A University of Houston researcher analyzed the nuances of how generative AI can influence
creativity. (Credit Getty Images)
Art has been around for centuries, but in the age of artificial intelligence, one
University of Houston researcher is examining if generative AI helps or hurts creativity.
Jinghui Hou, lead author and assistant professor in the C. T. Bauer College of Business,
began researching AI’s impact on creativity when the applications first became popular. Hou along with co-authors from around
the world analyzed the nuances of how generative AI can influence creativity, depending
on the context, in a paper published in October in Information Systems Research.
Jinghui Hou, lead author and assistant professor in the C. T. Bauer College of Business
Researchers identified two distinct stages of creativity: ideation and convergent
thinking. They define the ideation stage as brainstorming what to create.
“In the first stage we find that for anyone, including ordinary people and expert
designers, AI is very helpful because of its computational power,” Hou said. “It can
go beyond the imagination that humans have. For example, if I wanted to imagine a
tiger with wings, it would be hard to see that in my head, but AI can do it easily.”
In the stage of convergent thinking, they found that AI impacts creative professionals
differently than designers with lower levels of expertise. Following ideation, convergent
thinking demonstrates putting the technology into action to create art.
“In the implementation stage, we find that AI is still very helpful for those ordinary
people, but it creates more work for expert designers,” Hou said. “This is because
the designer has years of training to materialize a piece of artwork. We find that
AI uses different techniques to produce creative work. For designers, it can become
burdensome to revise what AI made.”
The business implications of the findings suggest that creatives and generative AI
developers should carefully consider how to best incorporate technology into the production
process, Hou said.
“We would suggest all people embrace AI in the brainstorming stage,” she said. “We
would suggest the designers of AI have the product more tailored to the different
users in the implementation stage. It could give users more freedom to fit the technology
to their usage pattern and workflow. In a sense, it’s not about people catering to
the AI, but the AI technology catering to people.”