Week 3 (Aug 27) – Updated!


Personal examples of generative art

SamuelPraveenNaomiRachaelJoeyAlinaSu Yang

These are the links to all your personal examples, good for all of you to look up for details and inspiration.


Cognitive Aspects of GA:
Algorithmic Thinking and Procedural Literacy

Lecture Slides

Further Reading
Dejan Grba – 2020 – Deriving Sense: Cognitive Aspects of Artefactual Creativity
My recent paper on the cognitive aspects of generative new media art.

Lecture Summary

A deeper understanding of the cognitive aspects of generative methodology is instrumental for the artists’ critical and creative approach, and for recognition of their achievements. Similar to other (new media) art disciplines, generative creativity requires ingenuity, multidisciplinary research, critical understanding of accumulated knowledge, and learning.

Modes of Thinking: Designing Algorithms and Procedural Literacy
The development of generative art projects involves two complex modes of thinking.
One is matching and interfacing the algorithmic and the unpredictable elements into a coherent system. It relies upon experience, knowledge and intuition to anticipate if the performative qualities of the system will match a desirable proportion of several requirements we covered in the previous lecture.
Another mode is the construction of algorithms as multi-purpose or specific task-oriented tools, which requires procedural literacy regardless of media in which you work, and programming skills if you are using creative coding. Procedural literacy, the “ability to read and write processes, to engage procedural representation and aesthetics,” (Further reading Reas et al. 2010, with a lot of examples) implies that programming is not a mechanical task but an act of dynamic communication through symbolic representation of the world.
Algorithm design runs in three steps:
– Deconstruction of certain phenomenon into a set of signs/components which describe it properly,
– Resolving that set into pure syntax of the chosen medium (removing the semantic layer), and
– Translation of the syntax into a series of operations/actions with(in) the chosen medium
(for example, within the coding environment such as Processing).
This three-step process is equivalent to the core technique of the observation-based drawing, painting or sculptural modelling. You have probably been going through it intuitively in developing your works, but it is important and beneficial to become consciously aware of them, so you can systematically study them in your work and improve your creative skills and techniques.

Broader Aspects and Considerations
This counterintuitive disassembly of experience requires a spectrum of cognitive skills which include:
– The sense for selecting an interesting/relevant phenomenon,
– The ability to assess if that phenomenon can be algorithmized under given conditions,
– Imagination and flexibility of reasoning,
– Distinguishing between the rational and irrational aspects in our mental concepts of natural phenomena, and
– The attention to the scope and limitations of the algorithmic system.
Keep in mind that whenever a previously incomputable natural phenomenon or creative process gets algorithmized, it is human intelligence doing the complex job of scrutinizing, symbolically structuring and encoding it into a functional system. The complex relationship between human creativity and human-built emulation of creativity reveals the essential flexibility of the human mind which can allow itself to be influenced by technology, and simultaneously absorb, repurpose, transform and invent it.
Creativity in general integrates three modes of learning:
– Sensual (perception, abstraction and insight),
– Interactive (physical experience and coordination), and
– Symbolic (procedure and language for understanding and communicating the process).
Sensual and interactive modes have been traditionally favored in art education, while the symbolic mode is more prevalent in art research and communication than in production. For the artists who use coding, the symbolic conditionality of programming environments is often a generous source of frustrations, but also a drive for improving their precision and discipline.

Within the context of new media art, procedural thinking faces some systemic challenges. The conceptual constraints of programming languages and hardware architectures can impose certain solutions and unwillingly spin the creative process. The fixed performative capabilities of the hardware can reflect in roughness and lack of spontaneity (Reading assignment 1: Watz 2010). These are compounded with current issues of the creative AI such as:
– The various modes of anthropomorphizing (Further reading: Mitchell 2019),
– Translation of sociopolitical biases into the training datasets,
– Misleading discourse about the capabilities and consequences of the AI,
– Misconceptions about the artistic creativity in relation to the AI, and
– Insensibility to the authentic creative potentials of the AI.
Ultimately, there are the undecidable problems in computability theory, and the more general limits of mathematical formalization established in Gödel’s incompleteness theorems.

To leverage the creative potentials of generative methodology, it is necessary to understand its expressive requirements, cognitive skills and abilities it involves, and its challenges in limitations related / specific to various media and technical environments.


Dejan Grba – 2017 – Analogies (When I Draw a Song for a Film)

Dejan Grba and Philippe Kocher – 2019 – Study 7/0
Web Page
Presentation Slides

Further examples to look up

Examples of generative art, design and architecture in Casey Reas, Chandler McWilliams & LUST – 2010 – Form+Code
Examples with code

Michael Najjar – 2008-2010 – High Altitude
Meaningful input + output: Mountain shaped by stock exchange index performance. In digital GA that use creative coding, statistics is often a powerful tool because it can reveal or imply certain trends.

Roman Signer
Consider the appeal and thrill of ludic, proto-scientific experiment driven by curiosity to actually taste—not just imagine—what will happen within certain preconceived but not fully controlled circumstances, and to build concepts and predictions from the incoming information.

Walter DeMaria – 1977 – Lighting Field
Applying the principles of scientific experiment, similar to Signer.
But please note the conditions and disclaimers for visiting the Lighting Field site to see how easily a “rebellious” art practice gets commercialized, mainstream and restrictive.

Related to Alina’s Initial Ideas

Bartholomäus Traubeck – 2011 – Years

Yuri Suzuki


Create Exploratory Generative Study

Focus on the main principles and aspects of generativity that we discussed in Week 2 and Week 3:
Logic of a Generative Artwork and
Algorithmic Thinking and Procedural Literacy.

Explore them through developing your work within one chosen medium: image, sound, text, video, animation, physical object/installation, web-based work, game, etc.

The work can be
– Analog or digital,
– Interactive or non-interactive.

Aim for
– Simplicity and clarity.
– Cultivating your approach to project development:
concept>quick exploration>prototyping>testing>finalizing.
– Learning through making.

Present your ideas to the class next week 3 Sep.

Document your progress weekly at the OSS Process category.

Final presentation of the work due Week 7 (24 Sep).

Work Study

Processing 2: Sound

Please download the class activity before the lesson begins.

processing tutorial 2 – Sound_compressed

Download Class Activity

Generative sketch consultations