Shading Gate

2021

Bridging the boundaries of Sunset Boulevard in Los Angeles

#PhysicalDesign
#AI
#DesignComputation
#ClimateChange


^Instructor
Charles Waldheim (Harvard GSD)

^Team
Individual

^Tool
RunwayML, Rhino, Grasshopper, Adobe Illustrator / Photoshop / After Effects

* image credit: Ed Ruscha

PROJECT CONTEXT & PROBLEM SPACE

Los Angeles has severe shade disparities, being caused by many intertwined factors: the original prefection of sunlight, the lack of trees, wealth disparities, racial inequity, and more. While climate change is happening, the raising temperature has urged us to take actions to seek for ways of adding shades.
The studio takes Ed Ruscha’s photo collection documenting LA’s famous street, Sunset BLVD, as the database to study the evolvement of streetscape of LA. As we take Ruscha’s photos as our starting point, potential spatial qualities for shades are analyzed and implemented through machine learning and other computational methods. The experiment of machine hallucination creates novel possibilities and opens up the interesting discussion on the potential future for spatial design.

The project takes UCLA campus entrance, located along Sunset BLVD, as a prototype for the experiement of shading up LA and bridging over the boundaries of different neighborhoods, population, and ownerships. It is a new gate introducing people into this interesting transition from quiet and wealthy residential neighborhood, Bel Air and Westwood, to the dynamic public university campus life. The methodology hopefully can be deployed on other parts of Sunset BLVD and the city, creating the juxtaposition between neighborhoods, ownerships, classes and population groups, blurring the boundaries, changing the rupture conditions, bringing the shade and abundant resources to the public realm, and extending the dynamics to the underused places along Sunset Blvd.

“Ruptures”

there are many ruptures and unexpected sudden changes along Sunset BLVD

Ed Ruscha Curation

The Ruscha database for StyleGAN training is curated based on edge, rupture, and neighborhood locations within a 20-meter buffer zone.

StyleGAN: Latent Space Study

how does the machine imagine the space to be?

Pilot Site Map

UCLA Entrance
34.078262, -118.439417

Site Shading Condition

How Does It Work?

Computational Methodology
Latent Space Img ︎︎︎ Customized Grasshopper Script: img to depth map to 3D ︎︎︎ Spatial Design

Design Outcome

Don’t leave right away! Here are some of my reflections...

This was an early project testing how we can involve AI and machine minds into design process - considering the boom of AI for public audience happened in the time of 2022 while this was a project in early 2021 - during the process of which I struggled a long time pursuading myself how to build the logic and meaning between machine generated visual and the design outcome. Ironically, I chose the topic of this project to focus on the social and physical raptures of neighborhoods, yet myself felt the huge rapture between design and technology along the way. Why would we use it? Where do we draw the line between human intellegence and machine minds? Does the technology in some ways limited the design?

After two years of industry work, and tested in-house AI generative tools for rounds in projects, I finally felt comfortable using it, a little bit more - not being emotionally attacked by it dragging me along the design process, but turning it into an additional tool and assistant to accelerate work efficiency. There is never a singular, flawless solution to a design problem, and it's important to remember that we are not in competition with one another - here I mean, us and machines.

I believe in the humane side of design that can never been replaced by machines by going back to the authenticity of ourselves, emotional strengths, and empathy.