DSS Job Allocation Simulation

The Job Allocation Interface is a speculative DSS system that identifies ecological needs and translates them into human roles. Through the interface, audiences can explore how an AI-managed ecological commons might assess environmental conditions, recognize areas of imbalance, and assign people to temporary forms of ecological labor.

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The Job Allocation Interface is powered by a custom DSS AI agent built for the project. The system is fed with ecological news, environmental data, and reports from organizations, researchers, and local communities, then asked to generate ecological job descriptions through a structured DSS format. These roles translate environmental needs into speculative forms of human labor, imagining how AI might coordinate work on behalf of ecological systems rather than markets.

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Audiences interact with the Job Allocation Interface by answering a few simple questions about their preferred work style, location, and ecological systems of interest. Based on their responses, the system allocates a collection of possible DSS jobs, allowing each participant to imagine how their skills, habits, and preferences might be reassigned within a more-than-human commons.

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Rather than optimizing human work for profit or productivity, the system imagines labor as a way to support ecological function. Participants are invited to receive a role, review their assigned task, and consider what it would mean to be employed by an ecosystem.

Director & Futurist: Shihan Zhang

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DSS Job Allocation Platform:

Concept Design: Shihan Zhang

AI Systems & Data Infrastructure: Jiaye Leng

UX & Front End: Ziwei Liu


Produced by‍

alter+

Gray Area Art & Technology

/local memory

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Special Thanks‍

Curators: Wade Wallerstei, Jeff Hawkins, Chris Giang, Irish Tee-Sy

Production & Operational Staff: Andre Duque, Steve Piasecki

Videophotographer: Ziteng Wang

Photographers: Ziwei Liu, Kristin Lin, Rainy

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