The debate on creativity has intensified with the rise of generative AI, especially of large language models (LLMs). Recent research shows that these systems can produce work that competes with, and in some cases exceeds, human creativity (Guzik et al., 2023; Bohren et al., 2024). At the same time, their use brings serious concerns about value, authenticity, and the long-term safeguarding of human creative practices (Mei et al., 2025; Messer, 2024). This tension highlights what might be called the “flattening threat”: there is a perceived risk that even as LLMs make it easier to generate ideas and boost productivity, they could also diminish the diversity, style and authenticity that enrich human creativity.

The field of AI is experiencing a participatory turn (Delgado et al., 2023). From tech companies to researchers, there is growing recognition that AI design and development should not happen in isolation from the people it affects. Regardless whether AI systems are designed for mental health, education or journalism, they need input from communities who deeply understand these domains. Interdisciplinary collaboration has been assuming a more pivotal role, bringing together computer scientists, researchers, ethicists and community members to create more aligned and responsible AI systems. This shift is certainly representative of progress.