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June 29, 2023

Gen AI is no screenwriter—yet

Even if gen AI doesn’t write the next bestseller, lessons of its use in the arts can be applied to business use, generally.

In the news

You can ask your favorite generative artificial intelligence (gen AI) program to write a report. You can ask it to write tips on securing corporate data, managing Gen Z or growing tomatoes. But don’t ask it to write an episode of the TV show Black Mirror.

Charlie Brooker, creator of the hit Netflix series, asked ChatGPT to do just that. The results, Brooker said, were not so good. (His language was more colorful, as the linked story reveals.)

The world is exploring the possibilities and limitations of generative AI. While some seem to fear the technology will write and star in feature films, and create the prints we buy at Home Goods, others are suggesting it’s time to pump the brakes.

Thomas Rabe, the CEO of Germany-based media conglomerate Bertelsmann, made news recently by saying gen AI could be “very positive provided we stay on top of it and understand its potential and threats.”

Those threats may prove thorny indeed. An image created with generative AI has already won an art contest, infuriating human entrants. And it is now common to use existing music to train generative AI programs that write songs—causing much copyright consternation in that industry.

The Cognizant take

Business leaders would do well to heed Rabe and explore generative AI, rather than building barriers against its use. As we wrote recently, these tools “will increasingly be used to facilitate some rudimentary tasks,” such as basic copywriting. But when it comes to creations demanding nuance and subtlety, they should be viewed as assistants, not replacements. 

Additional experience with ChatGPT, Google’s Bard and Microsoft’s Bing Chat reinforce this analysis. When tasked with writing a report on a business topic such as digital transformation, these programs produce results that bring to mind a paper written at the last minute by a furiously Googling college freshman. While not incorrect, the content is flat, derivative and unimaginative.

Which is not to say it’s useless. One of generative AI’s strengths, experience shows, is structure. It tends to organize material handsomely and produce documents of a reasonable length. So, the result of that query on digital transformation could be considered a strong outline and acceptable first draft.

What’s left for human attention is to add interest by varying sentence structure; remove redundancies that remind readers of that panicky college student (“another benefit to the organization of digital transformation is …”); and insert details most pertinent to the intended audience.

The strengths and weaknesses of generative AI demonstrate the path that forward-looking creative people should follow: Develop new skills that leverage the technology. Already, generating powerful prompts is a desirable skill in writing, code generation and other arenas. Both generative AI and those who use it must be trained to maximize its potential. Organizations will need editors to meld software- and human-created content.

It's also important to remember that generative AI in its current accessible form is in its infancy. It will follow the path established by tech through the ages, becoming better and less expensive; eventually, it will be baked into other apps. Microsoft Word already prompts authors to use inclusive language and appropriate levels of formality. It’s not much of a leap to envision this sort of assistance expanding further.

For business leaders, the wise move today is to encourage experimentation with generative AI, all the while thinking of it as a helping hand, rather than a replacement.

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