  Rideshare platforms exert significant control over workers through
algorithmic systems that can result in financial, emotional, and physical harm.
What steps can platforms, designers, and practitioners take to mitigate these
negative impacts and meet worker needs? In this paper, through a novel mixed
methods study combining a LLM-based analysis of over 1 million comments posted
to online platform worker communities with semi-structured interviews of
workers, we thickly characterize transparency-related harms, mitigation
strategies, and worker needs while validating and contextualizing our findings
within the broader worker community. Our findings expose a transparency gap
between existing platform designs and the information drivers need,
particularly concerning promotions, fares, routes, and task allocation. Our
analysis suggests that rideshare workers need key pieces of information, which
we refer to as indicators, to make informed work decisions. These indicators
include details about rides, driver statistics, algorithmic implementation
details, and platform policy information. We argue that instead of relying on
platforms to include such information in their designs, new regulations that
require platforms to publish public transparency reports may be a more
effective solution to improve worker well-being. We offer recommendations for
implementing such a policy.
