Algorithmic justice / participatory researchequity in AI developmentParticipation documented

Good Systems skilled trades co-design project

Austin, United States

NSF materials describe research on co-designing AI-based tools with skilled trade workers to support rather than replace their labor.

participatory designhuman-centered AIproblem formulationdesignevaluation
Overview
Region
North America
Lead organization
Good Systems / University of Texas at Austin
Organization type
university
Technology group
AI-enhanced worker tools
Activity status
funded
Start year
2024
Last updated
Mar 25, 2026
Participation documentation
Participation mode
co-design with affected users and domain experts
Participants
skilled trade workers; researchers; students
Methods
co-design; worker interviews; tool prototyping
AI lifecycle stages
problem formulation; design; evaluation
Evidence summary
NSF materials describe research on co-designing AI-based tools with skilled trade workers to support rather than replace their labor.
Atlas assessment
Core · High confidence · evidence grade A
Uncertainty
Public evidence indicates that stakeholders directly shaped AI design, data, deployment, evaluation, or oversight; residual uncertainty concerns the exact degree of shared decision power rather than project existence.
Project details
Participation group
Co Design
Technology description
AI-enhanced worker tools
Funding
Not documented
Region of activity
local
Verification status
Mixed Verified

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