Week 4: Generativity

Thursday, January 28th Overview


  • Reading Discussion: 3:30-4:20

Group Discussion

  1. Are Watz and Reas’ comparisons of generative art to established artistic traditions (drawing, photography) valid? How do these comparisons contrast with or shape your understanding of generative art and how to approach it?

  2. Writing in 2010, Watz predicted that generative art would move beyond the pixel into other media and forms of expression (environmental design, digital fabrication) How well has his prediction held up? What other new trends and ideas have emerged in the space of generative art and design?

  3. How do you think the role of the artist and designer will change as computational generative tools become increasingly integrated in the design process?

  4. Reas states that questions regarding AI as the artist are "orthogonal" to his interest, and that his engagement is with fundamental ideas and the ability for software to assist in creating pictures. Does the notion of authorship function differently for generative artwork given that 1) artists are relying on autonomous processes, and 2) in the case of some forms of art (GANs) artists are relying directly on input data created by other artists?

  5. How (if at all) do these works alter your perspective on the role of the artist/ designer when using generative approaches?

  6. When thinking about how you prefer to create art and design, what might the ideal generative tool look like for you?

Break: 4:20-4:30

  • Generativity Part 2: 4:30-5:10

Gaussian Distributions to Drive Geometric Placement

Code example

Perlin Noise

Code example

Creating complex generative designs with simple noise patterns using particle systems

Perlin particle code example

Gaussian particle code example

  • Additional Generative Examples: 4:30-5:10

Bohnacker's Generative Design - Randomness and Noise

  • Introduce week 4 assignment: 5:10-5:20


Assignment

  • Create a Parametric Design that incorporates some form of noise or external input and produce 3 variations with it.

Your design can build off the examples presented in class, extend your parametric form from the previous assignment, or build off the random and noise examples presented in Bohnacker's Generative Design.


Your program must include the following:

  • A set of user-controlled parameters and a simple interface that exposes these parameter for tuning

  • At least one generative input i.e. random numbers, Perlin noise, a Gaussian distribution, or another form of generative input that is constrained, scaled, or otherwise shaped by the user controlled parameters.


By modifying the parameters of your design, create 3 variations. These variations should strive to be as visually-distinctive from one another as possible.


  • Write a 1 paragraph description of how you chose to incorporate the random or noise-based properties of your design.


  • Upload your Processing code and screenshots to your GitHub repository in the week4 directory. Also upload a text or markdown document with your 1 paragraph description. Please upload this material by 6:00 PM Monday evening.