Readings and Findings
Readings ONE (BOOK)
After reading Invisible Cities by Italo Calvino, I notice a pattern of writing which allows me to imagine the city vividly although it was the same place described by Marco Polo. Below is a series of findings about how to section information so that users can imagine more effectively.
I categories the sections according to how I sectioned my compiled survey:
Movement (compiled in survey) : Movement in the city (Invisible Cities by Italo Calvino)
Physical appearance (compiled in survey) : Features and details of the City (Invisible Cities by Italo Calvino)
Behaviour (compiled in survey) : Behaviour in the city (Invisible Cities by Italo Calvino)
Example One: Continuous Cities 1
Example Two: Cities and the dead 2
Example Three: Cities and the desire 2
After doing this analysis of how details can prompt a better imagination of stories and in this case cities. I realised that this could be used for the organisation of the details rather than the creation of details/forms.
Readings TWO (Article)
Title: Ten Questions Concerning Generative Computer Art by Jon McCormack, Oliver Bown, Alan Dorin, Jonathan McCabe, Gordon Monro and Mitchell Whitelaw
Here are some quick summarized points of the paper:
Question 1: Can a Machine Originate Anything?
Philosophers such as Anthony O’Hear have argued that, no matter how sophisticated or independent, machines cannot originate art, because art “in the full sense is based in human experience” and requires a communication between artist and audience drawn from that shared experience. Computer works that mimic this communication are only parasitically meaningful; they derive their meaning from an analysis of existing art objects, not directly from human experience.
Question 2: What Is It Like to Be a Computer That Makes Art?
If the art object is simply an aesthetically appealing form, then consciousness seems unnecessary. On the other hand, if art requires a social or cultural context in which to operate, it probably also requires conscious intent on the part of the artist.
Question 3: Can Human Aesthetics Be Formalized?
Even for systems capable of voluminous output (e.g. image evolving systems), the aesthetic variation over all outputs is narrow, indicating that aesthetic responsibility in current generative art resides primarily with the artist rather than the system that generates the work.
Question 4: What New Kinds of Art Does the Computer Enable?
Art traditionally requires a mysterious process of creation unique to the artist, the artist’s skill and special way of seeing the world. Generative art has explicit mechanisms; if the process is entirely known it can be considered “mechanical” and repeated exactly across boundaries of space, time and culture. If art can be made mechanically, what is so special about artists
Question 5: In What Sense Is Generative Art Representational and What Is It Representing?
Is there a continuum or a hard distinction between generative art and data visualization? If generative art uses real-world data, what are the ethical and political implications of the artist’s chosen representations?
Question 6: What Is the Role of Randomness in Generative Art?
In science, statistical modeling is a powerful method, but randomness is sometimes used as a way of working around ignorance or incomplete knowledge: If we truly knew all the forces at play when we tossed a coin, we would know the result. If a generative artist has complete knowledge of the art-making process, why resort to randomness?
Question 7: What Can Computational Generative Art Tell Us about Creativity?
Two fundamental types: combinatorial creativity, in which fixed primitive elements are combined to create new structures, and emergent creativity, where new structures or symbol primitives emerge.
The processes underlying works can also be very insightful, leading to highly original, creative work. We have already raised the issue of how natural, physical and chemical processes form the basis for many generative artworks. Does the creativity reside primarily in the original phenomenon, the algorithm simulating it or in the artist’s interpretation of it?
Question 8: What Characterizes Good Generative Art?
Understanding an algorithm’s subtlety or originality opens a fuller appreciation of the eloquence of a generative work. However, this is a significant problem for most audiences, reinforced by focusing on the surface aesthetics of the art object as is often the case in computational generative art, where the computational process is rarely directly perceptible.
Our purpose with this question is not to narrowly or subjectively define “quality” in generative art but rather to provoke a better understanding of its defining aspects.
Question 9: What Can We Learn about Art from Generative Art?
Generative art redistributes traditional notions of authorship and intention, introducing autonomous processes and agents and allowing us to appreciate the systemic aspects of contemporary art production, exhibition and consumption from an illuminating perspective.
Question 10: What Future Developments Would Force Us to Rethink Our Answers?
History shows that optimistic speculation about technology is often ill-founded. Many automated “creative decision- making” systems found in current technology limit human creative choice rather than enhance it. Attempts to achieve open-ended evolution and generative complexity in software have so far proven
The Factory by Driessens & Verstappen was one of the works mentioned within the article that intrigues me the most becuase each sculpture is different, special and transient, but fabricated autonomously without human intervention. The artist was able to make a ‘new’ wax sculpture every 6 minutes and this sculpture will be photographed as a process for their documentation.
Step 1: In the transformation room a robot arm takes an amount of fluid wax and pours this into the water bassin. When completely solid, the new shape is scooped onto a conveyor belt, and placed in between ventilators to dry.
Step 2: When dry, the shape continues its way through The Factory. In the documentation studio, it is recorded on tape while it passes the camera.
Step 3: View in the documentation room through the the camera viewfinder. A wax shape is just passing by. Subsequently the shape is moving to the balcony, where the shape is presented to the public. It can be observed in detail here, before it finally disappears in the melting pot again.
Step 4: Finally the shape is moving towards the wax melting pot. Several minutes after it came into the world, the form is destined to disappear again and transform itself into other equally transient shapes.
Link about The Factory (robotic installation) by Driessens & Verstappen : https://notnot.home.xs4all.nl/factory/infofactory.html#docroom
Video link about The Factory: https://www.youtube.com/watch?time_continue=108&v=BVKw7HDXRqw
Readings THREE (Article)
Readings FOUR (BOOK)