Can we stop creating AI slop?

A photo of real people in an in-person workshop!

AI Slop and Environmental Impact

John Oliver's latest episode brilliantly exposes the reality of "AI slop" – the cheap, mass-produced AI-generated content flooding our social media feeds. From bizarre shrimp Jesus images to fake bread horses, this content isn't just strange – it's actively degrading our online platforms and fueling dangerous misinformation.

As someone who's been a longtime fan of John Oliver's meticulously researched journalism, I appreciate how he presents evidence-backed analysis. His show demonstrates the real-world consequences of AI slop: confusing first responders during disasters with fake victim images, stealing artists' work without compensation, and creating the "liar's dividend" where genuine evidence can be dismissed as AI-generated.

What about the critical aspect we need to discuss: the environmental cost of this digital pollution?

The numbers are astonishing. In 2022 alone, Google, Microsoft, and Meta consumed an estimated 580 billion gallons of water – enough to meet the annual needs of 15 million households – just to cool their data centers and AI servers. For every kilowatt hour of energy consumed, data centers require 2 liters of water for cooling, with 80% of that water lost to evaporation and never returned to its source.

In Arizona, data centers are withdrawing massive amounts of water in areas where farmers have had to fallow fields and families have gone without tap water for most of 2023. In Oregon, Google's data centers now account for 25% of water use in The Dalles, tripling their consumption between 2017 and 2022.

Here's my commitment: You will never get AI slop from me. All my videos will always feature me – real, authentic, human-created content. I refuse to contribute to this waste of precious resources by demonstrating AI tools that create meaningless content. When many YouTubers create AI slop while demonstrating tools, they're participating in a complete waste of resources that could power 120 homes for a year (the energy cost of training just one GPT-3 model).

When I demonstrate tools, I'm committed to creating something useful and practical – content that serves a real purpose rather than adding to the digital pollution choking our platforms and draining our planet's resources.

We need to be more conscious about the true cost of our digital choices. Every piece of AI-generated content has a real environmental footprint, and it's time we started treating our digital consumption with the same responsibility we apply to our physical consumption.

Watch video here: https://www.youtube.com/watch?v=TWpg1RmzAbc

Summary of the video:

John Oliver's AI Slop Analysis

Key Definition

AI Slop: Cheap, often bizarre, mass-produced AI-generated content designed to flood social media for engagement and profit.

Examples Presented

- Viral cat video

- Shrimp Jesus

- Bread horse

- Fake images that are incredibly popular and often mistaken for reality

Major Problems Identified

1. Platform Degradation

- Pinterest user finds app "unusable" due to overwhelming fake AI images

- Quality of online platforms deteriorating

2. Misinformation Spread

- Entire YouTube channels creating fake news about politicians and celebrities

- Millions of people believe this false content

- Real-world consequences: confusing first responders during disasters with fake victim images

3. Art Theft

- AI slop creators steal and repurpose real artists' work without compensation or credit

- Example: chainsaw sculptor Michael Jones's work being copied

4. "Liar's Dividend"

- Existence of deepfakes allows bad actors to dismiss genuine evidence as AI-generated

- Undermines trust in authentic content

Business Model

- Monetizing viral content through platform payouts

- Affiliate marketing schemes

Current Solutions

- Platforms starting to label AI content

- Efforts often insufficient

Li, P., Yang, J., Islam, M. A., & Ren, S. (2025). Making AI Less 'Thirsty': Uncovering and Addressing the Secret Water Footprint of AI Models. arXiv:2304.03271. https://arxiv.org/abs/2304.03271

Murray, B., & DiFelice, M. (2025, April 9). Artificial Intelligence: Big Tech's Big Threat to Our Water and Climate. Food & Water Watch. https://www.foodandwaterwatch.org/2025/04/09/artificial-intelligence-water-climate/

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