What are the Issues for Artist & Designers

December 9, 2024

Reflection by: Danai Fuengshunut

In November 2024, I held three short sessions to introduce WdKA art and design students to the development of generative AI. We looked at how this technology works and discussed some of the issues it raises. While some issues seem new, others have been part of the art&design practice in other forms. I’ll share some of the topics that were adressed during the sessions:

Environmental and Corporate Influence
Generative AI models require substantial computing power, consuming large amounts of electricity and impacting the environment. Much of this development is driven by a handful of large technology companies, which influences who can access these tools and under what conditions. For artists and designers, this concentration of power can limit creative freedom and availability.

Data, Bias, and Misinformation

Gen AI relies on vast amounts of data, raising concerns about privacy, surveillance, and the quality of the information used to train these models. Biased or racist outputs can result when AI systems learn from skewed data. Meanwhile, misinformation, fake news, and manipulated content influence what we can trust. While Gen AI amplifies these issues, they are not new; media and culture have always grappled with questions of responsibility and truth.

Equity, Labor, and Access
Equal access to the hardware, software, and skills needed for Gen AI is not guaranteed. In addition some workers in the industry face low pay and limited protections. Poor working conditions is an ongoing issue in creative fields that is now intensified by AI’s growing influence.

Copyright, Creativity, and Cultural Variety
AI challenges our ideas about ownership and copyright. It can reuse and remix content in ways that question who really “made” something. Many AI-generated outputs feel generic, which can limit the diversity of creative expressions and sideline less-represented cultures.

Some of these issues—environmental impact, corporate dominance, data bias, misinformation, labor conditions, inequitable access, copyright issues, and cultural homogenization—are not entirely new. They are part of a longer history in the creative practices. What AI does change is the scale, speed, and visibility of these problems these issues. There is a collective responsibility for all stakeholders involved in this development to push for fair use of data, more equal access, better labor conditions, and ways to protect unique cultural voices.