Creativity is often considered as an “intuition” or “talent” and can’t be easily interpreted in a logical way (Wu et al. 2021). The creative industries often refer to graphic design, film, music, video games, fashion, advertising, media or entertainment industries (Howkins 2002), related to the extraordinary thinking by supreme creative individuals (Weisberg 2006). However, creativity actually lies in all creative activities, from the arts to science, from everyday life to industry production. Today, creativity is considered to be a crucial competency (Binkley et al. 2012). Boden (2004), who pioneered the field of philosophy of cognitive science, offers the definition “Creativity is the ability to come up with ideas or artefacts that are new, surprising and valuable”. With the help of language, people used the creative process in art and technology, making creativity “one of the most striking features of the human species”, since at least 40,000 years ago (Carruthers 2002, p. 226). Creativity in today’s sense is at the heart of human endeavour, shaping various fields including education, art and healthcare (Esling and Devis 2020; Farina et al. 2024; Tredinnick and Laybats 2023).

For as long as we have written history, humans have been fascinated by the idea of thinking about thinking. The ancient Greeks saw self-reflection as a path to wisdom: Socrates urged his students to “know thyself”, while Aristotle suggested that the mind could even grasp its own activity. Centuries later, philosophers and logicians took this further, asking whether knowing something also means knowing that you know it. In the 1960s, Jaakko Hintikka captured this in a famous principle of logic: if an agent knows a fact, it should also know that it knows it. Fast forward to today, and this same idea has found new life in artificial intelligence, where researchers explore how machines might be designed not just to think, but to reflect on their own thinking.

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.