MIT Sloan Management Review Article on Does GenAI Impose a Creativity Tax?

LLMs can boost worker productivity, but outputs may reflect less human creativity and originality.

Generative AI systems that model language have shown remarkable proficiency at a variety of tasks, and employees have embraced them to speed up writing and software development work in particular. The productivity boosts promised by these tools, such as ChatGPT, are leading many managers to incorporate them into workflows. However, our research reveals that the potential efficiency improvements come with a potential downside.

Overreliance on AI may discourage employees from expressing their specific know-how and coming up with their own ideas, and could also result in increasingly homogenized outputs that limit the advantages of employee diversity. In the long term, this could diminish innovation and originality. Managers seeking to gain efficiencies via large language models (LLMs) will need to help employees thoughtfully balance productivity and creativity in their collaboration with AI.

About the Author

Francisco Castro is an assistant professor of decisions, operations, and technology management at UCLA Anderson School of Management. Jian Gao is a doctoral student at UCLA Anderson. Sébastien Martin is an assistant professor of operations at the Kellogg School of Management at Northwestern University.

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