Understanding the Concerns

Recent discussions among researchers have cast a spotlight on the cognitive effects associated with generative AI technologies. A report published by a team at Microsoft Research Cambridge outlines significant concerns regarding these tools. The researchers argue that generative AI can inhibit critical engagement with tasks, leading to long-term dependency and a decline in independent problem-solving skills.

This shift, as identified by the study, sees a transition in user effort from direct task execution to task stewardship. This reorientation raises questions about learning processes and skill development in an increasingly automated landscape.

The Role of Failure in Learning

Cook, a prominent voice in this discourse, emphasizes that the ability to fail is essential in mastering new skills. Traditionally, artists develop their craft over years of dedication and practice, which inherently includes the experience of failure. Cook highlights that while society often romanticizes natural talent in artists, the reality is that skill acquisition is often a repetitive and challenging process.

“If you actually talk to artists, they say, ‘Well, I got good by doing it over and over and over,’” says Cook. “But failure sucks. And we’re always looking at ways to get around that.”

According to Cook, generative tools can alleviate the discomfort of poor performance, but this comfort comes at a potential cost: the removal of valuable learning experiences.

The Positive Potential of AI

Despite the concerns regarding learning and creativity, there is a growing belief among artists and researchers that generative tools could empower creators in unexpected ways. Rather than simply performing tasks for users, these tools have the potential to enhance individual creativity, encouraging exploration and innovation.

“Using Midjourney does not do anything for me—it doesn’t change anything about me,” Cook states. “And I think that’s a wasted opportunity.”

Reflection: A Critical Component of Creativity

Researchers in the field of creativity frequently emphasize the importance of reflection—a form of deliberate and focused thinking that can spark new ideas or re-evaluate existing assumptions. This reflective process contrasts sharply with the rapid, frictionless interactions often instigated by generative tools.

One line of inquiry in co-creativity research is how AI might support, rather than stifle, reflective thinking. By introducing challenges or unexpected concepts into the creative process, generative tools could promote deeper engagement with ideas. Elisa Giaccardi, a design researcher at the Polytechnic University of Milan, poses the critical question:

“How can we make art without friction? How can we engage in a truly creative process without material that pushes back?”