Knowing how to craft useful questions for generative AI tools may end up being one of the great skills of the future

I’ve messed around with the AI image and text generators DALL-E 2 and ChatGPT, respectively. They’re pretty cool, although they clearly have limitations in the hands of an amateur like me. (For now.)

Of course, the technology is stratospherically above my head in terms of the details of how AI scientists go about creating these tools. But I still enjoy reading the things smart people have to say about them.

Charlie Warzel over at The Atlantic is his usual fascinatiing and illuminating self as he ponders questions about how the people who might be very much in demand for future jobs are those people who understand how to word questions (called “prompts”) for DALL-E and ChatGPT that get the most out of the technology:

At present, sorting the hype from genuine enthusiasm is difficult, but given the billions of dollars being funneled into this technology, it’s worth asking, in ways large and small: What does the world look like if the evangelists are right? If this AI paradigm shift arrives, one vital skill of the 21st century could be effectively talking to machines. And for now, that process involves writing—or, in tech vernacular, engineering—prompts.

Image-generating models such as DALL-E 2 and Midjourney and text-generation tools like ChatGPT market themselves as a means for creation. But in order to create, one must know how to guide the machines to a desired outcome. Asking ChatGPT to write a five-paragraph book report about Animal Farm will yield forgettable, even inaccurate results. But writing the introductory paragraph to the book report yourself and asking the tool to complete the essay will feed the machine valuable context.

Better yet, instruct the machine, “Write a five-paragraph book report at a college level with elegant prose that draws on the history of the satirical allegorical novel Animal Farm. Reference Orwell’s ‘Why I Write’ while explaining the author’s stylistic choices in the novel.” It will yield a far more sophisticated and convincing output.

Good prompts aren’t just specific. They seem to reflect a deeper understanding of the model you are trying to manipulate. One way to think of prompt trial and error is as an attempt to glean what information the model is pulling from and how the AI organizes and indexes the information at its disposal. It’s informed guesswork.

Despite making a living as a writer, I’m usually far too vague when instructing DALL-E 2 and Midjourney. When I had my 8-year-old nephew play with Midjourney this summer, his imagination conjured delightful scenes such as a flea surfing on a tsunami wave fighting a giant wasp, but, even together, we couldn’t come up with the details for our prompts to bring his specific vision to life. First, his flea didn’t look cartoonish enough; then, the tweaks I made turned the whole thing hyperrealistic and too scary for him. He lacked the stylistic language to talk to the model, and apparently, so did I.

To help people like me and my nephew, a cottage industry has already sprung up around those who can speak to the machines. On PromptBase, a marketplace for prompt engineers, you can purchase a few lines of text to feed into any number of generative-AI models. Some of the most popular prompts on the service are for generating “cute 3D renders of emojis in a clay style” with DALL-E 2 or creating sleek, modern logos via Midjourney.

It’s going to be a strange new world once these tools reach their full potential.

How generative AI works.

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