AI-Generated Content, Online Platforms, and the Fight for Authenticity: Who Loses When Content Production Requires Less Effort?

By Travis Lloyd (Cornell Tech)

Online platforms are being flooded with AI-generated content, and the people who sustain them are struggling to keep up. This disruption may have significant societal consequences, as these platforms are important sites for connection, entertainment, and commerce. They were built around the assumption that content is the product of genuine human effort. But this assumption no longer holds; since the launch of ChatGPT in 2022, generative AI tools have surged in popularity, and the technology has improved enough that these tools can now generate content across various media (text, audio, image, and video) that previously required significant skill and effort. Proponents argue this is unambiguously good. But for the people who sustain online platforms, the real question is: how will such platforms function now that content production has become nearly effortless?

My research answers this question by exploring the impacts of GenAI on two groups that occupy structurally different positions within the information ecosystem: Reddit moderators, who determine what content is permitted on platforms, and recording musicians, who are among the content producers that supply it. I’ve found that both groups are being forced to adapt to the arrival of GenAI, but they lack the technical, organizational, and legal tools to do so effectively. The consequences may be grave both for the groups themselves and for everyone who turns to the platforms for authentic social interactions and genuine human creativity.

AI-Generated Content and Reddit Moderators

To understand the impacts of GenAI on content moderators, I studied the experiences of volunteer moderators on Reddit. Reddit is one of the largest and fastest-growing social media sites, with millions of daily active users and hundreds of thousands of independent online communities, known as subreddits. In these communities, users post and leave comments on others’ posts, and each community has its own purpose, values, and norms. All platforms use some form of content moderation to keep their communities functioning, but Reddit empowers individual subreddits to appoint volunteer moderators to set and enforce their own rules.

I interviewed subreddit moderators from a variety of communities, including some of the largest and most active, such as r/explainlikeimfive, r/todayilearned, and r/news. These moderators shared three main categories of concern: content quality, community social dynamics, and community governance. They worried that low-quality AI-generated content would degrade their communities, disrupt human relationships, and make their jobs as moderators more difficult as it complicates governance decisions. In response, communities are adopting rules about AI-generated content, which moderators then need to enforce. This is challenging for two reasons: AI-generated content is nearly impossible to reliably detect, and enforcement adds to the workload of already-burdened volunteers. Moderators spoke about time-consuming heuristics that they used to identify AI use, such as checking users’ past posts, although they acknowledged these were not foolproof.

To get a broader sense of how widespread these concerns were, I also analyzed community rules across Reddit. Across a sample of over 200,000 subreddits gathered in November 2024, about 1% had a community rule about AI. But among the largest 1% of communities, 17% had these rules, and this number more than doubled between July 2023 and November 2024. In addition to being more common in large communities, these rules are also more common in communities that value authenticity and creativity, like art communities.

Taken together, these findings make clear that AI-generated content is a serious disruption for online communities that value authenticity. While these communities are setting their own norms around the use of this new technology, the difficulty of detecting AI-generated content makes enforcing these norms a challenge. Communities that value authentic interaction expect their members to put genuine effort into posts. GenAI undermines this by producing content that looks effortful while requiring none. This has cheapened interaction in these online communities, and they are pushing back. Far from an isolated dynamic, something similar is happening in a very different group that also relies heavily on online platforms: recording musicians.

AI-Generated Content and Recording Musicians

GenAI poses distinct threats to the studio and production work that recording musicians do to make a living. To understand these threats, I spent a year conducting 25 interviews with musicians and members of musician advocacy organizations. These interviews revealed two main categories of economic threat to musicians’ livelihoods: lost income as AI automates music production tasks, and intensifying competition for listeners from AI-generated music.

AI tools are marketed as democratizing creativity by automating the tedious parts of music production — but these “tedious parts” are a major source of income for working musicians. These tasks include session recording, mixing and mastering recordings, and composing music to accompany visual media like film, TV, or commercials. As AI takes over these tasks, paying jobs will disappear. Notably, the advocacy responses I encountered were not focused on protecting these jobs, leaving these working musicians particularly exposed to GenAI.

Most advocacy responses instead focused on the challenge of competing for listeners with AI-generated music. This is not a hypothetical future scenario: tools like Suno and Udio already exist that take only seconds to produce full-length songs in response to text prompts. If platforms can stream AI-generated music more cheaply than human-made music, then they have every incentive to funnel listeners to AI music through recommendations and playlists. The dramatically reduced effort required to produce AI music also threatens to flood the market with synthetic songs. Even if listeners prefer human music, it may become harder and harder to find, as the volume of AI music continues to grow. Finally, some artists worried their styles could be used to create direct replacements: why listen to a recording by a favorite artist when you could listen to a never-ending supply of songs that sound like that artist?

Advocates have responded by fighting for a range of protections, starting with what they call “The Three C’s” — Credit, Consent, and Compensation — which target the AI-training process. Specifically, they want AI companies to disclose what music is in their training data, require that artists “opt in” to having their work included, and compensate those who agree to participate.

Advocates have also called for actions from sellers of AI-generated music, including adding labels or disclaimers to identify AI-generated music, or even demonetizing streams of AI music.

For musicians, what is ultimately at stake is their ability to make a living. But listeners have a stake too: those who turn to music for authenticity and human expression risk losing access to both.

Tying it all together

Both cases reveal the same underlying threat: as AI-generated content floods online platforms, the humans who sustain them are being pushed out. If moderation becomes too burdensome, volunteer-dependent communities will collapse. If musicians can’t make a living, human-made music risks becoming a luxury.

But both cases also point to a third group in the information ecosystem with something at stake: the consumers who come to these platforms seeking human connection and creative expression. As AI and human content become harder to distinguish, consumers lose the ability to find the authenticity that they are looking for. In their attempts to govern AI, both moderators and recording musicians are trying to carve out spaces for authenticity in an increasingly synthetic world. Both groups are acting on the belief that people value authenticity — and the evidence suggests they are right. Yet how exactly we empower consumers to judge authenticity is an open question. We should take cues from the advocates fighting for this authenticity: the moderators working to keep online spaces human, and the musicians fighting to keep music that way too.

Travis Lloyd

DLI Doctoral Fellow

Cornell Tech

tgl33@cornell.edu

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Cornell Tech | 2026

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