arXiv AI
Jul 31
Human diversity fuels collective creativity that large language models cannot simulate or sustain
arXiv:2607. 26899v1 Announce Type: cross Abstract: Diverse human groups produce diverse ideas, the raw material of innovation.
Human diversity fuels collective creativity that large language models cannot simulate or sustain
Diverse human groups produce diverse ideas, the raw material of innovation. Generative AI challenges this engine twice over: everyday AI assistance may homogenize what diverse people create, and AI-simulated diversity may replace the people altogether.
Related stories
arXiv AI
Jun 9
Seeing the Hivemind: A Consensus-Aware Interaction Technique for Mitigating AI Homogenization
arXiv:2606. 09587v1 Announce Type: cross Abstract: People are increasingly using AI for creative tasks such as writing.
arXiv AI
Aug 5
Assessing the Effect of Cross-Domain Mapping on Creativity in Humans and Large Language Models
arXiv:2603. 19087v2 Announce Type: replace Abstract: Creativity is the ability to come up with novel ideas, a capacity crucial for human development and flourishing.
arXiv AI
Aug 11
Harnessing Abundance: A Generativity Perspective on Human-GenAI Collaboration
arXiv:2608. 07500v1 Announce Type: cross Abstract: Research on human-GenAI collaboration yields conflicting findings: GenAI can enhance creativity yet reduce collective diversity, with uneven benefits across skill levels.
arXiv AI
Jun 6
Individual Gain, Collective Loss: Metacognitive Adaptation in AI-Assisted Creativity
arXiv:2606. 05532v1 Announce Type: new Abstract: Recent studies reveal a paradox: AI enhances individual creative outputs while reducing collective diversity.
arXiv AI
Jun 11
Nonslop: A Gamified Experiment in Human-AI Collaborative Writing
arXiv:2606. 12350v1 Announce Type: new Abstract: The rapid proliferation of large language models (LLMs) raises critical questions about human creativity and individual expression in an era of AI-assisted creation.
arXiv AI
Aug 10
CreativeInstruct: Scalably Teaching LLMs to Balance Quality, Creativity, and Diversity
arXiv:2608. 07460v1 Announce Type: cross Abstract: While post-training improves the capabilities of large language models (LLMs), it generally lowers their output diversity and creativity, negatively impacting tasks that explicitly require creativity (e.
arXiv AI
Jul 31
Linguistic Monoculture in LLM-Assisted Language Use
arXiv:2607. 27134v1 Announce Type: new Abstract: Writing and communication are increasingly mediated by large language models (LLMs) that are being used to draft, revise and polish text.
arXiv AI
Jun 6
The Virtual Roundtable: Multi-Agent Personas Simulating the Dynamics of Human Brainstorming
arXiv:2606. 05178v1 Announce Type: cross Abstract: As AI-driven product development accelerates, the bottleneck is shifting from how we build to what we build.
Hugging Face Trending Papers
Aug 4
On the Diversity of Analogy Making in Large Language Models
Large Language Models (LLMs) have demonstrated remarkable potential for analogy making, a core cognitive capability that drives novelty and creativity. While prior research has extensively investigated the applications and underlying mechanisms of LLM-based analogy making, its output diversity remains largely unexplored, despite being essential for broadening cross-domain connections and fostering scientific innovation.
arXiv AI
Jul 3
CreativityPrism: A Cross-Domain Evaluation Framework for Large Language Model Creativity
arXiv:2510. 20091v3 Announce Type: replace-cross Abstract: Creativity is often seen as a hallmark of human intelligence.
arXiv Machine Learning
Jul 31
Epistemic diversity across language models mitigates knowledge collapse
arXiv:2512. 15011v3 Announce Type: replace Abstract: Artificial intelligence (AI) increasingly generates the very content used to train future AI systems.