Should Artificial Intelligence Align With Human Thinking In Innovation Processes?

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Chinese explanation / 中文解读

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Original abstract

Large Language Models (LLMs) are often integrated into today's innovation processes, but uniform AI assistance is incongruent with innovators' shifting cognitive states, encouraging over-reliance and premature convergence that erode idea diversity.We introduce a phase-specific, multi-agent human-AI innovation system that offers distinct AI assistance across exploration (divergence) and implementation (convergence).The system augments innovation phases with ideation support that probes assumptions and provides alternative framings to promote divergent exploration and an implementation chatbot that probe feasibility and accelerates convergent execution.We pilot the system in two innovation focused hackathons to show that human-thinking-aligned assistance preserves idea diversity during ideation while facilitating efficient convergence toward feasible prototypes during implementation.We plan to conduct a large-scale field experiment.

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