On the Creativity of AI Agents

TL;DR

This paper examines whether large language model agents can be considered truly creative by analyzing their outputs and underlying processes from functionalist and ontological perspectives.

Contribution

It provides a dual-perspective analysis of AI creativity, highlighting that LLM agents show functionalist creativity but lack ontological aspects, and discusses implications for future development.

Findings

LLM agents exhibit observable creative outputs.

They lack key ontological aspects of creativity.

Discussion on benefits and risks of AI creativity.

Abstract

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.