Can AI Imagery and Video Actually Be Good for the Creator Economy?

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Generative AI, those text to image and soon to come text to video apps,  have caught the imagination. Not hard to see why. They’re fun, cheap and useful.

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Their popularity has caught the attention of big tech companies too. During the summer, TikTok launched its 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 , Google and Microsoft launched Imagen Video and Image Creator, respectively.

The tech is also ushering in a new era of creators, helping people become first-time creators.

According to Lindsey Gamble, a self-described influencer marketing and innovation strategist, “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.”

Gamble explains that established creators can incorporate AI generators into their existing creative processes or workflows, “especially when it comes to ideation and inspiration” such as generating images and photos for storyboards.

Generative AI can also be used 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.

So, these are real world practical uses of an AI tool. What’s not to like?

There are two main issues. One is the challenge to copyright

“Some argue that people are infringing on copyrights and plagiarizing because generators use existing works from photographers, videographers, artists,” Gamble notes. “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. Although different than typical skillsets, leveraging technology is a skill in itself.”

Other challenges revolve around biases in the algorithms, using generators to create harmful content, and misinformation (or deepfakes), many of which are the same challenges that social media platforms face today.

Gamble doesn’t address this but does suggest that “the addition of revenue sharing or licensing will help make others more comfortable.”

Point is that generative AI is only just getting started. It’s going to improve rapidly. Sooner rather than later “people will view it similarly to how artists may sample existing songs to create new songs,” Gamble says. “There will also be more established norms, including how people look at the use of creating from others’ existing work.”

As someone suggested recently, the metaverse is going to be too big to be created by humans alone. There aren’t enough computer artists in the world to make it. That’s where AI generated visuals come in and where independent creators can possibly make a killing.

Gamble: “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.”