Last summer, Uber and Lyft "locked out" drivers from work in order to game the city's minimum wage law, a labor practice that was "unprecedented" according to economists who created the law. Bloomberg built an automated WhatsApp tipline to gather exclusive data (7,000+ screenshots from nearly 900 drivers) that showed how pervasive, widespread, and financially damaging this phenomenon was for drivers, as well as the impact on consumer fares and the economic gains for the companies. After Bloomberg's findings were published, the Federal Trade Commission opened an investigation into Uber and Lyft's alleged antitrust practice of limiting driver pay.
In this session, Bloomberg journalist Natalie Lung will share how they did it, share tips on how to maximize participation from sources through crowdsourcing, validate messy user-submitted data, and how to combine shoe-leather reporting with the affordances of automation.
