  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.
