Generative AI and the Future of Content Creation

The explosive growth of generative AI over the past year has been truly phenomenal. Launched with the public release of ChatGPT (was it really only a year ago?), it is now everywhere. Want to ride the wave, each application of Desk has eBay added generative capabilities, and increasing numbers of us find uses for it in our daily and professional lives.

Given its nature, it’s no surprise that content creators, in particular, have found it a powerful addition to their toolset. Marketing agencies, advertising creatives, news agencies and social media influencers are among the most enthusiastic early adopters.

While it offers great opportunities to improve efficiency and automate the manual, repetitive elements of creative work, it also raises significant challenges. Issues surrounding copyright, spammy content, hallucinations, the formal nature of algorithmic creation, and bias all need to be considered by professionals considering adopting it into their workflow.

With that in mind, here’s my overview of the impact generative AI is already having in this area, as well as some thoughts on what we can expect as the technology becomes even more powerful and society adapts to a world augmented by AI.

How is AI used in content creation?

Generative AI learns to create by studying data and discovering how to create similar data. Some of the most commonly used generative models today are large language models like the one that powers ChatGPT, which is capable of creating language and text, and streaming models, which create images and videos.

Technology-driven businesses have quickly assimilated it into their creative processes. For example:

Netflix uses generative AI to create more engaging movie trailers and works to create personalized trailers that will appeal to each member.

Buzzfeed uses it to create personalized content, including quizzes tailored to individual interests. He also created a generator recipe creator which suggests meals based on available ingredients.

Google presents a service designed for news agencies to allow them to automate the creation of reports. Media outlets such as the New York Times, the Guardian, the BBC, Bloomberg and Reuters are among the many that have published articles written by generative AI.

And a new generation of toolmakers is emerging. There is Synthesiswhich allows companies to create videos from text without the need to book actors or studios, and Sonic writing, which automates written content tailored to a brand’s voice, as well as the creation of AI chatbots. And there are many others.

Increase creative workflows

If you’re a creative wondering how to integrate generative AI into your daily work, the first rule is to remember that it’s there to augment your capabilities rather than replace them.

As Sam Garg, CEO and founder of Writesonic, explains, generative content itself is often very generic, formal, and not designed to do the one thing digital content usually needs to do, which is – to attract our attention.

This means that while generative AI tools are perfectly capable of, say, writing an article like this, a script for an ad, or generating a full promotional video, it’s usually not the best way to use it.

Garg says: “The idea is to augment humans rather than replace them. And fundamentally, looking at AI as a tool that enhances the productivity of humans and works in concert, rather than something that replaces humans.

This human approach ensures that the content does not become robotic and formulaic.

You can find uses for generative AI at almost every stage of the creative process – from ideation, to planning, to storyboarding, to copywriting, to fact-checking, to public distribution.

But quality content generally works for two reasons: it introduces something new, like a new idea, and it establishes an emotional connection with the audience.

These are two areas where generative AI often falls flat. He can’t really come up with new ideas in the same way a human can; it simply regurgitates what it knows from its training data. And he doesn’t really understand emotions the same way we do.

The Pitfalls of Generative AI in Content Creation

Besides the dangers of bland and uninteresting content, there are other issues to consider. At the top of the list are copyright issues, which are two-pronged.

First, the jury is still out on who owns the AI-generated content. Is it the person using AI to create the content? Is it the creator of the tools that generated it? Or is it the owner or creator of the original data that was used to train the AI ​​in the first place?

Second, if you avoid being sued by a creator who claims your AI copied their work, the question arises whether you will be able to enforce copyright on your own creations. This could obviously pose a problem for companies using it to create proprietary assets and materials.

There is also the fact that AI, as it stands, tends to make mistakes. That’s what we call hallucination because it often seems like they’re just making things up. Obviously, no company wants to appear stupid by publishing factually incorrect information. And there’s certainly enough misinformation online already that we don’t want to let the AI ​​run amok and create even more!

Where next?

Although it has already had a huge impact, we are clearly still in the early days with generative AI. In the near future, we will see tools that are even more powerful and, just as importantly, even simpler to use.

It’s very possible that many of the challenges we’ve discussed here – bland content, lack of emotional resonance, and factual inaccuracies – will be overcome. As language models become more powerful and complex, we may well see generative tools that can match humans when it comes to creating content that inspires and engages us.

This will make issues such as identifying deepfakes – highly realistic AI creations designed to deceive humans – and mitigating the spread of AI-generated misinformation even more crucial.

But it’s also likely that the technology will become increasingly accessible, meaning its powers can be used by a more diverse user base. This will result in generative tools and creations that draw on a richer tapestry of human stories and experiences.

Personally, I think there will always be a human need in the content creation process. After all, we are storytellers and creators by nature. But those of us who learn to use generative tools to spark our creative potential will have a distinct advantage over those who don’t, as we develop new ways to creatively express our thoughts and ideas.