[CALL FOR BOOK CHAPTERS] Art Machines - Poetics of Artificial Intelligence

  • Deadline:
    July 15, 2019, 11:59 p.m.

Art Machines - Poetics of Artificial Intelligence


Machine Learning, a branch of Artificial Intelligence where computers learn to solve problems, is now applied in virtually all areas of social life, including marketing, games, law, search engines, automated recommendations, translation, trading, etc.

The need for both public understanding and participation in technological changes that affect all of our lives in profound and wide-ranging ways is more urgent than ever. In this context, artistic work can provide new perspectives and critically explore and interact with these new technologies.

How should artists respond to the widespread presence of technologies whose internal operation is opaque to most, if not all, people? What kind of work are artists now making using machine learning technologies and methodologies? What are the future possibilities of machine learning for artists?

We are calling for artists, curators, technologists, and humanists, to submit book chapters exploring the relationship between art and machine learning.

Articles may include analytical essays, artistic and curatorial projects, and technical reports.

Possible topics include, but are not restricted to:

· Visualization. Scientists have developed innovative ways to visualize different aspects of machine learning. The aim is to understand those technologies better and to communicate with non-specialists. These visualizations are not only scientific tools but can also be considered as artistic projects in their own right. The urgency of visualization in this area has generated an interdisciplinary space between science and art.

· Experimentation. Artists are experimenting with the potential of machine learning to provide new instruments for artistic creation. One important way in which artists engage with technological black-boxes is to explore their potential uses through experimental action. This line of work is closely connected to the development of a “maker” culture in media art. Artists insist on making their own creative instruments, and they look at artificial intelligence as a potential system of artistic tools.

· Histories and Forms. Machine learning art has developed a wide range of practices. How can these practices be described and mapped? What are the different kinds of idioms and forms of machine learning art? What is their relationship to art practices that do not involve machine learning?

· Critique. Many artists who engage with machine learning in the creation of art also reflect upon the role that machine learning plays in wider society. Machine learning algorithms play a central role in modelling data users in ways that reflect broader patterns of economic power, and shape and reinforce discriminatory attitudes towards gender, sexual identity, race, and class. How can machine learning art itself engage with and transform the social uses of algorithms?

· Art Curation and Analysis. Machine learning, with its capacity to organise and map phenomena in previously unknown directions, promises to deliver novel ways of curating and analysing art. In what ways might machine learning contribute to new forms of curatorial practice, new ways of analysing style and form, and different ways of conceiving the history of artistic practices?


Richard W. Allen, City University of Hong Kong.

Tomás Laurenzo, City University of Hong Kong.

Héctor Rodríguez, City University of Hong Kong.

We will publish the book with a reputable academic publishing house. We aim to release the publication in 2020.

Full chapter submission deadline: 15th July 2019.

Paper acceptance notification: 1st October 2019.

Contributions reviews returned to authors: 1st November 2019.

Revised contributions submission: 1st January 2020.

We will accept submissions of papers between 3.000 and 8.000 words submitted as a word document.

Please submit your full chapters via email providing on the email body:

1. ​Title of your contribution

2. Abstract (maximum of 500 words)

3. Author(s) information: Last name, first name, role, institution and mail

4. Corresponding author.

The proposals must be in English and submitted as a word document (only one file), with the aforementioned style. Documents are to be sent to artmachines@laurenzo.net

Each contribution must be original and unpublished work, not submitted for publication elsewhere. In the case of article based on shorter conference papers, a section explaining the original contributions of the submitted chapter must be included.


Please use the author-date system of reference, using parenthesis in the text accompanied by a reference list at the end of the article from Chicago Manual of Style 17. Please use CMS17 for all matters of style and for detailed breakdown of reference format. Submissions that do not use CMS17 will not be considered.

Text citation:

……….action-reaction (Bloggs 2011).


Bloggs, Joe. 2011. Why Matter Matters. New York: Advantage Books.

For additional information or clarifications please contact artmachines@laurenzo.net