Temporal Marginalisation by Ride-sharing Platforms
Tensions emerge when algorithms designed to match supply and demand, such as on-demand service platforms, do not account for the way time is differential. Automated on-demand services contribute to, and normalise, temporal orders that marginalise ‘just-in-time’ workers. This talk considers how platforms for ride-sharing can undermine the work of drivers when they do not support mutual, transient awareness of different temporalities, drawing on our work in India and Namibia in the context of other literature.

Julie Hui
School of Information, University of Michigan, USA
Watched, but Moving: Negotiating Gendered Mechanisms of Control in Gig Work
Women gig workers are impacted by algorithmic and non-algorithmic control practices in the context of home service platforms in Bangalore. Control is enacted through location tracking, communication monitoring, customer ratings, among many other practices commonly deployed by gig work platforms. However, these mechanisms of control impact workers' lives in myriad ways beyond just the conditions of work. Women workers negotiate their identities and sense of agency through the visibility afforded by platform control. We question, How do platform control mechanisms reinforce or challenge entrenched socio-cultural structures? How do women gig workers negotiate platform control in ways that enhance personal agency?

Naveen Bagalkot
Srishti Manipal Institute of Art, Design & Technology, India
Nervo Verdezoto
School of Computer Science and Informatics, Cardiff University, UK

The Invisible Work of Maintenance: Challenges and Implications for the Future of Frontline Health Work
As per the imagination of the future embedded in the National Digital Health Blueprint, the health workers in India are seen as data-collectors and content-distributors. As we begin to imagine ‘Future of Health Work’, it is important to pause and really understand how this work happens, bringing new sociocultural and technical insights to system design. Based on a case study of frontline health workers in Karnataka (South India), we describe how Frontline Health workers often act as invisible “maintainers” of community health infrastructures caring for themselves and the community. We discuss the implications of what kind of futures we can imagine in community health. 

Carlos Toxtli
West Virginia University, USA
The AI industry has powered a futuristic reality of self-driving cars and voice assistants to help us with almost any need. However, this industry has also created systemic challenges. For instance, while it has created new labor platforms for improving machine learning algorithms, several workers on these platforms are earning less than minimum wage. In this talk, I will discuss not only how AI can be benefitted from crowd workers, but also how crowd workers can be benefitted from AI to improve their wages, well-being, and work.

When: February 23rd 1100 EST/1600 GMT/1800 CAT/2130 IST
Where: https://ucl.zoom.us/j/91854315774

Warmly,
Neha & Akhil