Exploring Creativity Support for Concept Art Ideation

Creatives often struggle with fixation on a narrow set of ideas. There is potential for co-creative systems to stimulate creatives in new and powerful ways. We sought to lay a foundation for such systems with an exploratory study. We recruited 20 university students and asked them to rapidly draw a series of creature concepts with two technology probes, one of which generates ambiguous stimuli from user strokes. We analyzed the 240 sketches visually and discovered that while most participants were fixated on humanoid forms, those that began sketching with the ambiguous stimuli first were provoked to explore more unusual varieties (p < 0.01). We also interviewed participants and used thematic analysis to analyze the data. While some participants resisted the partial loss of control and freedom, most believed the stimuli encouraged more divergent exploration and holistic thinking, and they acknowledged their potential benefit in the earliest stages of the ideation process.

[1]  Pegah Karimi,et al.  Creative sketching partner: an analysis of human-AI co-creativity , 2020, IUI.

[2]  Brian Magerko,et al.  Designing Co-Creative AI for Public Spaces , 2019, Creativity & Cognition.

[3]  Prashanth Thattai Ravikumar.  Notational Communication with Co-creative Systems: Studying Improvements to Musical Coordination , 2017, Creativity & Cognition.

[4]  Brian Magerko,et al.  Designing for Socially Interactive Systems , 2017, Creativity & Cognition.

[5]  Brian Magerko,et al.  Empirically Studying Participatory Sense-Making in Abstract Drawing with a Co-Creative Cognitive Agent , 2016, IUI.

[6]  Brian Magerko,et al.  Drawing Apprentice: An Enactive Co-Creative Agent for Artistic Collaboration , 2015, Creativity & Cognition.

[7]  T. Hammond.  Dialectical Creativity: Sketch-Negate-Create , 2015 .

[8]  A. Clarke,et al.  Situational Analysis in Practice : Mapping Research with Grounded Theory , 2015 .

[9]  Brian Magerko,et al.  An Enactive Model of Creativity for Computational Collaboration and Co-creation , 2015, Creativity in the Digital Age.

[10]  Antonios Liapis,et al.  Mixed-initiative co-creativity , 2014, FDG.

[11]  Amitava Das,et al.  Poetic Machine: Computational Creativity for Automatic Poetry Generation in Bengali , 2014, ICCC.

[12]  Hannu Toivonen,et al.  From Isolation to Involvement: Adapting Machine Creativity Software to Support Human-Computer Co-Creation , 2014, ICCC.

[13]  Scott Robertson,et al.  How to Draw: Drawing and Sketching Objects and Environments from Your Imagination , 2013 .

[14]  Lilia Halim,et al.  Effects of Problem-solving Strategies in the Teaching and Learning of Engineering Drawing Subject , 2012 .

[15]  R. van Ee,et al.  United we sense, divided we fail: context-driven perception of ambiguous visual stimuli , 2012, Philosophical Transactions of the Royal Society B: Biological Sciences.

[16]  Krzysztof T. Konecki.  Visual Grounded Theory: A Methodological Outline and Examples from Empirical Work , 2011 .

[17]  Yong Jae Lee,et al.  ShadowDraw: real-time user guidance for freehand drawing , 2011, ACM Trans. Graph..

[18]  Masanori Sugimoto,et al.  Beyond binary choices: Integrating individual and social creativity , 2005, Int. J. Hum. Comput. Stud..

[19]  Steve Benford,et al.  Ambiguity as a resource for design , 2003, CHI '03.

[20]  P. Tierney,et al.  Creative Self-Efficacy: Its Potential Antecedents and Relationship to Creative Performance , 2002 .

[21]  J. Shah,et al.  Collaborative Sketching (C-Sketch)--An Idea Generation Technique for Engineering Design. , 2001 .

[22]  Gloria Kauffman,et al.  "I just need to draw": Responding to literature across multiple sign systems , 2000 .

[23]  Steven M. Smith,et al.  Creative Cognition: Theory, Research, and Applications , 1996 .

[24]  T. B. Ward.  Structured Imagination: the Role of Category Structure in Exemplar Generation , 1994, Cognitive Psychology.

[25]  B. Glaser.  The Constant Comparative Method of Qualitative Analysis , 1965 .