The Rise Of AI-Powered Text-To-Image/Video Generators & What It Means For The Creator Economy

Source: OpenAI

Artificial Intelligence (AI) has existed in some form for decades. But it has become much more intelligent, powerful, and popular in recent years.

The Rise Of AI-Powered Text-To-Image/Video Generators

Generative AI, a form of AI that uses machine learning algorithms to create new content based on existing work, has rapidly gained traction. This has given rise to many text-to-image and text-to-video generators like OpenAI’s DALL-E 2 and Midjourney that allow people to use text to generate images and videos. To use these generators, users enter strings of text to describe the type of image or video they want. Then, the generator uses a dataset of text-matching images and videos to produce a never-before-seen image or video.

The ease of use and content quality have resulted in millions of people flocking to them. Most people use them as a means of expressing themselves, but many have also recognized their value beyond novelty.

Big Tech Takes Notice

The popularity of AI-generated visuals has caught the attention of big tech companies too. During the summer, TikTok launched the AI Greenscreen feature, which allows users to type text prompts to generate an image that can be used as a background in their videos. Meta also introduced Make-A-Video recently, which lets people create high-quality videos with text prompts. Google and Microsoft have also entered the space with Imagen Video and Image Creator, respectively.

What It Means For The Creator Ecosystem

AI-powered generators are ushering in a new era of creators, helping people become first-time creators. People who may not possess the skillset to take an engaging photo or create a video, now have the opportunity to do so with this technology. AI lowers the barrier to entry for content creation, even more so than what the iPhone does for photography or TikTok does for video.

Established creators can incorporate AI generators into their existing creative processes or workflows, especially when it comes to ideation and inspiration. For example, they could generate images and photos that can serve as a storyboard instead of putting one together through traditional means. Creators can use generative AI to expand into other creative works while saving time and money. For example, a creator that typically outsources graphic design work could use AI to handle it themselves and benefit from doing it for free or at a much cheaper cost within seconds.

Regardless of the use case, this helps solve some of the key challenges people face with creating and sharing content, such as turning an idea into a tangible asset, creating content in a timely fashion with less effort, and creating high-quality content.

Existing Challenges

Generative AI isn’t without challenges. One of the most notable challenges is the idea of using others' original work. Some argue that people are infringing on copyrights and plagiarizing because generators use existing works from photographers, videographers, artists, and others. Commercializing AI-generated content can be particularly problematic. Some have started monetizing their creations, such as selling prints of them on Etsy or licensing them to stock photo platforms, which has caused a great deal of pushback from certain creative communities.

An argument can be made, though, for people who use generators. The specific images and videos that are generated depend on the exact text they input, including the combination of words and order of words. People must know how to manipulate the software, such as adding and refining text prompts to get their desired results. As Karen Cheng, a visual artist who created the first AI magazine cover for Cosmopolitan this past summer, revealed that it can take hours and hours to identify the text prompts that deliver desired results. Although different than typical skillsets, leveraging technology is a skill in itself.

Other existing challenges are biases in the algorithms, using generators to create harmful content, and misinformation, many of which are the same challenges that social media platforms face today.

Going Forward

Like most disrupting spaces, generative AI will grow and improve over time. Generators will become even more powerful, helping people to produce even higher-quality content, especially video, in a shorter period of time. There will also be more established norms, including how people look at the use of creating from others’ existing work. The addition of revenue sharing or licensing will help make others more comfortable. But eventually, as more people, including creators and brands, benefit from generative AI, people will view it similarly to how artists may sample existing songs to create new songs.

Overall, AI-powered generators will help creators accelerate their creativity and speed up their productivity, allowing them to churn out content, build audiences, and monetize faster than ever. As a result, there will be even more creators in the ecosystem, which is a benefit for all.