Any views expressed within media held on this service are those of the contributors, should not be taken as approved or endorsed by the University, and do not necessarily reflect the views of the University in respect of any particular issue.

Background

Digital practice often relies on digital process, workflows and methods of incremental development and transformation.

In particular Manovich points to design workflow and aesthetic through the lens of import and export[1], hybridity and reuse. Rather than form following function, as Droog design have it, “form follows process”.

These aesthetics of transformation, amplification and distortion can be found in the worlds of machine learning and artificial intelligence. What are the possibilities and challenges of new generations of text, image, music, code and video generators using machine learning models? What are the impacts on ethics, design, aesthetics, plagiarism, art, copyright and creativity of transformation, transfer, discrimination and diffusion?

What is the role of the designer, composer or performer working with these tools and models. Is creation in the curation, classification, prompts and process? What kinds of skills of evaluation and authorship do artists need in the age of AI?

This project aims to explore current, publicly available AI  and ML tools from a practitioner’s perspective, setting out to use these tools as part of the creative process, embracing their quirks and idiosyncrasies and allowing them to emerge with their own unique imprint. The final output could be an installation, performance or other experience.

One way to approach this is through diffusion and transformer models.

Where do we go from here?

What you will learn on this project:

  • How to engage with AI and ML tools as a part of an existing or new creative
  • How to work collaboratively with new technologies and within your group.
  • How to engage closely with reflection on process and creative practice and use your
  • reflection as part of an iterative process.
  • How to engage critically with questions of provenance/copyright/original work in the field of AI and create work that handles these questions responsibly

Suggested submission forms and formats:

  • A process study or set of process studies.
    This could take the form of a presentation of a practitioner’s or multiple practitioners’ process, a piece of academic writing or a reinvention of a piece of work as a prelude to your group’s larger project.
  • An installation of process driven artworks
  • A process driven performance

Suggested reading, resources and examples:

[1] http://manovich.net/content/04-projects/051-import-export/48_article_2006.pdf

css.php

Report this page

To report inappropriate content on this page, please use the form below. Upon receiving your report, we will be in touch as per the Take Down Policy of the service.

Please note that personal data collected through this form is used and stored for the purposes of processing this report and communication with you.

If you are unable to report a concern about content via this form please contact the Service Owner.

Please enter an email address you wish to be contacted on. Please describe the unacceptable content in sufficient detail to allow us to locate it, and why you consider it to be unacceptable.
By submitting this report, you accept that it is accurate and that fraudulent or nuisance complaints may result in action by the University.

  Cancel