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This paper analyzes the creativity of LLM agents through functionalist (output-focused) and ontological (process-focused) lenses. It argues that LLM agents exhibit functionalist creativity, but lack key aspects of ontological creativity related to underlying processes and social/personal dimensions. The paper concludes by discussing the desirability and potential pathways for achieving both forms of artificial creativity, weighing the associated benefits and risks.
LLM agents can generate novel outputs, but don't yet possess the deeper, process-driven creativity that defines human innovation.
Large language models (LLMs), particularly when integrated into agentic systems, have demonstrated human- and even superhuman-level performance across multiple domains. Whether these systems can truly be considered creative, however, remains a matter of debate, as conclusions heavily depend on the definitions, evaluation methods, and specific use cases employed. In this paper, we analyse creativity along two complementary macro-level perspectives. The first is a functionalist perspective, focusing on the observable characteristics of creative outputs. The second is an ontological perspective, emphasising the underlying processes, as well as the social and personal dimensions involved in creativity. We focus on LLM agents and we argue that they exhibit functionalist creativity, albeit not at its most sophisticated levels, while they continue to lack key aspects of ontological creativity. Finally, we discuss whether it is desirable for agentic systems to attain both forms of creativity, evaluating potential benefits and risks, and proposing pathways toward artificial creativity that can enhance human society.