I am not defending Shipt and there is no doubt gig workers are in a very vulnerable position. However, the data analysis results as presented in the article do not support the article's main point. "40% are getting paid at least 10% less" is not unnatural to expect whenever pay is redistributed, especially since some 30+% are getting at least 10% more. Imagine a _hypothetical_ situation where Shipt is 100% on point and driving a fairer version of the algorithm patch removing a way for workers to "optimize" for short, well paid trips, resulting in pay cuts to those who had learnt how to do it, while not changing/increasing pay for everyone else. We would see the same kind of result: some portion of workers would get paid 10% less, some 10% more. This does show that workers are paid differently for the same work they have been doing, but does not prove the change is unfair.
A clear case of adverse selection in the old pricing model.<p>From a game-theoretic perspective in a gig marketplace you don’t want jobs that are strictly better, else sophisticated market participants (workers) will select the best ones leaving chaff - and a worse experience - for the less sophisticated participants.<p>What you are looking for is preference optionality, eg one Uber driver might prefer not to do very long trips, another might prefer it, and you ideally get paid fairly for either.<p>In this case as others have noted, it doesn’t actually sound like an unfair change. Perhaps communications could have been better though.
Do the worker's even see how much they'll make up front? If not, how is this fair, or even legal? I'm doubtful anyone here would go and work for McDonald's with the agreement being that they pay you what they think you're worth, after the job's done. We all see the asymmetry at play, and how it'd be abused at a moments notice.
If the whole point of the algo change is to correct an unfairness by which a strict fee+cart value approach doesn’t reliably reflect the amount of work somebody’s being asked to do, isn’t this exactly the outcome we expect? That the people who were putting more work in now get more money, while the people who were benefiting from sniffing out the “easy” jobs now make something more in line with everybody else’s compensation?<p>It does seem unsporting on the company’s part to play coy about the details. I wonder what the imperative was there: to avoid squabbling with workers about what “effort” means? To reduce the chances of legal scrutiny in one of the thousands of jurisdictions they operate in? To preserve the flexibility to quietly turn the dial in their own favor in the future?<p>I’m reminded of how Uber caught flak over surge pricing, and ultimately dealt with that by making pricing completely opaque. Now they still might say “prices are a little higher because of the weather” if they decide to, but normally you don’t even <i>expect</i> to know whether your price for a given ride is based on their estimate of your desperation, their having sized you up as price-insensitive, driver supply, or what…
“There’s no technical reason why these algorithms need to be black boxes; the real reason is to maintain the power structure.”<p>I’m kind of amazed that the article has the courage to say this out loud. The New York Times or any mainstream publication would never have been so honest.<p>If anything they would have said some weasel words like “some ex-associates of shipt have complained that the app’s compensation system is unfair.” Rather than just blurt out the truth, which is that it’s unfair by design because the owners of the app want to maintain a certain power relationship. It’s the kind of thing that everyone knows but is not allowed to say in printed form.
> The system used optical character recognition—the same technology that lets you search for a word in a PDF file<p>That's not correct, at least for "digitally-born PDFs" that were made on a computer and haven't been scanned. In that case, the PDF can be parsed directly, without OCR, to get text. That's what a tool like PyPDF2 does, for example.
There is an inherent flaw in those algos - they can be played by bots that scan for the best orders, while workers without bots and customers with smaller orders are left hanging. Better to just pay by the hour - you agree to deliver any order thrown at you during your shift.
>Those deliveries were made by Shipt workers, who shopped for the items and drove them to customers’ doorsteps.<p>I've seen Shipt's operations internally, and they don't go shopping for stuff at stores and then deliver them, unless that's a different part of the business.
>60 percent of workers were making about the same or slightly more under the new scheme. But we felt that it was important to shine a light on those 40 percent of workers<p>Absolutely pathetic investigative journalism on display. This is a hit piece thinly veiled under the guise of being pro worker that fails to support the main point of algorithmic management of gig workers is worse for everyone but the corporation employing it.<p>If anything, they proved that shipt's algo did exactly what it was designed and reported to do, make payments more fair.
Looks like nothing happened after:<p>> <i>They asked for a meeting with Shipt executives, but they never got a direct response from the company. Its statements to the media were maddeningly vague, saying only that the new payment algorithm compensated workers based on the effort required for a job, and implying that workers had the upper hand because they could "choose whether or not they want to accept an order."</i><p>> <i>Did the protests and news coverage have an effect on worker conditions? We don’t know, and that’s disheartening.</i>
Wow, gig or not, workers should be paid transparently.<p>Which should be obvious but this is kind of the problem with enshittification where once a business feels they have a bit of a moat (like with a two sided marketplace) they will erode the service to take every advantage unless stopped by regulation. No one likes regulation because it's effectively crufty technical debt and our political system is far too slow, corrupt, or incompetent to effectively refactor it so the best we can do is either nothing and endure the enshittification or layer on more cruft, usually far after the fact multiple years and court fights later.