Data Shows Black-Box Algorithm Reduces Shopper Pay

During the pandemic, Shipt launched a black box pay algorithm, dubbed v2. Shipt’s shoppers immediately recognized this pay “change” for what it was: a devastating pay cut. The shoppers knew what was coming because black box algorithms are nothing new in the gig economy. They are an exceeding popular way of increasing profits by lowering worker pay. Gig companies love black box algorithms because they allow the companies to hide the components determining pay from their workers. This lack of transparency allows the gig companies to drop pay at any time without warning. Shipt, however, quickly dismissed the concerns of its shoppers and specifically denied v2 would reduce shopper pay. Thus, Shipt shoppers spent the last few months collecting the data, ultimately submitting over 3,000 pay earnings summaries to Coworker.org.

Careful analysis of the data revealed the shoppers were correct: v2 was a significant pay cut. Specifically, the data conclusively established that 41% of shoppers experienced a decrease in earnings from the new pay scale in September and a full 60% of shoppers saw their earnings fall in October. Shoppers who were affected by the pay cut saw an 11% pay cut in September and, by October, affected shoppers were experiencing a 15% pay cut. This indicates we can expect to see an even higher pay cut as more shoppers are impacted.

Additionally, the findings show our earnings aren’t actually based on effort. Large orders take the most time, and require the most effort, yet they’re the orders that have lowered pay.

While this is the first time we’re crowdsourcing data to Coworker.org, it won’t be the last. Please submit your earnings here so we can continue to track v2.

Read more about the report on Gizmodo and Coworker’s blog

Thank you to Drew Ambrogi at Coworker.org and Dan Calacci, a Phd student at MIT.

www.shiptlist.org