More Web Proxy on the site http://driver.im/

research-article

Public Access

Relating Cognitive Models of Design Creativity to the Similarity of Sketches Generated by an AI Partner

Authors:

Nicholas Davis,

Mary Lou Maher,

Lina LeeAuthors Info & Claims

C&C '19: Proceedings of the 2019 Conference on Creativity and Cognition

Pages 259 - 270

https://doi.org/10.1145/3325480.3325488

Published: 13 June 2019 Publication History

Abstract

This paper presents and evaluates a new method for inspiring creativity in a co-creative design system. The method uses a computational model of aconceptual shift based on clustering of deep features from a database of sketches. The co-creative sketching tool maps a user's sketch to a sketch of a distinct category that has high, medium, or low visual and semantic similarity. We hypothesize that the degree of similarity between the user's and the system's sketches is associated with a range of cognitive models of creativity in a design context. We report on the findings of an empirical study that analyzes different design scenarios in which the user sketches in response to a proposed conceptual shift. The findings show that how similar the computational agent's sketch is to the user's original sketch is related to the presence of three types of design creativity in the user's response: combinatorial, exploratory, and transformational.

References

[1]

2019. SketchTogether. (2019). https://sketchtogether.com

[2]

John A Biles and others. 1994. GenJam: A genetic algorithm for generating jazz solos. In ICMC, Vol. 94. 131--137.

[3]

Margaret A Boden. 1996. Creativity. In Artificial Intelligence. Elsevier, 267--291.

[4]

Margaret A Boden. 2004. The creative mind: Myths and mechanisms. Routledge.

Digital Library

[5]

V. Carbune. 2017. Recurrent Neural Networks for Drawing Classification. (2017). https://www.tensorflow.org/tutorials/sequences/recurrent_quickdraw

[6]

Simon Colton, Geraint A Wiggins, and others. 2012. Computational creativity: The final frontier?. In Ecai, Vol. 2012. Montpelier, 21--16.

Digital Library

[7]

Jim Davies, Ashok K Goel, and Nancy J Nersessian. 2009. A computational model of visual analogies in design. Cognitive Systems Research 10, 3 (2009), 204--215.

Digital Library

[8]

Nicholas Davis. 2013. Human-computer co-creativity: Blending human and computational creativity. In Ninth Artificial Intelligence and Interactive Digital Entertainment Conference.

[9]

Nicholas Davis, Chih-PIn Hsiao, Kunwar Yashraj Singh, Lisa Li, Sanat Moningi, and Brian Magerko. 2015. Drawing apprentice: An enactive co-creative agent for artistic collaboration. In Proceedings of the 2015 ACM SIGCHI Conference on Creativity and Cognition. ACM, 185--186.

Digital Library

[10]

Nicholas Davis, Chih-PIn Hsiao, Kunwar Yashraj Singh, Lisa Li, and Brian Magerko. 2016. Empirically studying participatory sense-making in abstract drawing with a co-creative cognitive agent. In Proceedings of the 21st International Conference on Intelligent User Interfaces. ACM, 196--207.

Digital Library

[11]

Ernest A Edmonds, Alastair Weakley, Linda Candy, Mark Fell, Roger Knott, and Sandra Pauletto. 2005. The studio as laboratory: combining creative practice and digital technology research. International Journal of Human-Computer Studies 63, 4--5 (2005), 452--481.

Digital Library

[12]

Dedre Gentner. 1983. Structure-mapping: A theoretical framework for analogy. Cognitive science 7, 2 (1983), 155--170.

[13]

John S Gero. 2000. Computational models of innovative and creative design processes. Technological forecasting and social change 64, 2--3 (2000), 183--196.

[14]

Guy Hoffman and Gil Weinberg. 2010. Gesture-based human-robot jazz improvisation. In Robotics and Automation (ICRA), 2010 IEEE International Conference on. IEEE, 582--587.

[15]

Mikhail Jacob, Gaëtan Coisne, Akshay Gupta, Ivan Sysoev, Gaurav Gav Verma, and Brian Magerko. 2013. Viewpoints ai. In Ninth Artificial Intelligence and Interactive Digital Entertainment Conference.

[16]

Jonas Jongejan, Henry Rowley, Takashi Kawashima, Jongmin Kim, and Nick Fox-Gieg. 2016. The quick, draw!-ai experiment. (2016).

[17]

Pegah Karimi, Nicholas Davis, Kazjon Grace, and Mary Lou Maher. 2018a. Deep Learning for Identifying Potential Conceptual Shifts for Co-creative Drawing. arXiv preprint arXiv:1801.00723 (2018).

[18]

Pegah Karimi, Kazjon Grace, Nicholas Davis, and Mary Lou Maher. 2018b. Creative Sketching Apprentice: Supporting Conceptual Shifts in Sketch Ideation. In International Conference on-Design Computing and Cognition. Springer, 721--738.

[19]

Pegah Karimi, Mary Lou Maher, Kazjon Grace, and Nicholas Davis. 2018c. A computational model for visual conceptual blends. IBM Journal of Research and Development (2018).

[20]

Antonios Liapis, Georgios N Yannakakis, and Julian Togelius. 2013. Sentient Sketchbook: Computer-aided game level authoring. In FDG. 213--220.

[21]

Todd Lubart. 2005. How can computers be partners in the creative process: classification and commentary on the special issue. International Journal of Human-Computer Studies 63, 4--5 (2005), 365--369.

Digital Library

[22]

Pedro Lucas and Carlos Martinho. 2017. Stay Awhile and Listen to 3Buddy, a Co-creative Level Design Support Tool. In ighth International Conference on Computational Creativity, ICCC, Atlanta.

[23]

Tomas Mikolov. 2016. word2vec: Tool for computing continuous distributed representations of words. https://code.google.com/p/word2vec. (2016).

[24]

David Norton, Derrall Heath, and Dan Ventura. 2014. Autonomously Managing Competing Objectives to Improve the Creation and Curation of Artifacts. In ICCC. 23--32.

[25]

R Keith Sawyer and Stacy DeZutter. 2009. Distributed creativity: How collective creations emerge from collaboration. Psychology of aesthetics, creativity, and the arts 3, 2 (2009), 81.

[26]

Ben Shneiderman. 2007. Creativity support tools: Accelerating discovery and innovation. Commun. ACM 50, 12 (2007), 20--32.

Digital Library

[27]

Ben Shneiderman, Gerhard Fischer, Mary Czerwinski, Mitch Resnick, Brad Myers, Linda Candy, Ernest Edmonds, Mike Eisenberg, Elisa Giaccardi, Tom Hewett, and others. 2006. Creativity support tools: Report from a US National Science Foundation sponsored workshop. International Journal of Human-Computer Interaction 20, 2 (2006), 61--77.

[28]

Masaki Suwa and Barbara Tversky. 1997. What do architects and students perceive in their design sketches? A protocol analysis. Design studies 18, 4 (1997), 385--403.

[29]

Matthias Voigt, Björn Niehaves, and Jörg Becker. 2012. Towards a unified design theory for creativity support systems. In International Conference on Design Science Research in Information Systems. Springer, 152--173.

Digital Library

[30]

Geraint A Wiggins. 2006a. A preliminary framework for description, analysis and comparison of creative systems. Knowledge-Based Systems 19, 7 (2006), 449--458.

Digital Library

[31]

Geraint A Wiggins. 2006b. Searching for computational creativity. New Generation Computing 24, 3 (2006), 209--222.

Digital Library

Cited By

Figoli FBruggeman RRampino LCiuccarelli P(2025)AI-against-design map: A systematic review of 20 years of AI-focused studies in design researchDesign Studies10.1016/j.destud.2024.10127996(101279)Online publication date: Jan-2025
https://doi.org/10.1016/j.destud.2024.101279
Choi DHong SPark JChung JKim J(2024)CreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AIProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642794(1-25)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642794
Song ZWu YZhang LTao WLi LDing G(2024)Modeling of Drama Performance Intelligent Evaluation Driven by Multimodal DataGenetic and Evolutionary Computing10.1007/978-981-97-0068-4_22(220-232)Online publication date: 2-Feb-2024
https://doi.org/10.1007/978-981-97-0068-4_22
Show More Cited By

Index Terms

Relating Cognitive Models of Design Creativity to the Similarity of Sketches Generated by an AI Partner
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Collaborative interaction

Recommendations

Creative sketching partner: an analysis of human-AI co-creativity
IUI '20: Proceedings of the 25th International Conference on Intelligent User Interfaces

The creative sketching partner (CSP) is a proof of concept intelligent interface to inspire designers while sketching in response to a specified design task. With this interactive system we are studying the effect of an AI model of visual and conceptual ...
The influence of sketch quality on perception of product-idea creativity

This paper explores the relationship between the quality of a sketch and how others perceive the creativity of the idea portrayed by the sketch. In this study, sketch quality is characterized through its line work, perspective, and proportions. Four ...
"Sketching" nurturing creativity: commonalities in art, design, engineering and research
CHI EA '06: CHI '06 Extended Abstracts on Human Factors in Computing Systems

The workshop seeks to bring together researchers and practitioners from diverse creative practices such as interaction design, industrial design, architectural design, media art, music, programming, writing, and scholarly work, to gain insight into the ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

C&C '19: Proceedings of the 2019 Conference on Creativity and Cognition

June 2019

745 pages

ISBN:9781450359177

DOI:10.1145/3325480

General Chairs:
Steven Dow
UC San Diego, USA
,
Mary Lou Maher
UNC Charlotte, USA
,
Program Chairs:
Andruid Kerne
Texas A&M University
,
Celine Latulipe
UNC Charlotte, USA

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 June 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

National Science Foundation

Conference

C&C '19

Sponsor:

SIGCHI

C&C '19: Creativity and Cognition

June 23 - 26, 2019

CA, San Diego, USA

Acceptance Rates

C&C '19 Paper Acceptance Rate 30 of 101 submissions, 30%;

Overall Acceptance Rate 108 of 371 submissions, 29%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
1,190
Total Downloads

Downloads (Last 12 months)307
Downloads (Last 6 weeks)39

Reflects downloads up to 11 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Figoli FBruggeman RRampino LCiuccarelli P(2025)AI-against-design map: A systematic review of 20 years of AI-focused studies in design researchDesign Studies10.1016/j.destud.2024.10127996(101279)Online publication date: Jan-2025
https://doi.org/10.1016/j.destud.2024.101279
Choi DHong SPark JChung JKim J(2024)CreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AIProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642794(1-25)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642794
Song ZWu YZhang LTao WLi LDing G(2024)Modeling of Drama Performance Intelligent Evaluation Driven by Multimodal DataGenetic and Evolutionary Computing10.1007/978-981-97-0068-4_22(220-232)Online publication date: 2-Feb-2024
https://doi.org/10.1007/978-981-97-0068-4_22
Shi YGao TJiao XCao N(2023)Understanding Design Collaboration Between Designers and Artificial Intelligence: A Systematic Literature ReviewProceedings of the ACM on Human-Computer Interaction10.1145/36102177:CSCW2(1-35)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610217
Chang MDruga SFiannaca AVergani PKulkarni CCai CTerry M(2023)The Prompt ArtistsProceedings of the 15th Conference on Creativity and Cognition10.1145/3591196.3593515(75-87)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3591196.3593515
Halperin BLukin S(2023)Envisioning Narrative Intelligence: A Creative Visual Storytelling AnthologyProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580744(1-21)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580744
Zhang CYao CWu JLin WLiu LYan GYing F(2022)StoryDrawerProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501914(1-15)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3501914
Chung JHe SAdar E(2021)The Intersection of Users, Roles, Interactions, and Technologies in Creativity Support ToolsProceedings of the 2021 ACM Designing Interactive Systems Conference10.1145/3461778.3462050(1817-1833)Online publication date: 28-Jun-2021
https://dl.acm.org/doi/10.1145/3461778.3462050
Karimi PRezwana JSiddiqui SMaher MDehbozorgi NPaternò FOliver NConati CSpano LTintarev N(2020)Creative sketching partnerProceedings of the 25th International Conference on Intelligent User Interfaces10.1145/3377325.3377522(221-230)Online publication date: 17-Mar-2020
https://dl.acm.org/doi/10.1145/3377325.3377522
Lin YGuo JChen YYao CYing FBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)It Is Your Turn: Collaborative Ideation With a Co-Creative Robot through SketchProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376258(1-14)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376258

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents