Progressive Ideation using an Agentic AI Framework for Human-AI Co-Creation

TL;DR

This paper introduces MIDAS, a novel multi-agent AI framework that enhances human-AI co-creation by progressively generating and refining diverse, novel ideas through a team of specialized AI agents mimicking human meta-cognitive processes.

Contribution

The paper presents MIDAS, a distributed agentic AI system that improves idea diversity and novelty in human-AI co-creation, moving beyond single AI systems.

Findings

MIDAS effectively generates more diverse ideas.

MIDAS assesses both global and local novelty.

The framework promotes active human-AI collaboration.

Abstract

The generation of truly novel and diverse ideas is important for contemporary engineering design, yet it remains a significant cognitive challenge for novice designers. Current 'single-spurt' AI systems exacerbate this challenge by producing a high volume of semantically clustered ideas. We propose MIDAS (Meta-cognitive Ideation through Distributed Agentic AI System), a novel framework that replaces the single-AI paradigm with a distributed 'team' of specialized AI agents designed to emulate the human meta-cognitive ideation workflow. This agentic system progressively refines ideas and assesses each one for both global novelty (against existing solutions) and local novelty (against previously generated ideas). MIDAS, therefore, demonstrates a viable and progressive paradigm for true human-AI co-creation, elevating the human designer from a passive filterer to a participatory, active, collaborative partner.