6 papers
StylisticBias: A Few Human Visual Cues Drive Most Social Biases in MLLMs
Shaghayegh Kolli, Timo Cavelius, Nafiseh Nikeghbal +2
Multimodal large language models (MLLMs) are increasingly deployed in personally and societally consequential settings, yet the visual cues that shape how these models judge people…
FairFare: A Tool for Crowdsourcing Rideshare Data to Empower Labor Organizers
Dana Calacci, Varun Nagaraj Rao, Samantha Dalal +5
Rideshare workers experience unpredictable working conditions due to gig work platforms' reliance on opaque AI and algorithmic systems. In response to these challenges, we found th…
FareShare: A Tool for Labor Organizers to Estimate Lost Wages and Contest Arbitrary AI and Algorithmic Deactivations
Varun Nagaraj Rao, Samantha Dalal, Andrew Schwartz +3
What happens when a rideshare driver is suddenly locked out of the platform connecting them to riders, wages, and daily work? Deactivation-the abrupt removal of gig workers' platfo…
Rideshare Transparency: Translating Gig Worker Insights on AI Platform Design to Policy
Varun Nagaraj Rao, Samantha Dalal, Eesha Agarwal +2
Rideshare platforms exert significant control over workers through algorithmic systems that can result in financial, emotional, and physical harm. What steps can platforms, designe…
QuaLLM: An LLM-based Framework to Extract Quantitative Insights from Online Forums
Varun Nagaraj Rao, Eesha Agarwal, Samantha Dalal +2
Online discussion forums provide crucial data to understand the concerns of a wide range of real-world communities. However, the typical qualitative and quantitative methodologies…
Data Collectives as a means to Improve Accountability, Combat Surveillance and Reduce Inequalities
Jane Hsieh, Angie Zhang, Seyun Kim +7
Platform-based laborers face unprecedented challenges and working conditions that result from algorithmic opacity, insufficient data transparency, and unclear policies and regulati…