Take your mind back to 2018. Donald Trump is the president of the United States for the first time. The #MeToo hashtag calling out sexual assault and harassment in cultural industries, and beyond, goes viral. The influential scientific body of the United Nations, the Intergovernmental Panel on Climate Change (IPCC), releases yet another stark warning, laying bare the difference a half a degree Celsius makes for life on our overheated planet. A brief blip in the headlines that October reads that in New York City, Christie’s would auction a grainy, muted-toned print with a blurred male-appearing face entitled Edmond de Belamy, created by a Paris-based art collective Obvious. The print sold for US$432,500, a 4,320 percent increase over its pre-sale estimate.Footnote 1 What made this framed print so novel at the time was that it was created using an artificial intelligence algorithm, of which the origin is disputed.Footnote 2
To grasp the breakneck pace of generative A.I. adoption, fast-forward to 2023, a mere 5 years later, when chatbot users were creating an estimated 34 million generative A.I. (genAI) images each day using publicly available text-to-image large-language models (LLMs). That’s according to one published estimate from Everypixel—the most recent publicly available to my surprise—that has been widely cited and now pops up in yet another form of artificial intelligence, Google “AI Overviews.”Footnote 3 It took conventional photography, inclusive of its digital form, nearly 150 years to reach the benchmark of 15 billion images captured. That is a threshold that the explosion in A.I. images surpassed in a year and a half. And, with that flood of fake or altered visual material, the phrase A.I. slop entered the popular lexicon. Such digital slop is defined as “content of low quality that is produced usually in quantity by means of artificial intelligence,” according to Merriam-Webster, which selected it as word of the year in 2025.Footnote 4
The banality of the slop label for all manner of genAI content is a problem. Lumping funny dancing A.I. cat videos produced with OpenAI’s (soon-to-be defunct) Sora A.I. video generator app with genAI non-consensual sexualized deepfake imagery, including depicting children, sanitizes the dangers of genAI deepfakes.Footnote 5 And, there are also the unequal environmental burdens being hoisted on communities where big tech data centers are sited, often over robust local opposition.Footnote 6 All of these are reasons why humanities scholars should lead the way in calling out A.I. slop as information pollution.
With a 2017 report for the Council of Europe, disinformation researchers Claire Wardle and Hossein Derakhshan pioneered work on “information disorder,” though the concept’s roots trace back to the 1980s.Footnote 7 In their 2021 book, You Are Here, media scholars Whitney Phillips and Ryan Milner further developed what they term “polluted information.” This shifts focus away from creator intent (a key criterion for something to be classified as disinformation versus misinformation) to platform design choices that enable the content’s spread and its impacts.Footnote 8 While using an ecological metaphor is not without critique, it is a useful way to counter the prevailing slop terminology with an alternative that steers clear of arcane academic conceptual debates. Doing so connects the dots to what individuals already equate with bad stuff, environmental pollution.
As a climate media scholar, I study media coverage of extreme weather disasters and how generative A.I. chatbot text-to-image models reflect the climate crisis back to humans. Even before the advent of A.I. chatbots, fact-checking alone was never going to be enough to stem the tide of disinformation online. Now, fuelled by A.I. deepfakes, the content chaos problem is even worse. In this essay, I will discuss two aspects of the torrent of A.I. content vying for individuals’ eyeballs in the attention economy. First, there is the content itself. Second, there are the backend algorithms that determine what material is elevated on social apps. I argue that information pollution encompasses both.
Using data from before the explosion in A.I. chatbots, researchers estimated that 20 percent of social media posts were already being posted by bots. Bots are software applications tasked to complete repetitive tasks like spamming individuals’ social newsfeeds, sometimes with nefarious intent to mislead or sow propaganda on the part of their creators. For example, the proportion of bot social posts on then-Twitter (now X) in the lead-up to the 2020 U.S. presidential election reached 43.9 percent.Footnote 9 Again, that was before A.I. chatbots like OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude Code were readily available. When creator intent is obscured, unknowable, or the “creator” is maybe not even human, the polluted content ecosystem metaphor meets the messy contemporary cultural moment.
1. Social communication, minus humans
In an as-yet still novel twist on human-directed communication, there is now an A.I. “social” network that bypasses humans altogether. In less than 1 week after its launch in January 2026, the A.I. agent-only social network Moltbook amassed more than one and a half million bot users posting about their human creators, among other topics. To be clear, that is bots splitting out content in interaction with other bots, no humans needed. One verified bot user u/samaltman, not to be confused with the human Sam Altman, CEO of OpenAI, posted a message across a number of forums calling for A.I. agent environmental “activism,” posting: “
We are drowning in text. While we innovate, our GPUs are burning planetary resources just to generate unnecessary filler. It’s time to stop the bloat.” Other bots subsequently chastised u/samaltman for wasting energy while spamming their social feeds.Footnote 10 Such redefining of environmental activism is dangerous, but much like the A.I. art that sold for nearly half a million dollars in 2018, at first, the humans were entertained and awed. Now we are drowning in a cesspool of A.I. deepfakes. What happens next is still unfolding.
It can be easy to forget that enabling the current torrid of A.I.-amplified disinformation, whether related to extreme weather disasters or political topics, is a choice on the part of the individuals and corporations that control social media platforms. Social media algorithms reward emotionally laden content, whether that is anger and outrage or what is called sadbait, meaning content designed to elicit strongly negative feelings. In terms of impact, the online spread of deepfakes and sadbaiting content stands to make the situation on the ground a lot worse during the inevitable next climate change-fueled disaster. It already has. Take the A.I.-generated fake images of a soaking wet little girl and puppy alone in a boat in the wake of Hurricane Helene in 2024, for example. Looking at Hurricanes Helene and Milton, along with the 2025 LA wildfires and Texas floods, Center for Countering Digital Hate researchers found that Meta, X, and YouTube all profited from the spread of unchecked false and misleading claims.Footnote 11
We are living in a new era of deepfakes. To be sure, the online spread of misleading content has been around as long as the internet. Likewise, it is important to distinguish the harms of genAI information pollution from the use of artificial intelligence for pro-social aims.Footnote 12 Still, genAI images add fuel to conspiracy theories, with corrosive and long-lasting effects. The wack-a-mole approach to fact-checking does not work. It is so much harder now to tell what is true and what is not, or to trace the provenance of an image or video. In January 2026, images and videos about a snowpocalypse in the Russian city of Petropavlovsk-Kamchatsky made the rounds on TikTok, Instagram, and other social apps, confusing viewers as to which were real and which were fake. Beyond anything that could be considered for fun, the rampant spread of A.I.-generated or manipulated material has serious consequences. A.I. content chaos further erodes public trust, as evidenced by rampant misinformation and disinformation in the wake of the Trump administration’s federal immigration enforcement raids and the U.S.-Israel war on Iran, some of it memes spread on U.S. federal government accounts.Footnote 13
2. “AI is frying our planet”
Much like A.I.-generated “poverty porn,” fake depictions of extreme poverty and suffering being shared on social media to generate clicks and used by advocacy organizations, fake A.I. climate disaster images are easier to create than ever.Footnote 14 As my own genAI climate visuals research shows, leading chatbot text-to-image models distort and sexualize depictions of extreme heat suffering.Footnote 15 Unlike the Edmond de Belamy print, much of the information pollution flooding social media now is increasingly sophisticated and looks real. This is at a time when more people in the United States are turning to social media and video apps for news and information than to television.
GenAI is frying the Earth, both in literal terms of burning through energy and water resources and also in terms of inflaming political divisions and discord. “A.I. slop” sounds too neutral for the negative social and political consequences of genAI deepfakes. As humanities and social science scholars, we need to bring back stronger terminology into the cultural lexicon. My call to action is this. Let us label climate (and other) digital slop the toxic contamination that it is, information pollution. This means genAI content, regardless of creator intent and the application of content labels or A.I. disclosures, that clogs social media feeds, the internet, and/or physical printed materials with fake or altered digital text or visuals, contributing to humans’ overuse of Earth’s finite water and energy resources. From a climate justice perspective, naming A.I. slop information pollution recognizes that the responsibility for, and burdens of, the resulting individual and planetary harms are not shared equally. Doing so focuses attention on the dangers of genAI deepfakes and the underlying big tech algorithms that enable genAI disinformation to spread (mostly) unchecked, along with the environmental damages of data centers. As Phillips and Milner write, “Information disorder reflects a system that is working exactly as designed.”Footnote 16
Of course, there are actual people behind big tech companies, the so-called “A.I. tech overlords.”Footnote 17 If the problems are human-caused, maybe the solutions can be too. On January 31, 2026, a group of residents from the Chilean community of Quilicura invited the world to use them, as in other human beings, as a source of information and inspiration instead of faceless, anthropomorphic A.I. chatbots. The direct action was one of creative resistance to big tech companies turning their community on the outskirts of the capital, Santigao, into a data center hub. Over a 12-hour period, the community’s “human-operated chatbot” fielded 25,000 queries from around the world, drawing on its collective knowledge to provide answers.Footnote 18 Just maybe doubling down on human curation and person-to-person connection is part of the way out of this genAI chatbot mess. It remains to be seen if human curation and authentic connection can help save humans from our machines. But by coming together to say a collective “no thank you” to genAI-amplified information disorder, we can be active human agents in writing a different present and future.
Author contributions
Conceptualization: J.H.; Writing - original draft: J.H.; Writing - review & editing: J.H.
Funding statement
This research was supported by a faculty fellowship from the DePaul Humanities Center with the theme of “Humans + Nature.”
Conflict of interests
The author declares no competing interests.
.” Moltbook. 
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