As AI improves, what does it mean for user-generated content?

The rise of the creator economy was one of the most disruptive forces to emerge from the internet, paving the way for independent writers, artists, musicians, podcasters, YouTubers and social media influencers to connect with audiences directly and earn money from doing so. 

Creators have flocked to platforms such as Facebook, Instagram, Vimeo, Substack, TikTok and more, where they can not only create but also publish and share their user-generated content. Social media enables individuals to become self-publishers and independent producers of content, disrupting existing business models and enabling an entire generation of creative minds to establish their own path to success. 

Until recently, the creativity such individuals express was always thought to be a uniquely human quality and therefore invulnerable to disruption by advancing technology. However, the rise of generative AI, which comes so soon after the emergence of the creator economy, threatens to disrupt this nascent industry and significantly alter the way new content is produced. With generative AI models, anyone can churn out paragraphs of text, lines of software code, high quality images, audio, video and more, using simple prompts. 

How does AI aid with user-generated content?

Generative AI burst into the public consciousness with the arrival of ChatGPT in late 2022, taking the internet by storm, and since then tech companies have rushed to create all manner of consumer-friendly applications that can aid in content creation. 

For instance there’s ChatGPT itself, which is all about text-generation, capable of writing blog posts, essays, marketing copy, email pitches, documents and more, based on a simple prompt where the user tells it what to write. 

More impressive forms of content generation include image generating models such as Midjourney, which can create dramatic pictures based on user’s ideas of what they want to see, and there are now even video generators, such as OpenAI’s Sora, Google DeepMind’s Veo and Runway that can do the same. 

Generative AI is also having an impact on video game content generation. Take the novel technology developed by AMGI Studios for its hit Web3 game My Pet Hooligan, which uses proprietary motion capture and AI algorithms to capture the gamer’s facial expressions and replicate them on their in-game avatars. It further uses generative AI to provide each user character (which is a unique NFT) with its own distinctive personality that users can learn about through a chat interface. 

Other ways people use generative AI to enhance creativity include Buzzfeed’s personalized content creation tools, which enable users to quickly create customized quizzes tailored to each individual, and its generative AI recipe creator, which can serve up ideas for meals based on whatever the user has in the fridge. 

Three ways this can go

In the eyes of some, AI-generated content has emerged as a major threat to user-generated content, but not everyone sees it that way. It’s unclear what kind of impact generative AI will ultimately have on the creator economy, but there are a number of possible scenarios that may unfold. 

Scenario 1: AI enhances creativity

In the first scenario, it’s possible to imagine a world in which there’s an explosion of AI-assisted innovation, in which content creators themselves adopt AI to improve their performance and productivity. For instance, designers can use AI to quickly generate basic ideas and outlines, before using their human expertise to fine-tune those creations, be it a logo or a product design or something else. Rather than replace designers entirely, generative AI simply becomes a tool that they use to improve their output and get more work done. 

An example of this is GitHub’s coding assistant Copilot, which is a generative AI tool that acts as a kind of programming assistant, helping developers to generate code. It doesn’t replace their role entirely, but simply assists them in generating code snippets – such as the lines of code required to program an app to perform standard actions. But the developer is the one who oversees this and uses his creativity to design all of the intricacies of the app. 

AMGI’s in-game content generation tools are another example of how AI augments human creativity, creating unique in-game characters and situations that are ultimately based on the user’s actions. 

Such a scenario isn’t a threat to creative workers and user-generated content. Rather than taking people’s jobs, AI will simply support the people who do those jobs and make them better at it. They’ll be able to work faster and more efficiently, getting more work done in shorter time frames, spending more of their time prompting the AI tools they use and editing their outputs. It will enable creative projects to move forward much faster, accelerating innovation. 

Scenario 2: AI monopolises creativity 

A more dystopian scenario is the one where algorithmic models leverage their unfair advantage to totally dominate the world of content creation. It’s a future where human designers, writers, coders and perhaps even highly skilled professionals like physicists are drowned out by AI models that can not only work faster, but at much lower costs than humans can.

From a business perspective, if they can replace costly human creators with cheap and cheerful AI, that’s great, translating to more profitability. But there are concerns, not only for the humans that lose their livelihoods, but also on the impact of creativity itself. 

As impressive as generative AI-created content sometimes is, the outputs of these algorithms are all based on existing content – namely the data they’re trained on. Most AI models have a habit of regurgitating similar content. Take an AI writer that always seems to write prose in the same, instantly recognizable and impersonal way, or AI image generators that constantly churn images with the same aesthetic. 

An even more alarming example of this is the AI music generators Suno and Uncharted Labs, whose tools are said to have been trained on millions of music videos posted on YouTube. Musicians represented by the Recording Industry Association of America recently filed lawsuits against those companies, accusing them of copyright infringement. Their evidence? Numerous examples of supposedly original songs that sound awfully familiar to existing ones created by humans. 

For instance, the lawsuit describes a song generated using Suno, called “Deep down in Louisiana close to New Orle” which seems to mirror the lyrics and style of Chuck Berry’s “Johnny B. Goode.” It also highlights a second track, “Prancing Queen” that seems to be a blatant rip off of the ABBA hit “Dancing Queen.”

These examples raise questions over AI’s ability to create truly original content. If AI were to monopolise creativity, it could result in true innovation and creativity screeching to a halt, leading to a future that’s sterile and bland. 

Scenario 3: Human creativity stands out

Given AI’s lack of true authenticity and originality, a third possible way this could play out is that there is a kind of backlash against it. With consumers being overwhelmed by a sea of mundane, synthetic imagery and prose, those with an eye for flair will likely be able to identify true, human creativity and pay a premium for that content. After all, humans have always shown a preference for true originality, and such a scenario could well play into the hands of the most talented content creators. 

It’s a future where being human gives creators a competitive edge over their algorithmic rivals, with their unparalleled ability to come up with truly original ideas setting their work apart. Human culture, fashions and trends seem to evolve faster than generative AI models are created, and that means that the most original thinkers will always be one step ahead. It’s a more reassuring future where humans will continue to create and be rewarded for their work, and where machines will only ever be able to copy and iterate on existing ideas.  

This is perhaps the most likely scenario and, reassuringly, it means there will always be a need for humans in the mix. Humans, after all, are characterised by their creativity – everything that exists in the modern world today was created by someone, whether it’s the shoes on your feet, the device you’re reading this article with, or the language you speak. They’re all human creations, inspired by original ideas rooted in the human brain, and humans – especially those who find AI can do their jobs for them – will have more time to sit and think and potentially come up with even better ideas than the ones we’ve had so far.