Supermind Ideator: How scaffolding Human-AI collaboration can increase creativity

Previous efforts to support creative problem-solving have included (a) techniques such as brainstorming and design thinking to stimulate creative ideas, and (b) software tools to record and share these ideas. Now, generative AI technologies can suggest new ideas that might never have occurred to the users, and users can then select from these ideas or use them to stimulate even more ideas. To explore these possibilities, we developed a system called Supermind Ideator that uses a large language model (LLM) and adds prompts, fine tuning, and a specialized user interface in order to help users reformulate their problem statements and generate possible solutions. This provides scaffolding to guide users through a set of creative problem-solving techniques, including some techniques specifically intended to help generate innovative ideas about designing groups of people and/or computers (“superminds”). In an experimental study, we found that people using Supermind Ideator generated significantly more innovative ideas than those generated by people using ChatGPT or people working alone. Thus our results suggest that the benefits of using LLMs for creative problem-solving can be substantially enhanced by scaffolding designed specifically for this purpose.

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Institutions

Publication Details

Journal
Collective Intelligence
Published
2024-10-01
DOI
https://doi.org/10.1177/26339137241305117
Citations
6
Primary Topic
Design Education and Practice
Type
article
Field-Weighted Citation Impact
1.28

Funders

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article

Supermind Ideator: How scaffolding Human-AI collaboration can increase creativity

Max Sina Knicker, Robert Laubacher, Pranav Ragupathy, Steven Rick et al.
6 citations
Collective Intelligence
Design Education and Practice
1.28
article

Supermind Ideator: How scaffolding Human-AI collaboration can increase creativity

Max Sina Knicker, Robert Laubacher, Pranav Ragupathy, Steven Rick, Jennifer L. Heyman, Jared R. Curhan, Gianni Giacomelli, Thomas W. Malone, Nancy Taubenslag, Younes Jeddi, Haoran Wen
article en
6 citations

Abstract

Previous efforts to support creative problem-solving have included (a) techniques such as brainstorming and design thinking to stimulate creative ideas, and (b) software tools to record and share these ideas. Now, generative AI technologies can suggest new ideas that might never have occurred to the users, and users can then select from these ideas or use them to stimulate even more ideas. To explore these possibilities, we developed a system called Supermind Ideator that uses a large language model (LLM) and adds prompts, fine tuning, and a specialized user interface in order to help users reformulate their problem statements and generate possible solutions. This provides scaffolding to guide users through a set of creative problem-solving techniques, including some techniques specifically intended to help generate innovative ideas about designing groups of people and/or computers (“superminds”). In an experimental study, we found that people using Supermind Ideator generated significantly more innovative ideas than those generated by people using ChatGPT or people working alone. Thus our results suggest that the benefits of using LLMs for creative problem-solving can be substantially enhanced by scaffolding designed specifically for this purpose.

Collective IntelligenceVol. 3(4)
École Polytechnique (FR), The Polytechnic University of Japan (JP), Université Mohammed VI Polytechnique (MA), Massachusetts Institute of Technology (US)
Toyota Research Institute, National Research Foundation
Openalex Percentile: Top 22%
Design Education and Practice
1.28
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