image above: at the Generative Center in Lugano Besso, 2024, Jan Eckert.
A visit to our partners at the Generative Center in Lugano Besso turned into a rich dialogue exploring the creative potential and challenges of machine learning. In conversation with a diverse group of experts – Felix Bachman Quadros, co-founder of the Generative Centre, sociologist and writer-photographer Jean Odermatt, contemporary art critic and educator Flavia Pelosi, and photographer Erica Manole – we explored several critical aspects of AI’s impact on creative processes. Their diverse perspectives, spanning technology, sociology, art criticism and practical art-making, enabled a multifaceted exploration of how AI is reshaping creative practice in the digital age:
Acceleration
In our discussion on creative potential and the acceleration of creative output, we explored how AI tools are fundamentally changing the speed and scale of creative production. This acceleration creates new opportunities for rapid prototyping and iterative design processes that were previously unimaginable, while raising questions about the value of creative gestation and reflection in artistic practice.
Resources
The tension between creative production with reduced human resources and the high energy demands of machine learning platforms emerged as a key consideration. This paradox highlights a key sustainability issue: while AI can democratise creative tools and reduce human labour, its significant environmental footprint challenges us to critically examine the true costs of this technological advance in the context of responsible innovation.
Creative processes
We have explored how the restriction of creative processes to prompting represents a significant shift in artistic practice. This constraint is reshaping the creative landscape, forcing creators to develop new skills in prompt technology while potentially distancing them from traditional hands-on creative techniques. This shift raises fundamental questions about the nature of creativity itself and the role of physical engagement in the creative process.
Next Generation’s Responsibility
As AI technologies become increasingly embedded in creative processes, the next generation of creators will need to develop new frameworks for ethical creation that balance technological advancement with cultural preservation. A critical challenge emerges: how can future creators maintain artistic judgement when their primary exposure to design and art is through AI-generated output rather than foundational education? This generation must pioneer new collaborative models that harmonise human creative capacity with machine generative capabilities, while anchoring their practice in artistic and ethical principles that transcend mere technical interaction with AI to embrace humanity’s rich cultural heritage.
On-screen perception
The limitation of creative output to on-screen perception has sparked a fascinating debate about the multi-sensory nature of human creativity. Current AI technologies cannot fully replicate the tactile, spatial and physical dimensions of creative expression of embodied experiences. This limitation highlights the importance of considering how multimodal perceptions of creative output could be better integrated into future AI developments to create more holistic creative experiences.
Intellectual Property
Our conversation about IP infringement by AI companies highlighted the complex legal and ethical challenges facing the creative industries. The practice of training AI models on copyrighted works is forcing us to rethink traditional concepts of authorship and ownership. However, this discussion also revealed an interesting parallel with the historical development of artistic practice, where sampling and re-sampling of creative output has been a fundamental element of creative expression and innovation across different artistic movements and periods.
Social inequality
Finally, we explored how social inequality due to limited access to AI tools is creating new digital divides. While AI promises to democratise creativity, the concentration of computational resources in the hands of large tech companies risks exacerbating existing social and economic inequalities. This dynamic poses a critical challenge to ensuring equitable access to creative technologies while promoting inclusive innovation in the digital age.