Artificial Intelligence, Machine Learning and Generative Models in the Arts and Design | Leonardo/ISAST

Artnodes Journal: Artificial Intelligence, Machine Learning and Generative Models in the Arts and Design

Dates or Deadline: 
1 March 2020 to 20 March 2020
Contact: 
Pau Alsina

Deadline: 20 March 2020
Submissions to be published in issue 26 (July 2020)

EDITORS:

Ruth West
Professor/Director, xREZ Art + Science Lab (http://xrezlab.com), College of Visual Arts and Design, College of Engineering, College of Sciences
University of North Texas
Member, ACM SIGGRAPH Digital Arts Community Committee
Board Member and LEAF Chair: Leonardo, the International Society for the Arts, Sciences and Technology
ruth.west@unt.edu

Andres Burbano
Associate Professor, Department of Design, Universidad de los Andes
PhD in Media Arts and Technology | University of California, Santa Barbara
burbano@gmail.com

The pace of development and usage scenarios for artificial neural networks is accelerating, made possible in part by access to large-scale training datasets combined with massive parallel GPU computing. From legal sentencing recommendations to autonomous vehicles, facial recognition and surveillance, personalized medicine and learning, conversational agents embedded in everyday objects and real-time intelligent responsive environments, we are transforming all aspects of human endeavour through the application of machine learning (ML), artificial intelligence (AI) and generative models. This gives rise to an urgent need to envision and understand the societal impact of these innovations, and provide greater interpretability of neural networks and transparency with regard to the underlying biases grounded in the very data that enables their utility.

Explorations of the relationship between AI and the arts have existed throughout the historical development of artificial intelligence, such as Hofstadter's early work at the intersection of computing, AI, the visual arts, music, and poetry. With the democratization of software libraries, access to commodity hardware for GPU computing and open access to artificial neural network models, we are witnessing exponential growth in the application of ML and AI in all the domains of art (visual, sonic, performing, spatial, transmedia, film, and narrative). As artists and designers create never-before-heard sounds and images of never-before-seen faces, explore new processes for human-machine co-creation and infinitely parameterize the design of objects, are we at the dawn of a new paradigm in creative practice? Or can this explosion of activity be considered part of the continuum of generative art practices spanning the history of human creativity and the evolution of culture? In this issue, we pose the question, does generative and machine creativity in the arts and design represent an evolution of “artistic intelligence”, or is it a metamorphosis of creative practice yielding fundamentally distinct forms and modes of authorship?

Topics

For issue 26 of Artnodes, we are calling for articles that explore the past, present, and future of generative and machine creativity, or ML and AI in all the domains of art and design, including:

- The relationship between autonomous cognition and the arts, and its current or potential impact on the evolution of general AI.

- Classification schemata, taxonomies and ontologies providing a lens onto contemporary approaches to AI in the arts and design, and views on its past and future.

- Elucidating the underlying dimensions of communities of practice within the exponential growth in the number of creative practitioners utilizing ML/AI.

- Defining the nature of ML/AI as a medium and its relationship to prior media and artistic instruments.

- Are the questions raised by the generative arts still relevant in the practice of AI, the arts, design and music?

- Curatorial practices addressing contemporary applications of AI in the arts and design, and their relationship to curatorial practices in traditional artistic modalities.

- Evaluating the computational creativity and aesthetics of ML/AI art and design.

- Ethics, bias, the nature of authorship, and equal access in relation to applications of ML/AI in the arts and design.

- Case studies presenting creation in any artistic modality utilizing machine learning, artificial neural networks, and/or artificial intelligence.

- The aesthetics of non-human creation or human machine co-creation.

- ML/AI in responsive intelligent environments and public art.

- Post human creativity and creative artefacts.

- The future of human creativity in an era of creative AI.

- ML/AI tools and methods (new or existing) in the arts and design.

- Embodied autonomous cognition and embodied AI.

- Inclusive practices, diversity, gender and identity in ML/AI in the arts and design.

- Emerging marketplaces for artefacts and processes resulting from ML/AI in the arts and design.

Submission process

To submit an article, register an account on the Artnodes site and follow the submission instructions. You can review the author guidelines and submission checklist at https://artnodes.uoc.edu/about/submissions/

Queries

For problems with the platform: publicacions@uoc.edu
For questions about how the journal works: artnodes@uoc.edu

About Artnodes

Artnodes is an open-access academic journal produced by the UOC since 2002. It is published twice a year, in June and December. Its articles come from public calls for scientific articles and are submitted for blind review by experts in the relevant subject area. The journal is indexed in Q2 in the Scimago Journal & Country Rank (2016), Carhus Plus+, Scopus (Elsevier), MIAR, Latindex, FECYT Seal of Quality, etc. You can find more information here. You can find more information here: https://artnodes.uoc.edu/about/#indexing.

Grow With Leonardo