns heard and even crashed Reddit for three hours. Further, NFSW protests temporarily prevented Reddit from selling ads on some subreddits. Since going public this year and amid a push to reach profitability, Reddit has been more focused on ads than ever. (Most of Reddit’s money comes from ads.)
Reddit’s Nestler told The Verge that the new policy was reviewed by Reddit’s Mod Council. Reddit is confident that it won’t lose mods because of the change, she said.
“Demotes us all to janitors”
The news marks another broad policy change that is likely to upset users and make Reddit seem unwilling to give into user feedback, despite Go_JasonWaterfalls saying that “protest is allowed on Reddit.” For example, in response, Reddit user CouncilOfStrongs said:
Don’t lie to us, please.
Something that you can ignore because it has no impact cannot be a protest, and no matter what you say that is obviously the one and only point of you doing this – to block moderators from being able to hold Reddit accountable in even the smallest way for malicious, irresponsible, bad faith changes that they make.
Reddit user belisaurius, who is listed as a mod for several active subreddits, including a 336,000-member one for the Philadelphia Eagles NFL team, said that the policy change “removes moderators from any position of central responsibility and demotes us all to janitors.”
As Reddit continues seeking profits and seemingly more control over a platform built around free user-generated content and moderation, users will have to either accept that Reddit is changing or leave the platform.
Advance Publications, which owns Ars Technica parent Condé Nast, is the largest shareholder in Reddit.
Given the flood of photorealistic AI-generated images washing over social media networks like X and Facebook these days, we’re seemingly entering a new age of media skepticism: the era of what I’m calling “deep doubt.” While questioning the authenticity of digital content stretches back decades—and analog media long before that—easy access to tools that generate convincing fake content has led to a new wave of liars using AI-generated scenes to deny real documentary evidence. Along the way, people’s existing skepticism toward online content from strangers may be reaching new heights.
Deep doubt is skepticism of real media that stems from the existence of generative AI. This manifests as broad public skepticism toward the veracity of media artifacts, which in turn leads to a notable consequence: People can now more credibly claim that real events did not happen and suggest that documentary evidence was fabricated using AI tools.
The concept behind “deep doubt” isn’t new, but its real-world impact is becoming increasingly apparent. Since the term “deepfake” first surfaced in 2017, we’ve seen a rapid evolution in AI-generated media capabilities. This has led to recent examples of deep doubt in action, such as conspiracy theorists claiming that President Joe Biden has been replaced by an AI-powered hologram and former President Donald Trump’s baseless accusation in August that Vice President Kamala Harris used AI to fake crowd sizes at her rallies. And on Friday, Trump cried “AI” again at a photo of him with E. Jean Carroll, a writer who successfully sued him for sexual assault, that contradicts his claim of never having met her.
Legal scholars Danielle K. Citron and Robert Chesney foresaw this trend years ago, coining the term “liar’s dividend” in 2019 to describe the consequence of deep doubt: deepfakes being weaponized by liars to discredit authentic evidence. But whereas deep doubt was once a hypothetical academic concept, it is now our reality.
The rise of deepfakes, the persistence of doubt
Doubt has been a political weapon since ancient times. This modern AI-fueled manifestation is just the latest evolution of a tactic where the seeds of uncertainty are sown to manipulate public opinion, undermine opponents, and hide the truth. AI is the newest refuge of liars.
Over the past decade, the rise of deep-learning technology has made it increasingly easy for people to craft false or modified pictures, audio, text, or video that appear to be non-synthesized organic media. Deepfakes were named after a Reddit user going by the name “deepfakes,” who shared AI-faked pornography on the service, swapping out the face of a performer with the face of someone else who wasn’t part of the original recording.
In the 20th century, one could argue that a certain part of our trust in media produced by others was a result of how expensive and time-consuming it was, and the skill it required, to produce documentary images and films. Even texts required a great deal of time and skill. As the deep doubt phenomenon grows, it will erode this 20th-century media sensibility. But it will also affect our political discourse, legal systems, and even our shared understanding of historical events that rely on that media to function—we rely on others to get information about the world. From photorealistic images to pitch-perfect voice clones, our perception of what we consider “truth” in media will need recalibration.
In April, a panel of federal judges highlighted the potential for AI-generated deepfakes to not only introduce fake evidence but also cast doubt on genuine evidence in court trials. The concern emerged during a meeting of the US Judicial Conference’s Advisory Committee on Evidence Rules, where the judges discussed the challenges of authenticating digital evidence in an era of increasingly sophisticated AI technology. Ultimately, the judges decided to postpone making any AI-related rule changes, but their meeting shows that the subject is already being considered by American judges.
Enlarge/ Still of Procreate CEO James Cuda from a video posted to X.
On Sunday, Procreate announced that it will not incorporate generative AI into its popular iPad illustration app. The decision comes in response to an ongoing backlash from some parts of the art community, which has raised concerns about the ethical implications and potential consequences of AI use in creative industries.
“Generative AI is ripping the humanity out of things,” Procreate wrote on its website. “Built on a foundation of theft, the technology is steering us toward a barren future.”
In a video posted on X, Procreate CEO James Cuda laid out his company’s stance, saying, “We’re not going to be introducing any generative AI into our products. I don’t like what’s happening to the industry, and I don’t like what it’s doing to artists.”
Cuda’s sentiment echoes the fears of some digital artists who feel that AI image synthesis models, often trained on content without consent or compensation, threaten their livelihood and the authenticity of creative work. That’s not a universal sentiment among artists, but AI image synthesis is often a deeply divisive subject on social media, with some taking starkly polarized positions on the topic.
Procreate CEO James Cuda lays out his argument against generative AI in a video posted to X.
Cuda’s video plays on that polarization with clear messaging against generative AI. His statement reads as follows:
You’ve been asking us about AI. You know, I usually don’t like getting in front of the camera. I prefer that our products speak for themselves. I really fucking hate generative AI. I don’t like what’s happening in the industry and I don’t like what it’s doing to artists. We’re not going to be introducing any generative AI into out products. Our products are always designed and developed with the idea that a human will be creating something. You know, we don’t exactly know where this story’s gonna go or how it ends, but we believe that we’re on the right path supporting human creativity.
The debate over generative AI has intensified among some outspoken artists as more companies integrate these tools into their products. Dominant illustration software provider Adobe has tried to avoid ethical concerns by training its Firefly AI models on licensed or public domain content, but some artists have remained skeptical. Adobe Photoshop currently includes a “Generative Fill” feature powered by image synthesis, and the company is also experimenting with video synthesis models.
The backlash against image and video synthesis is not solely focused on creative app developers. Hardware manufacturer Wacom and game publisher Wizards of the Coast have faced criticism and issued apologies after using AI-generated content in their products. Toys “R” Us also faced a negative reaction after debuting an AI-generated commercial. Companies are still grappling with balancing the potential benefits of generative AI with the ethical concerns it raises.
Artists and critics react
Enlarge/ A partial screenshot of Procreate’s AI website captured on August 20, 2024.
So far, Procreate’s anti-AI announcement has been met with a largely positive reaction in replies to its social media post. In a widely liked comment, artist Freya Holmér wrote on X, “this is very appreciated, thank you.”
Some of the more outspoken opponents of image synthesis also replied favorably to Procreate’s move. Karla Ortiz, who is a plaintiff in a lawsuit against AI image-generator companies, replied to Procreate’s video on X, “Whatever you need at any time, know I’m here!! Artists support each other, and also support those who allow us to continue doing what we do! So thank you for all you all do and so excited to see what the team does next!”
Artist RJ Palmer, who stoked the first major wave of AI art backlash with a viral tweet in 2022, also replied to Cuda’s video statement, saying, “Now thats the way to send a message. Now if only you guys could get a full power competitor to [Photoshop] on desktop with plugin support. Until someone can build a real competitor to high level [Photoshop] use, I’m stuck with it.”
A few pro-AI users also replied to the X post, including AI-augmented artist Claire Silver, who uses generative AI as an accessibility tool. She wrote on X, “Most of my early work is made with a combination of AI and Procreate. 7 years ago, before text to image was really even a thing. I loved procreate because it used tech to boost accessibility. Like AI, it augmented trad skill to allow more people to create. No rules, only tools.”
Since AI image synthesis continues to be a highly charged subject among some artists, reaffirming support for human-centric creativity could be an effective differentiated marketing move for Procreate, which currently plays underdog to creativity app giant Adobe. While some may prefer to use AI tools, in an (ideally healthy) app ecosystem with personal choice in illustration apps, people can follow their conscience.
Procreate’s anti-AI stance is slightly risky because it might also polarize part of its user base—and if the company changes its mind about including generative AI in the future, it will have to walk back its pledge. But for now, Procreate is confident in its decision: “In this technological rush, this might make us an exception or seem at risk of being left behind,” Procreate wrote. “But we see this road less traveled as the more exciting and fruitful one for our community.”
Enlarge/ Still from a Chinese social media video featuring two people imitating imperfect AI-generated video outputs.
It’s no secret that despite significant investment from companies like OpenAI and Runway, AI-generated videos still struggle to achieve convincing realism at times. Some of the most amusing fails end up on social media, which has led to a new response trend on Chinese social media platforms TikTok and Bilibili where users create videos that mock the imperfections of AI-generated content. The trend has since spread to X (formerly Twitter) in the US, where users have been sharing the humorous parodies.
In particular, the videos seem to parody image synthesis videos where subjects seamlessly morph into other people or objects in unexpected and physically impossible ways. Chinese social media replicate these unusual visual non-sequiturs without special effects by positioning their bodies in unusual ways as new and unexpected objects appear on-camera from out of frame.
This exaggerated mimicry has struck a chord with viewers on X, who find the parodies entertaining. User @theGioM shared one video, seen above. “This is high-level performance arts,” wrote one X user. “art is imitating life imitating ai, almost shedded a tear.” Another commented, “I feel like it still needs a motorcycle the turns into a speedboat and takes off into the sky. Other than that, excellent work.”
An example Chinese social media video featuring two people imitating imperfect AI-generated video outputs.
While these parodies poke fun at current limitations, tech companies are actively attempting to overcome them with more training data (examples analyzed by AI models that teach them how to create videos) and computational training time. OpenAI unveiled Sora in February, capable of creating realistic scenes if they closely match examples found in training data. Runway’s Gen-3 Alpha suffers a similar fate: It can create brief clips of convincing video within a narrow set of constraints. This means that generated videos of situations outside the dataset often end up hilariously weird.
An AI-generated video that features impossibly-morphing people and animals. Social media users are imitating this style.
It’s worth noting that actor Will Smith beat Chinese social media users to this trend in February by poking fun at a horrific 2023 viral AI-generated video that attempted to depict him eating spaghetti. That may also bring back memories of other amusing video synthesis failures, such as May 2023’s AI-generated beer commercial, created using Runway’s earlier Gen-2 model.
An example Chinese social media video featuring two people imitating imperfect AI-generated video outputs.
While imitating imperfect AI videos may seem strange to some, people regularly make money pretending to be NPCs (non-player characters—a term for computer-controlled video game characters) on TikTok.
For anyone alive during the 1980s, witnessing this fast-changing and often bizarre new media world can cause some cognitive whiplash, but the world is a weird place full of wonders beyond the imagination. “There are more things in Heaven and Earth, Horatio, than are dreamt of in your philosophy,” as Hamlet once famously said. “Including people pretending to be video game characters and flawed video synthesis outputs.”
