poster

CausalMapper: Challenging designers to think in systems with Causal Maps and Large Language Model

Authors:

Stephen MacNeilAuthors Info & Claims

C&C '23: Proceedings of the 15th Conference on Creativity and Cognition

Pages 325 - 329

https://doi.org/10.1145/3591196.3596818

Published: 19 June 2023 Publication History

Abstract

Professional designers often construct and explore conceptual representations (e.g.: design spaces) to help them reason about complex design situations and consider potential design pitfalls. However, it is often challenging, even for professional designers, to exhaustively consider the many pitfalls that might result from design activity. We present CausalMapper, a mixed-initiative system, that leverages a large language model (LLM) and a causal map representation to teach design students how to reason about the relationships between problems and solutions. Where creativity support tools often focus on ideating creative solutions, our mixed-initiative approach focuses on ideating ecosystems of solutions that holistically address a set of related problems. By leveraging the generative creativity of LLMs, designers are inspired to consider solutions and potential consequences that emerge when solutions are adopted. At the same time, leveraging the designers’ domain knowledge to account for and correct the biases inherent in LLMs. Through a case study, we demonstrate the functionality of this mixed-initiative system. The goal of this demo is to present a creativity support tool that is intended to teach design students to think more systematically by generating ideas that challenge their thinking rather just augmenting their creative potential.

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Cited By

Armstrong LLiu AMacNeil SMetaxa D(2024)The Silicon Ceiling: Auditing GPT’s Race and Gender Biases in HiringProceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization10.1145/3689904.3694699(1-18)Online publication date: 29-Oct-2024
https://dl.acm.org/doi/10.1145/3689904.3694699
Denny PMacNeil SSavelka JPorter LLuxton-Reilly AMonga MLonati VBarendsen ESheard JPaterson J(2024)Desirable Characteristics for AI Teaching Assistants in Programming EducationProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653574(408-414)Online publication date: 3-Jul-2024
https://dl.acm.org/doi/10.1145/3649217.3653574
Hou IMettille SMan OLi ZZastudil CMacNeil S(2024)The Effects of Generative AI on Computing Students’ Help-Seeking PreferencesProceedings of the 26th Australasian Computing Education Conference10.1145/3636243.3636248(39-48)Online publication date: 29-Jan-2024
https://dl.acm.org/doi/10.1145/3636243.3636248
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cover image ACM Conferences

C&C '23: Proceedings of the 15th Conference on Creativity and Cognition

June 2023

564 pages

ISBN:9798400701801

DOI:10.1145/3591196

Copyright © 2023 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 19 June 2023

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C&C '23: Creativity and Cognition

June 19 - 21, 2023

Virtual Event, USA

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Cited By

Armstrong LLiu AMacNeil SMetaxa D(2024)The Silicon Ceiling: Auditing GPT’s Race and Gender Biases in HiringProceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization10.1145/3689904.3694699(1-18)Online publication date: 29-Oct-2024
https://dl.acm.org/doi/10.1145/3689904.3694699
Denny PMacNeil SSavelka JPorter LLuxton-Reilly AMonga MLonati VBarendsen ESheard JPaterson J(2024)Desirable Characteristics for AI Teaching Assistants in Programming EducationProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653574(408-414)Online publication date: 3-Jul-2024
https://dl.acm.org/doi/10.1145/3649217.3653574
Hou IMettille SMan OLi ZZastudil CMacNeil S(2024)The Effects of Generative AI on Computing Students’ Help-Seeking PreferencesProceedings of the 26th Australasian Computing Education Conference10.1145/3636243.3636248(39-48)Online publication date: 29-Jan-2024
https://dl.acm.org/doi/10.1145/3636243.3636248
Wazzan AMacNeil SSouvenir R(2024)Comparing Traditional and LLM-based Search for Image GeolocationProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638305(291-302)Online publication date: 10-Mar-2024
https://dl.acm.org/doi/10.1145/3627508.3638305
Huang ZGutierrez SKamana HMacneil S(2023)Memory Sandbox: Transparent and Interactive Memory Management for Conversational AgentsAdjunct Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586182.3615796(1-3)Online publication date: 29-Oct-2023
https://dl.acm.org/doi/10.1145/3586182.3615796

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