What is a Deepfake
The term “deepfake” is a blend of “deep learning” a form of Artificial Intelligence and
“fake.” A deepfake is synthetic media (video, image, or audio) that has been digitally manipulated or entirely generated using sophisticated AI technology to convincingly show a person appearing to say or do something they never actually said
or did.
What is AI Slop
The term “AI slop” refers to digital content—such as text, images, videos, or audio—that has been created using generative artificial intelligence, and is characterized by a lack of effort, quality, or deeper meaning, often produced in an
overwhelming volume.
It has a pejorative connotation, similar to the way “spam” is used to describe unwanted, low-value content.
AI slop is viewed as an “environmental pollution” problem for the internet, where the costs of mass production are nearly zero, but the cost to the information ecosystem is immense.
AI slop contributes significantly to the general erosion of trust in the internet by blurring the line between human-created authenticity, machine-generated noise and fraud.
Lies! It’s ALL Damn Lies!
AI slop and deepfakes are fundamentally similar because both are forms of synthetic media created by the same powerful generative AI models (text-to-image/video). They both contribute to a widespread erosion of trust online by blurring the
line between human-made content and digital fabrication. While a deepfake is a targeted, high-quality forgery designed to maliciously deceive (e.g., faking a political speech), AI slop is low-quality content mass-produced out of indifference for accuracy or
effort, often just for clicks.
Nevertheless, both types of content flood the digital ecosystem, making it increasingly difficult for users to distinguish authentic, verified information from machine-generated noise.
Key Characteristics of AI Slop
- Low Quality/Minimal Effort: The content is often generated quickly, with little to no human review for accuracy, coherence, or originality.
- High Volume/Repetitive: It’s mass-produced to flood platforms, often prioritizing quantity and speed over substance.
- Driven by Profit: It is frequently created for “content farming,” designed to manipulate search engine optimization (SEO) or social media algorithms to generate ad revenue or engagement.
Examples of AI Slop
- Images: Surreal or bizarre images (like the viral “Shrimp Jesus”), low-quality or inconsistent stock photos, or social media posts featuring images with subtle flaws (like extra fingers or garbled text).
- Text: SEO-optimized articles that are vague, repetitive, or inaccurate; mass-produced low-effort blog posts; or entirely AI-written books.
- Social Media: Fake social media profiles, or sensational, low-effort videos and posts designed purely for clickbait and engagement.
The general concern is that the rapid proliferation of AI slop is polluting the internet, making it harder to find high-quality, authentic human-created content and blurring the lines between real and fabricated information.
The contribution to mistrust is not primarily about malicious deepfakes (though that is a related trust problem); it’s about the sheer volume and mediocrity of content that makes the web unreliable.
AI Slop Drives Mistrust
Blurring Reality and Fabricating “Truth”
- The Problem of “Careless Speech”: AI models are built to generate text that sounds plausible and authoritative, not necessarily text that is truthful. AI slop is often created with indifference to accuracy, meaning it presents subtle inaccuracies
or outright falsehoods with complete confidence. - Viral Misinformation: Because AI can produce content so cheaply and quickly, it allows for the mass creation and distribution of misleading content (like fake images during a natural disaster or absurd celebrity claims) that can easily
go viral before being fact-checked. - Normalizing Fake Content: When users are constantly exposed to AI-generated images, videos, and articles that are “just good enough,” they become desensitized. The constant exposure makes the audience question the origin of
all digital content, leading to a state where nothing can be fully trusted until proven otherwise.
Undermining Authority and Credibility
- Degrading Search Results: AI slop sites, designed only to manipulate SEO, push genuinely high-quality, researched, and expert human content down the rankings. When you search for vital information and the top results are vague, repetitive,
or inaccurate, you lose faith in the search engine’s ability to act as a reliable guide to the web. - The “We Don’t Care” Signal: When a brand, news site, or business publishes content that is clearly generic, full of buzzwords, or poorly edited because it was quickly spun up by AI, it sends a message of complacency and low effort. This
DILLIGAF attitude damages brand trust and suggests the company doesn’t care enough to communicate with intention. - Fake Reviews and Social Proof: AI slop is used to generate fake reviews and create inauthentic social media engagement (bots commenting “great photography” on a thousand AI images). This corrupts the systems of social proof—like ratings,
likes, and comments—that people rely on to judge quality, making it impossible to trust whether a product or a trend is genuinely popular.
The “Enshittification” of the Internet
“Enshittification” is a term coined by writer and activist
Cory Doctorow. The widespread adoption of AI slop is accelerating what some critics call the enshittification of digital platforms—the degradation of services as platforms prioritize profit (through mass-produced, algorithm-friendly content) over user
value.
- As the internet fills with more and more machine-generated “junk,” human creators struggle to be seen, and the entire digital environment becomes less useful and more frustrating.
- This cycle reinforces the idea that the internet is increasingly becoming an unpleasant, unreliable space designed to farm engagement rather than to connect, inform, or entertain in a meaningful way.
The core of the mistrust is the inability to answer two simple questions with confidence: “Did a real person make this?” and “Is this true?”
Protect Yourself: Digital Literacy Matters
Protecting yourself from AI slop and deepfakes requires a dual approach: critical consumption (protection) and responsible behavior (not spreading). The core defense is applying strong media literacy skills to everything you see online.
Critical Consumption (Protection)
Protecting yourself from the proliferation of AI slop and deepfakes requires developing strong habits of critical consumption. The core practice is to refuse to blindly trust what you see and to develop systematic ways of verifying authenticity.
This involves checking the source—prioritizing content from established, fact-checked news outlets over anonymous or clickbait accounts that have a financial motive to spread low-effort content.
You must inspect the media itself by slowing down and looking closely for tell-tale AI errors, such as distorted hands, missing jewelry, or unnatural movements in videos.
Source Verification:
- Check the source, not just the content. Prioritize content from established, reputable news and expert sources.
- Trace the origin. Use reverse image/video search tools (like Google or TinEye) to find the original source and context of the media.
Inspecting Media and Spotting the “Tells”:
Slow down and inspect closely. Look for visual artifacts that AI generators frequently get wrong.
Look for anomalies
- Photos: like distorted hands, extra or missing fingers, melted or smudged background details, unnatural shadows, or inconsistent jewelry.
- Videos: For videos, watch for robotic, jerky, or unnatural body movements, and any lip-syncing issues.
Fact-Checking and Skepticism:
- Assume it could be fake. If a piece of content elicits a strong emotional reaction (shock, anger, or awe), immediately pause and assume it is manipulation bait.
- Verify claims independently. Cross-check the story with multiple, credible, independent news organizations before accepting or sharing it.
How to Not Spread AI Slop (Responsible Behavior)
Your personal sharing habits are the most powerful tool against the spread of synthetic content:
- Stop the Emotional Share: If a piece of content—image, video, or headline—elicits an immediate, intense emotional response (outrage, shock, fear, or awe), PAUSE. Content creators use emotional triggers to bypass your critical thinking and
get you to share instantly. - Question the Motive: Before clicking ‘Share,’ ask: “Who benefits if I share this?” If the answer is an anonymous clickbait site, an algorithmic content farm, or a source pushing a strong, unverified agenda, do not share.
- Refuse to Amplify Slop and Deepfakes: Do not engage with or comment on clearly low-quality, AI-generated content (like repetitive, nonsensical articles or bizarre images). Algorithms reward all engagement, so even a comment saying “This
is fake” helps the slop gain visibility. - Add Context When Necessary: If you absolutely must share a piece of content that looks potentially fake (e.g., to discuss a trend), clearly label it yourself (e.g., “Warning: This appears to be AI-generated/unconfirmed”).
By adopting these habits, you move from being a passive consumer to an active filter and a digitally literate consumer engaged in protecting yourself and others from misinformation and lies. These are the most effective way to protect the
integrity of the digital ecosystem.
