Researchers at the University of North Carolina at Chapel Hill have found that while artificial intelligence can spin increasingly convincing stories, its characters may still lack one of the qualities that make human-written fiction memorable: mystery.
As AI writing tools become more common in publishing and entertainment, Carolina researchers wanted to understand whether the characters created by these systems are as varied and nuanced as those crafted by human authors. Their findings suggest that, despite advances in technology, AI still tends to rely on familiar patterns.
The study examined how characters in stories generated by AI compare with those written by people. Drawing on ideas from literary theory, the researchers analyzed eight different aspects of character portrayal, including whether characters seem realistic or exaggerated, whether they evolve over time and whether they remain mysterious or fully understood by the end of a story.
To do this, the team developed CASPER, an automated framework that evaluated thousands of stories and measured character traits in ways that had never before been systematically applied to AI-generated fiction.
"We found that AI models tend to 'play it safe' with their characters, in the sense that they wrap up storylines neatly," said Anneliese Brei, a graduate student in computer science at UNC-Chapel Hill and lead author of the study. "Human writers, on the other hand, are sometimes more willing to leave questions unanswered and let characters remain mysterious. That difference matters because ambiguity is often what makes a story linger with a reader."
The research comes at a time when AI tools designed specifically for creative writing are gaining traction. Platforms such as Sudowrite and Squibler can help draft novels, while AI is increasingly being used in film and television to generate script outlines and dialogue. Surveys have also shown that many fiction writers now incorporate AI into some part of their creative process.
Their analysis revealed that AI-generated characters often lean more heavily on recognizable archetypes and tend to arrive at tidy resolutions by the end of a story. Human writers, by contrast, appeared more comfortable allowing characters to remain unresolved, contradictory or open to interpretation.
"One of our most surprising findings was that bigger and more powerful AI models don't necessarily create more varied characters than smaller ones," said Nicholas Sanaie, an undergraduate student in computer science at Carolina and co-author of the study. "That tells us the challenge isn't just about scale. It's about how these models understand storytelling itself."
CASPER gives researchers, developers and creative professionals a way to benchmark whether newer AI systems are actually improving portraying complex characters rather than simply becoming more fluent writers. It could also guide the development of future storytelling tools that better support creativity and narrative depth.
"As more people collaborate with AI to write novels, screenplays and other creative works, we need ways to understand both what these systems do well and where they fall short," said Snigdha Chaturvedi, associate professor of computer science at UNC-Chapel Hill and senior author of the study. "CASPER gives us a lens for evaluating character depth and diversity, which can ultimately help developers build storytelling systems that better reflect the complexity of human experience."
For writers experimenting with AI, the findings offer a practical takeaway: AI may be an increasingly capable creative partner, but the most compelling stories may still require the distinctly human willingness to embrace uncertainty, contradiction and characters who don't fit neatly into familiar molds.
