arXiv:2606.13196v1 Announce Type: new Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative. This paper asks under what conditions a machine can become genuinely creative, and how human agency can be preserved within shared cognitive and creative environments. It develops a requirement framework derived from Designics, the science of meaning-bearing intentional change. The paper argues that genuine machine creativity should not be defined by output novelty, current performance, or transient architecture alone.
The rapid advancement of generative AI systems necessitates a framework for understanding and defining genuine machine creativity, especially as outputs become indistinguishable from human work.
This paper attempts to establish a foundational framework for understanding machine creativity, moving beyond mere performance to address deeper conceptual questions of agency and meaning, which will redefine human-AI collaboration.
The discussion around AI creativity shifts from 'what machines can do' to 'under what conditions genuine creativity emerges' and how human agency is preserved.
- · AI ethicists
- · Creative industries relying on novel ideas
- · Researchers in AI and cognitive science
- · Platforms defining AI creativity solely by output novelty
- · Purely performance-based AI benchmarks
Further research and philosophical debate will be spurred on the nature of AI consciousness and agency regarding creative acts.
New regulatory frameworks may emerge to define oversight and accountability for genuinely creative AI systems, particularly in intellectual property.
Long-term societal integration of AI could be reshaped based on whether machines are deemed capable of 'meaning-bearing intentional change,' impacting human identity and purpose.
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Read at arXiv cs.AI