In this article, I have learned a lot of knowledge about generative art, and there are many parts I am interested in. Amy Goodchild unfolds a broad spectrum of information, showcasing the multifaceted expressions of generative art. Whether it’s the interplay between randomness and rules or the fusion of art and technology, I have developed a great interest in generative art.
- Randomness, in particular, strikes me as immensely enjoyable, offering a rich vein of creative inspiration. This process resembles brain development, where our subjective consciousness might be “misunderstood,” yet it operates within certain boundaries. It’s this balance between control and spontaneity in randomness that captivates me.
- The concept of pseudorandomness is equally intriguing—utilizing an algorithm with “seeds” to generate outcomes. The capabilities of p5.js code, from drawing and animating to experimenting with randomness, were revelations to me. Discovering the pseudorandom number generator (prng) opened my eyes to blending control with unpredictability, letting artists navigate creativity amidst structured chaos. The idea that “When the algorithm is given the same seed, it produces the same results each time” is something I’m eager to explore further, hoping to verify Goodchild’s observations in practice.
- True Randomness sounds interesting too, simulating a natural phenomenon (like rain falling on a window), and hopefully I can try this technique in the future.
I appreciate that she quotes many creative concepts and examples of artists, and vividly analyzes the connection between generative art, traditional art and reality. It’s very educational. For example, she mentions how the Proposal in Sol LeWitt’s Wall Drawing interacts with humans, as if the relationship between an artist and a computer algorithm is so similar. Another example is Studio Moniker’s project, which connects many interesting thoughts. The image of uncertainty in a computer program is like the interaction between people in a game, and at that moment I seemed to feel that the code is not cold, they can follow instructions like humans can ignore it. Goodchild’s Simulated Ecosystems are also interesting. Those elements simulate the phenomena of reproduction and extinction in the biological chain, and are presented in a way that breaks the grid, making the generative art more meaningful.
Amy Goodchild’s discussion on the relationship between generative art and abstract art is also interesting. Her exploration of generative art is not just about how technology creates art, but also explores the philosophy of art and how much control the artist has over the final work. Generative art blurs the boundaries between artist, tool and observer, so generative art is not just a set of code, behind it is also under the control of the artist and generated with the help of digital tools.
Interestingly, my first encounter with generative art was over a decade ago, though it was merely a fleeting moment then. At the time, I wasn’t aware that the images I admired were known as generative art. This semester, the term ‘Generative Art’ rekindled that dormant memory, offering me a long-awaited introduction to the concept. Thank you Will for sharing in the AI class.