• Deadline:
    Feb. 20, 2018, 11:59 p.m.
  • Location:
    Centro Contemporáneo de Creación de Andalucía (C3A) , Córdoba, Spain

Presented by: Centro Contemporáneo de Creación de Andalucía (C3A) & School of Creative Media, City University of Hong Kong.

Symposium Director: Héctor Rodríguez
Associate Director: Tomás Laurenzo

Dates: March 15 – March 17

Website: http://arsincognita.concept-script.com/

Ars Incognita – poetics of artificial creativity is a symposium bringing together artists and scholars to consider the impacts of machine learning on arts and culture. With a hybrid research and education focus, we aim at drawing the attention of artists, researchers, and the general public to critical issues around machine learning.


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, insurance, search engines, online movie and book recommendations, machine 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 on how citizens can 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 people?

We are calling for artists, scientists, researchers, and designers interested in giving a 15 to 45-minute long presentation on one or several of the following areas of interest:

Visualization. Scientists themselves are already developing innovative ways to visualize different aspects of machine learning. The aim is to understand those technologies better and to communicate with non-specialists. Their visualizations are not only scientific tools. They 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 and art historians are experimenting with the potential of machine learning to provide new instruments for artistic creation and analysis. Their aim is to discover how these technologies can change how we produce and analyze art. 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.

Critique. Artists and humanists are increasingly considering the social and ideological aspects of machine learning. Many of these aspects and consequences are not intended by those who design these technologies. Questions here involve the impact of machine learning on gender, sexual identity, race, and class, for instance in the form of data-based discrimination. Machine learning implementations often produce models of users, and these models embody broader patterns of economic and cultural power.

Applicants can fill in the online form: