In an episode called "Joan is Awful" from the new season of Black Mirror, a world is depicted where a streaming service called StreamBerry produces deepfaked, synthetically generated TV shows centered around the lives of its users. This intriguing portrayal offers a glimpse into a possible dystopian future, one that closely aligns with the direction we are potentially heading, where companies prioritize user engagement over their well-being, mental health and privacy. This got me thinking, how far are we from a platform that generates content on its own and glues the audience to the screen even more so than now?
How it might look like
A screen filled with content that was generated only for you. You keep scrolling through the never-ending flow of captivating videos and images. Every now and then you stop for a few seconds to look at a deepfaked panda hugging a tree and then start scrolling again, that will be the positive reinforcement for the content-generating AI to generate more pandas or trees or maybe hugging. Slowly through your interactions with the app, it gets to know what you like, know what you dislike, it gets to know you.
These methods are already deployed somewhat in the current social media platforms. Platforms already learn user preferences through their interactions with the app. But what will be new is that the platforms will not rely on humans to generate content for them anymore. When the platform can generate content by itself, it becomes self-sufficient. Diffusion models like Stable diffusion and Midjourney can already generate images in a few seconds now. Soon these models can generate images and even videos in under a second. That breakthrough will enable these platforms to generate content on the fly. With each scroll new freshly generated content for your eyes and ears, tailored just for you.
How it will work
The thing about these diffusion models is that even though they can generate incredible images and videos, the prompt always comes from humans. So human initiates the process of generation. For these self-sufficient content generation platforms the prompt generation must be automated. The prompt must also come from an AI, a language model, the ones you interact with when you talk to ChatGPT or Bing. Given the user preference data and various types of metadata, a language model will take it as input and will generate a prompt or maybe a series of prompts that will then be used by the diffusion model to generate the contents for the For You page. Let's call this language model the Prompt model. This prompt model can also be used as a reinforcement learning agent which will try to generate prompts to maximize its reward aka user engagement. Maybe even using collaborative filtering these prompts, generated for one user can be propagated to other people's For You page with similar tastes.
Today recommendation algorithms ask the question, what content or content creator can increase the engagement of a certain user? Soon the question will be, what prompts will generate the content that increases the engagement of a certain user?
Content creators vs Prompt creators
Not all the prompts will be generated by the platform's AI of course. Users can also create their prompts and generate content of their own. Maybe the generation services will be different from the platforms it is posted in but either way, there will be competition between these groups on who can grab more attention from the users. The scary thing about the Prompt model and the whole system is that it will never get discouraged. When your street food vlogging page doesn't get too many views or likes you might think it's not worth it, you might stop, or your ego might get hurt by critical comments or maybe the lack of comments. Machines don't have ego, all those negative comments will be used as fuel to generate even better content. One other thing is that whatever the human creators create, it's all going to be used to train the diffusion models anyway. Unless there are some laws put in place to restrict the platforms from using user content as training data.
The value of human creators
If this ever becomes a reality I like to think that the value of human creators will increase. In the sea of never-ending content, authenticity will become more important than surface-level beauty. The fact that another fellow human has created this content will be of significant value to users. Just like a handmade vase is more valuable than a vase made in a factory.
Or maybe the opposite will be true. Maybe the fact that a particular video regardless of who or what made it, was made only for you will be of value. Maybe exclusivity will be more important than originality and authenticity. That will be a sad reality one I don't want to see realize.
How far is it
We have seen massive strides in the space of diffusion models with Stable Diffusion and Midjourney creating breathtaking images from a few lines of text. But art can only keep a user engaged for so long. What we consume most on social media are memes or photographs taken from real-world events. Photographs cannot be replicated by AI as they will lose their authenticity. Memes however can be generated with these models but the humor must come from the Prompt model as well as the text that goes in that image. Memes are, most of the time, based on recent events so the Prompt model must keep up to date with what is happening in the world which is a hard task in and of itself. Moreover, embedding text in the generated image has been very difficult for diffusion models although some improvements have been made by architectures like DeepFloyd that solve the problem.
Video generation however is still in its infancy at the time of this writing. The video generation capabilities are amazing but not lifelike as shown in the Black Mirror episode. Also, generating video will be a time-consuming task (unless models or GPUs get faster), which is unacceptable in an age where users have very little patience and cannot stand a loading screen.
So it seems like a social media platform like this is quite far away but not at all impossible to create.