A Bottom-Up End-User Intelligent Assistant Approach to Empower Gig Workers against AI Inequality
Jaylexia Clark
Meng Jiang
Yang Yang
Tamara Kay
Danielle Wood
Jay Brockman
Published at
CHIWORK
| Durham, NH USA
2022
Abstract
The growing inequality in gig work between workers and platforms
has become a critical social issue as gig work plays an increasingly
prominent role in the future of work. The AI inequality is caused by
(1) the technology divide in who has access to AI technologies in gig
work; and (2) the data divide in who owns the data in gig work leads
to unfair working conditions, growing pay gap, neglect of workers’
diverse preferences, and workers’ lack of trust in the platforms.
In this position paper, we argue that a bottom-up approach that
empowers individual workers to access AI-enabled work planning
support and share data among a group of workers through a network of end-user-programmable intelligent assistants is a practical
way to bridge AI inequality in gig work under the current paradigm
of privately owned platforms. This position paper articulates a set of
research challenges, potential approaches, and community engagement opportunities, seeking to start a dialogue on this important
research topic in the interdisciplinary CHIWORK community.