These are user-focused studies which were conducted as part of the research into drawing habits and to evaluate the usability of the drawing research prototypes.

Drawing Practices, Workflows and Technology

Conducted Autumn 2018

The principal research question for my PhD is how can technology and current developments in Artificial Intelligence and Computer Vision contribute to the drawing process for an artist? The first step of this research is to conduct a qualitative survey of visual artists. The objective of this qualitative survey is to understand the drawing process of visual artists, their use of technology within drawing, and their attitudes towards a potential collaborative role that technology can contribute towards their drawing process. The outcomes from this project will inform the use cases for a PhD research project on collaborative drawing systems for visual artists.

More specifically, the aims of the qualitative study are:

  • Observe and document an artist’s drawing process, to seek common patterns and differences in how an artists does the activity of drawing
  • Gather facts about technology which is used within the artist process, in particular to compare that towards traditional physical artistic mediums
  • Conduct a sentiment analysis, on attitudes (either positive or negative) towards the use of technology in drawing. * Ask baseline questions about the artist’s use of technology in general, which will be useful to compare with their attitude of use of technology and drawing.
  • Receive feedback on a real-time drawing system design which explores a collaborative human-AI drawing interactions

As such, the aim of the study is to gather information about their process, their environment, and their attitudes toward technology and drawing. This will be achieved via a mixed methods study through observation and semi- structured interviews.

Within academic research, the drawing-as-knowing community has focused on looking at the drawing process as opposed to traditional analysis of final “completed” drawings (Cain 2010). These developments have contributed to recent formal academic investigations within the collective and collaborative drawing process amongst artists (Journeaux and Gørrill 2017). However, with the respects to technology, research into improvisation and collaboration systems in the arts has primarily focused on musical collaboration, and an open question is how such systems might exist within the visual arts (McCormack and d’Iverno 2016). The hypotheses center around various factors that influence the artist’s use and attitudes towards technology such as age, amateur versus professional artist, and the type of artists (i.e. fine arts, professional illustrator, and doodler).

Literature Cited

Cain, P., 2010. Drawing: The Enactive Evolution of the Practitioner, Intellect Books.

Journeaux, J. & Gørrill, H., 2017. Collective and Collaborative Drawing in Contemporary Practice, Cambridge Scholars Publishing.

McCormack, J. & d’Inverno, M., 2016. Designing Improvisational Interfaces. In F. Pachet et al., eds. International Conference on Computational Creativity. pp. 98–105.

Drawing Data Gathering

Conducted Winter 2020

The principal research question for my PhD is how might Artificial Intelligence (AI) enhance the drawing workflow via co-creativeinteractions? As part of the research, a system is being develop which records the drawing process via multiple cameras and acommercial drawing tablet. The objective of this study is the provide an initial drawing data that is intended to develop, train and test adrawing AI. One question to answer as part of this study is, what volume of user data is sufficient to train a an AI with enoughvariability among different drawers?