A Novel Idea Generation Tool using a Structured Conversational AI (CAI) System
B. Sankar, Dibakar Sen
TL;DR
The paper presents a novel CAI-based active ideation interface that uses a GPT model to counteract initial latency and bottlenecks faced by novice designers during early ideation. It details the design of a structured, prompt-engineered CAI workflow and a moodboard interface, plus techniques for fine-tuning, multi-session context, and temperature-based nudging to balance novelty with relevance. Through a pilot study with 30 design students, CAI-generated ideas show higher novelty, fluency, and variety than traditional methods, supporting the potential of CAI to supplement (not replace) human critique in ideation. The work introduces AI3C and PFIC/AOC structural frameworks to organize problem statements, ideas, and concepts, aiming to provide scalable, interpretable, and reusable prompts for design ideation with measurable outcomes. This approach could meaningfully accelerate early-stage product design and broaden access to creative ideation for less-experienced designers, though automated shortlisting remains an area for future development.
Abstract
This paper presents a novel conversational AI-enabled active ideation interface as a creative idea-generation tool to assist novice designers in mitigating the initial latency and ideation bottlenecks that are commonly observed. It is a dynamic, interactive, and contextually responsive approach, actively involving a large language model (LLM) from the domain of natural language processing (NLP) in artificial intelligence (AI) to produce multiple statements of potential ideas for different design problems. Integrating such AI models with ideation creates what we refer to as an Active Ideation scenario, which helps foster continuous dialogue-based interaction, context-sensitive conversation, and prolific idea generation. A pilot study was conducted with thirty novice designers to generate ideas for given problems using traditional methods and the new CAI-based interface. The key parameters of fluency, novelty, and variety were used to compare the outcomes qualitatively by a panel of experts. The findings demonstrated the effectiveness of the proposed tool for generating prolific, diverse and novel ideas. The interface was enhanced by incorporating a prompt-engineered structured dialogue style for each ideation stage to make it uniform and more convenient for the designers. The resulting responses of such a structured CAI interface were found to be more succinct and aligned towards the subsequent design stage, namely conceptualization. The paper thus established the rich potential of using Generative AI (Gen-AI) for the early ill-structured phase of the creative product design process.