Brief

This course considers the relationship between emerging design technologies and environmental science from a critical and computational perspective. It is interested in the application of artificial intelligence to ecology as a means of discovering wildly performative para-architectures. The tension between AI and global warming as the 21st century’s most defining technology and crisis, respectively, frames a near future for young designers where the existential threat of environmental collapse is mixed up with the delirious optimism of neoliberal technology to produce a multiplicity of design attitudes oscillating between technophilia and technophobia, dystopia and utopia, posthuman and superhuman, living and non-living, progressive mutualism and conservative individualism, retro-agrarianism and techno-futurism, and other arrays of hyperpolarized value systems.

Confronted with the intoxicating yet overwhelming conflation of crisis and opportunity, we will resist ideology and dismantle the binary categories of man vs nature and nature vs technology into a constellation of hybrid conditions.  Leaning heavily on the work of Gilles Deleuze and Félix Guattari to productively deterritorialize our habits of thought, we will operate as ambiguously positioned design researchers working in the cracks between architecture, ecology, data science, and philosophy. In particular, we will develop design techniques and novel workflows that cluster and cross-pollinate components of AI with ecological datasets to generate speculative but tightly controlled design experiments which reject solutionism in favor of feral environmental aesthetics. The course will manipulate multiscalar abiotic and biotic information (for example fluid dynamics, solar radiation simulations, biomass distributions) using AI tools (such as evolutionary algorithms, machine learning, and neural networks) to produce assemblages that are curious how humans can learn from non-humans, how living systems can learn from non-living systems, and vice-versa.

The semester will occur in three Modules. Module 1 will consist of a series of paired readings from key influential AI and ecological thinkers. Module 2 will consist of technical workshops and computational experimentation to familiarize students with contemporary AI tools. Much of the work will be conducted through Grasshopper’s AI add-ons (Galapagos, Dodo, Monolith, Millipede, Crow, Owl, and LunchBox, among others). Students will also be exposed to AI tools less conventionally used within the discipline of architecture, namely Generative Adversarial Networks (GANs). Module 3 will apply the historical, theoretical, and critical positions of Module 1 to the computational proficiencies of Module 2 to generate a final model that expounds upon the concept of Postnatureness. Students will leverage their representational skills using digital and/or physical methods which blur the boundary between virtual and actual. Notes: no previous experience with Grasshopper or AI is required; students can expect to spend up to $100 on physcial model materials.

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Selected Course Bibliography:

“Geographies of Sensitive Matter: On Artificial Intelligence at Urban Scale,” B. Bratton

Machinic Hallucinations, M. del Campo, N. Leach

The Second Digital Turn, M. Carpo

A Thousand Plateaus, G. Deleuze, F. Guattari

The Ecological Approach to Visual Perception, J.J. Gibson

Architecture in the Age of Artificial Intelligence, N. Leach

Ecology without Nature, Timothy Morton

Order out of Chaos, I. Prigogine, I. Stenger

On Growth and Form, D. Thompson

“Computing Machinery and Intelligence,” A. Turing

A Stroll through the Worlds of Animals and Men, J. Von Uexküll

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Learning Outcomes:

1. Develop an understanding of key concepts and thinkers related to the history and theory of ecology and artifical intelligence

2. Apply the dialectic method as means of creating disjunctive synthetic aesthetics of human and non-human relationships within and beyond the discipline of architecture

3. Gain facility of emerging design technology tools to simulate and manipule flows of energy towards speculative digital and/or physical models which engage the environmental sciences from a critical and computational perspective.

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