Artificial Intelligence Art
|Erasmus code / ISCED:||(unknown) / (unknown)|
|Course title:||Artificial Intelligence Art|
|Name in Polish:||Artificial Intelligence Art|
|Organizational unit:||Faculty of Mathematics, Informatics, and Mechanics|
General university courses
General university courses at Faculty of Mathematics, Informatics, and Mechanics
|ECTS credit allocation (and other scores):||
|Type of course:||
This lab-focused course investigates how AI is disrupting the creative processes and changing how we view the world, with a particular interest in memory and algorithmic representation. The scope of the course ranges from the recent developments in creative deep learning technologies to the use of algorithmic tools in implementing interdisciplinary arts and science projects.
Recruitment for the course will be conducted separately, by applications. Students of mathematics, Computer Science, bioinformatics and Machine learning who pass this course may obtain OGUN (human/social science general university course) credits.
Artificial intelligence (AI) has developed significantly in the recent times with a variety of deep learning architectures. In this rapid prototyping team-focused course, we study and reimagine the implications of AI, bias, and algorithmic justice within creative use and design process. Especially, during the semester, students will create interdisciplinary arts and design projects with the central theme that memory, dreams, and nation-state collective narratives being defined through rapidly developing technologies like GPT-3, Stable Diffusion, and others.
The focus will be on the challenges presented by the artistic creation of using AI language and vision models to define individual and collective visual memory, or other types of data and models. We will survey and have hands-on experiences with many AI tools, as demanded by students interests and projects, such as speech to text, text to image, image to image, and image to video, and others. For examples, sentences and phrases are translated into images extensively sourced from various repositories of databanks. Programming, prompt engineering, and experimenting with models, software, datasets will be central. In the process, the course will look at the issues of algorithmic bias, and the aesthetics of AI with a strong focus on current societal issues.
Through a team based rapid prototyping, Dr. Neo Christopher Chung from the University of Warsaw and Dr. Ellen Pearlman, visiting Fulbright Scholar in Art, Media, and New Technologies from MIT/ThoughtWorks Arts, will conduct this special colab atthe University of Warsaw. Find out more about the Art-A-Hack (https://artahack.io) rapid prototyping approach.
How to apply:
This special colab is by application only. Email to email@example.com and firstname.lastname@example.org.
Describe your project idea or your particular interest in this colab concept. We welcome applications with diverse backgrounds. No prior knowledge with AI art necessary. When we receive your applications, we will match you up with others in team settings.
Your studies, skills, and background
Your project ideas or interests of how to contribute.
Art Hack Practices by Victoria Bradbury, Suzy O’ Hara
Collective Wisdom: Co-Creating Media within Communities, across Disciplines and with Algorithms by Katerina Cizek, William Uricchio
AI Art: Machine Visions and Warped Dreams by Joanna Zylinska
Defining AI Arts: Three Proposals by Lev Manovich
Understanding the creative AI tools and technologies
Learning how to work within interdiscplinary teams
|Assessment methods and assessment criteria:||
Course participation, homework, final project
Classes in period "Summer semester 2022/23" (future)
|Time span:||2023-02-20 - 2023-06-18||
see course schedule
|Type of class:||
Lab, 45 hours
|Coordinators:||Neo Christopher Chung, Ellen Pearlman|
|Group instructors:||Neo Christopher Chung, Ellen Pearlman|
|Students list:||(inaccessible to you)|
Students of mathematics, Computer Science, bioinformatics and Machine learning who pass this course may obtain OGUN (human/social science general university course) credits.
Copyright by University of Warsaw.