ΑΙhub.org
 

Dataset reveals how Reddit communities are adapting to AI


by
25 April 2025



share this:

A watercolour illustration in two strong colours showing the silhouettes of four people, two of whom have dogs on leads. They all cast shadows, and vary between realistic representations and those formed by representations of algorithms, data points or networks. The people and their data become indistinguishable form each other.Jamillah Knowles / Data People / Licenced by CC-BY 4.0

By Grace Stanley

Researchers at Cornell Tech have released a dataset extracted from more than 300,000 public Reddit communities, and a report detailing how Reddit communities are changing their policies to address a surge in AI-generated content.

The team collected metadata and community rules from the online communities, known as subreddits, during two periods in July 2023 and November 2024. The researchers will present a paper with their findings at the Association of Computing Machinery’s CHI conference on Human Factors in Computing Systems being held April 26 to May 1 in Yokohama, Japan.

One of the researchers’ most striking discoveries is the rapid increase in subreddits with rules governing AI use. According to the research, the number of subreddits with AI rules more than doubled in 16 months, from July 2023 to November 2024.

“This is important because it demonstrates that AI concern is spreading in these communities. It raises the question of whether or not the communities have the tools they need to effectively and equitably enforce these policies,” said Travis Lloyd, a doctoral student at Cornell Tech and one of the researchers who initiated the project in 2023.

The study found that AI rules are most common in subreddits focused on art and celebrity topics. These communities often share visual content, and their rules frequently address concerns about the quality and authenticity of AI-generated images, audio and video. Larger subreddits were also significantly more likely to have these rules, reflecting growing concerns about AI among communities with larger user bases.

“This paper uses community rules to provide a first view of how our online communities are contending with the potential widespread disruption that is brought by generative AI,” said co-author Mor Naaman, professor at the Jacobs Technion-Cornell Institute at Cornell Tech, and of information science in the Cornell Ann S. Bowers College of Computing and Information Science. “Looking at actions of moderators and rule changes gave us a unique way to reflect on how different subreddits are impacted and are resisting, or not, the use of AI in their communities.”

As generative AI evolves, the researchers urge platform designers to prioritize the community concerns about quality and authenticity exposed in the data. The study also highlights the importance of “context-sensitive” platform design choices, which consider how different types of communities take varied approaches to regulating AI use.

For example, the research suggests that larger communities may be more inclined to use formal, explicit rules to maintain content quality and govern AI use. In contrast, closer-knit, more personal communities may rely on informal methods, such as social norms and expectations.

“The most successful platforms will be those that empower communities to develop and enforce their own context-sensitive norms about AI use. The most important thing is that platforms do not take a top-down approach that forces a single AI policy on all communities,” Lloyd said. “Communities need to be able to choose for themselves whether they want to allow the new technology, and platform designers should explore new moderation tools that can help communities detect the use of AI.”

By making their dataset public, the researchers aim to enable future studies that can further explore online community self-governance and the impact of AI on online interactions.




Cornell University




            AIhub is supported by:



Related posts :



AIhub interview highlights 2025

  22 Dec 2025
Join us for a look back at some of the interviews we've conducted with members of the AI community.

Identifying patterns in insect scents using machine learning

  19 Dec 2025
Scientists will use machine learning to predict what types of molecules interact with insect olfactory receptors.

2025 AAAI / ACM SIGAI Doctoral Consortium interviews compilation

  18 Dec 2025
We collate our interviews with the 2025 cohort of doctoral consortium participants.

A backlash against AI imagery in ads may have begun as brands promote ‘human-made’

  17 Dec 2025
In a wave of new ads, brands like Heineken, Polaroid and Cadbury have started celebrating their work as “human-made”.

AIhub blog post highlights 2025

  16 Dec 2025
As the year draws to a close, we take a look back at some of our favourite blog posts.

Using machine learning to track greenhouse gas emissions

  15 Dec 2025
PhD candidate Julia Wąsala searches for greenhouse gas emissions in satellite data.

AAAI 2025 presidential panel on the future of AI research – video discussion on AGI

  12 Dec 2025
Watch the first in a series of video discussions from AAAI.

The Machine Ethics podcast: the AI bubble with Tim El-Sheikh

Ben chats to Tim about AI use cases, whether GenAI is even safe, the AI bubble, replacing human workers, data oligarchies and more.



 

AIhub is supported by:






 












©2025.05 - Association for the Understanding of Artificial Intelligence