Maintaining Diversity of Human Expression in the Age of AI
AI systems are rapidly converging toward statistical averages, limiting the richness and value of their outputs. Our research focuses on developing methods for diversifying AI outputs across creative and technical domains, ensuring that AI enhances rather than diminishes human autonomy and expression.
AI systems are producing increasingly uniform outputs, threatening diversity of expression and limiting value creation
In a recent study, 249 out of 250 poems generated by ChatGPT without special prompting were all identified by ChatGPT itself as being derived from the same poet (John Keats). This striking homogeneity illustrates how large language models tend to converge toward a "safe" statistical mean.
This homogenization extends beyond poetry to code, design, business ideas, marketing copy, brand slogans, and other domains where innovation requires deviation from the norm. It's not just a problem for artists—it's a critical issue for businesses, consumers, and society at large.
Large language models (LLMs) like ChatGPT learn patterns from vast datasets, but they tend to optimize for the "average" response that's statistically most likely to be correct or well-received. This leads to several problems:
AI systems converge toward a narrow range of outputs that represent a statistical average rather than the full spectrum of possibilities
AI tools can replace human decision-making rather than augmenting it, reducing agency and creative control
Businesses and markets thrive on differentiation and innovation, which are threatened by homogeneous AI outputs
Learn how AI diversity research can improve competitive advantage, customer experience, and innovation in business contexts
Discover how AI diversity research can enhance creative expression, artistic exploration, and cross-media collaboration
Join our mission to maintain creative and technical diversity in the age of AI
I invite fellow poets, narrators, musicians, and visual artists to contribute to this research by sharing your experiences and creative insights. Your perspective is invaluable as we develop techniques that preserve the full spectrum of creative expression.
Ways to collaborate:
We're always looking for collaborators interested in the technical and social aspects of AI diversity. Whether you're a machine learning researcher, social scientist, or software developer, there are many ways to contribute:
Even if you're not sure how you want to get involved, we'd love to hear from you. Whether you're an artist concerned about AI's impact on creativity, a business leader interested in the competitive implications of AI homogenization, or simply someone interested in this important issue, please reach out.
Get in TouchPerforming research on AI diversity and human-AI collaboration
I'm a postdoctoral researcher at Microsoft Research in NYC, with a focus on diversifying the output of AI in both creative and technical domains. With a background in computer science and expertise in deep learning, generative models, and music AI, I approach artificial intelligence from a unique perspective: how can we ensure AI systems enhance human creativity and autonomy rather than diminish them?
My research addresses two related but distinct dangers in current AI development:
Get in touch to discuss research collaboration, creative partnerships, or learn about research findings