Generative AI, Human Creativity and Art

Exciting news! Our esteemed Digital Business Institute Research Fellow, DK Lee, along with co-author Eric Zhou, have had their paper accepted and will be forthcoming at PNAS Nexus on March 5th. Their paper, Generative AI, Human Creativity, and Art, is based on a large dataset and robust econometric methods, is the first of its kind to explore the relationship between generative AI, human creativity, and art. Some findings:

After adopting Text-to-Image Models like Midjourney/Dall-e/Stable Diffusion:
🎨 Artists produce 2X more (first month), stabling off to 25%
🎨 Their art rating goes up to 50% more over time
🎨 While peak content novelty (focal objects and object relationships) increases over time, average content novelty declines, suggesting an expanding but inefficient creative space
🎨 AI adoption decreased value capture (favorites earned) concentration among the adopted

🖼️The results imply that ideation and likely filtering are necessary skills in the text-to-image process, thus giving rise to “generative synesthesia” – the harmonious blending of human senses and AI mechanics to discover new creative workflows.

Check out the paper on SSRN and join the discussion on the future of art and generative synesthesia.

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