Algorithmic Wage Discrimination (2023) | Hacker News Reader

Algorithmic Wage Discrimination (2023)

columbialawreview.org

149 pointstacon101 comments

As with price discrimination, I think there are only two possible ways this can go:

Either we pass some laws that deeply upset some oligarchs and future eras see this one as a "wild west" of data-driven exploitative practices, or we permanently destroy the bargaining power of everyone not big enough to be doing mass-surveillance, which is effectively the end of markets and the rise of a sort of advanced feudalism (which some would argue is quite far along already)

One obviously seems better to me, but to be fair I am biased, being in the class of people who don't own an enormous corporation

If history is any teacher here it's going to be latter with the loudest voices of support coming from people are convinced that these systems couldn't and aren't possibly harming them, that they are above-average and therefore benefiting, and only those slack-jawed lazy nonspecific others who aren't (but absolutely are) working hard will be the target.

That's definitely the recent history, and the current propaganda strategy of modern oligarchs, but looking even a little beyond living memory there are many other solutions history can offer us, including labor solidarity, trust-busting, and of course more extreme measures that most would likely prefer to avoid, but which history shows us do happen sometimes

The third way is that companies find hiring workers, with all their complaints and needs and desire for dignity, too inconvenient, so they replace them with things that have none of those.

Particularly relevant since this paper is primarily about ride hailing and delivery services.

Despite all the hand-wringing most claims to be able to do this seem pretty implausible at this stage. But for the sake of argument, assuming this happens, this is not different from the second scenario I've described. Of course, if there are no workers, one wonders how companies might find "consumers" against whom to price-discriminate, but with companies unilaterally and individually controlling both what people pay and are paid, the whole system of labor and consumption as a market is a fiction anyway. It's crazy that so many people seem to think that transformative technologies will both somehow replace all human labor and keep all present economic relations intact except for the ability of anyone to get a job, given how many economic choices have been made to center labor as the primary means by which people are supported. To reiterate, the options are prevent this nonsense through collective action (either in the form of a government or through other forms of coordination) or move to a more oppressive relationship between a tiny population of oligarchs and everyone else than the "labor market" that is ostensibly the way this economic relationship is currently arranged

For the ride hailing side of things, it's already happened; there is no question of plausibility. I've probably done 50 rides in 2024, and only two had human drivers.

And I'm sure that'll stay working in San Francisco as long as there's enough bribe money to cover pushing past the considerable concerns about safety in "edge cases." It's entirely possible that's forever, if nothing breaks up the current consolidation of power as described

It's not hard to see where this is going. Rideshare drivers have already become essentially their own underclass in America. They seldom own the equipment of their job, yet they're responsible for all the maintenance costs, costs for their (mandatory) insurance are horrendous, and they're left with hardly anything before they've even paid for medical insurance or an apartment.

It's not really sharecropping, since Uber doesn't write car loans. Feudalism? In a society so utterly dependent on cars, that doesn't seem terribly far off.

Yea, feudalism is probably the best description, and it applies to cars as well as anything with a computer in it, as well as the more traditional land and food supply. This is not that surprising given that the safeguards that have been systematically dismantled over the last 50 years were by and large created to prevent feudalism, as was most of the apparatus of what we currently call "government"

It does now raise the question - are other countries, particularly those with well-developed public transit infrastructure, more insulated from this particular form of techno-feudalism? It seems to me like the essential-ness of a resource is what enabled feudal structures around it.

I think so, but the pushes to integrate privately-controlled computers into every facet of required infrastructure means the feudalism in other domains has come and will continue to tighten for any country that doesn't adequately rebuff it

Good point.

I suppose the "good" news is that none of the rideshare companies have managed to prove that their business model is even profitable. So, even in this stupid postmodern techno-feaudalist hellscape, maybe we won't have people effectively indentured by their cars.

The entire history of the tech industry is one of profitability being a trifling concern compared to buy-in from the investor class and sometimes government subsidies. Feudalism doesn't require profits, only power over resources

Mega-rich people aren't investing in Uber in order to acquire power over serfs. They're doing it in order to make more money. So far, they seem to be mistaken in the potential profitability, but that doesn't make "feudal power over others" their goal.

Profitability may be a trifling concern for the companies, but it's not for the investors.

There's a lot of money in feudal power over others, once it's established, not to mention that it's an end-run around policy channels to reshape society. Some investors really do mostly want direct ROI and are likely disappointed by plays like Uber in this regard, but it's at this point kind of crazy to assume this is the main driving force behind such investments, given how often they cash out in power and policy change rather than direct profit

The reaction here has been interesting. As someone with a heavier social-science and politics background than most HNers, I started reading the introduction before there were any comments here and went “oh my god, of course this is a thing, why did it never occur to me both that this would/is happen/happening, and to put it in these terms“, and my mind started chasing down the mechanisms by which it must work. Bombshell is a word that came to mind as soon as it dawned on me what the paper’s getting at.

Then I came back to this thread and had a similar experience to when I checked on the Internet’s reaction to The Last Jedi after I got out of the theater, and was surprised to find that my experience of it as the only almost-actually-good SW film since the original trilogy was, um, not what most others had taken away.

It's always useful to keep in mind the wide variety of HN users. For certain cohorts, the likes of Peter Thiel, Elon Musk and such are considered the pinnacle of their aspirations, and abusing workers is viewed as business smarts.

Who goes to work for Elon cannot really be so-called abused - already knew what is coming when applied

I think one thing going on is that the form of argument is unfamiliar to a lot of readers. Many seem to have taken away that the paper’s about the concerns the “Blueprint” it mentions sets out to address, or about traditional bonus structures or variable or productivity-based pay, because the intro covers both of those things in some detail—rather, the paper is laying those out as background. The paper is not about those.

This is a common form for papers and arguments in the social sciences, but maybe a lot of HNers aren’t used to it.

[edit] to be clear, the paper lays out plainly that this is the case, and a person unfamiliar with this way of writing could figure it out from the text per se, but if one is not looking out for this kind of structure I can see how one might overlook the parts where it straight-up says “that’s not what this is about: here is what this is about”

So, what is it getting at that's not obvious until it's pointed out and you haven't run across before (and how is that related to having a social-sciences background)?

Before app work, unpredictable schedules were a problem for people juggling multiple part-time jobs. Presumably they still are and the news just has a new shiny to play with.

Paying people more to cover undesirable shifts means that people with more flexibility or who choose to make more personal sacrifices will get paid more. I remember something about... pharmacists I think it was? and how these factors lined up with some of the traditional "group X gets paid more than group Y" groupings.

A job that doesn't artificially limit available positions will tend to pay just slightly more than whatever job ranks next for having a wider pool of eligible workers. Something where the next thing in that ranking is panhandling or unemployment is never going to pay well unless prospective workers are turned away.

> Paying people more to cover undesirable shifts means that people with more flexibility or who choose to make more personal sacrifices will get paid more. I remember something about... pharmacists I think it was? and how these factors lined up with some of the traditional "group X gets paid more than group Y" groupings.

This is key because it’s close to the thing that made me go “ah ha” reading the intro: modern surveillance and algorithmically-managed pricing (so, cheaply modified at arbitrarily-fine resolution based on arbitrarily-many quantifiable factors) open up the possibility of pushing this exact effect from groups of workers to individual workers.

You can avoid (at least to some degree not previously achievable) addressing a pool of workers and instead only clear the rate for a particular worker. No human management input needed per-decision or in any part of the broader offer-decision process and surrounding data gathering and measuring, which is what makes it possible.

In dumb people terms, corporate gig economy players are using algorithms to artificially depress wages of random workers for work that is very similar in scope, if not the exact same (they work similar hours, in a similar area, with similar vehicles and in some cases they are even getting offers for the exact same job with wildly varying wages)

It’s like how a normal person who’s worked with a couple of solo independent contractors (say, for some work on their house) and has a sense of how they both price things from past bids, might offer a job they need done by a certain time to both of them—exact same job—at different rates, all else being equal (the homeowner rates their work as comparable), just because they know one of them historically bids lower. They’d prefer the cheaper one, but are willing to pay either rate, and need the job done by time X, so offer it to both, first to accept gets it.

Now throw in a bunch more factors than just prior bid history, thousands of workers in the dataset instead of two, and such high volume and pace of work that you can afford to periodically experiment by setting, say, a random 10% of each set of offer-receivers lower than your formula would usually suggest, to see if anything’s changed and maybe they’re more-desperate for some reason (you don’t even need to know why… though, imagine if you could spot reasons some workers might be more desperate! Hm…)

Now (maybe) extrapolate to similar, slower-paced efforts in less-marginal areas of work. Interesting (yikes) possibilities.

This is a topic my friends and I have been talking about since at least 2018, and much of this review just feels affirming. It's good to know 4 bozos in Wisconsin aren't the only ones realizing life sucks for Uber drivers. All I can really do about it is vote.

The thing that stood out to me the most is the transparency argument. When you get paid hourly, you're told upfront how much extra you get paid for overtime, for odd hours, etc. But with rideshare apps, a number just shows up on your screen. You have no knowledge of why that number is what it is.

There's also the social side of the transparency issue. Back when I worked foodservice, I could just ask my coworker what they got paid per hour. As a rideshare driver, you never see your coworkers. Even if you did, you have nothing to compare. There's no "per hour," and "per mile" is rife with caveats, assuming the app even shows you that. With no way to compare to each other, how do rideshare drivers collectively discern what is or isn't fair pay?

Great app idea for the bright minds of HN: an app that lets a rideshare driver easily record hour + mileage when working, combines it with the daily earnings (to get $/hr and $/mile) and let's them share with fellow workers.

No, like, this is fucking different. Read the damn article. Like, get down to pages 42-46. I know it's a lot to read, it's a law review article, it's fine if you don't read it, but like "oh what is it getting at?" is something that you have to read the article to see.

So like, before the gig economy, yes, you might be juggling a job at McDonald's with another at Jo-Ann with a hardware store, and Jo-Ann called up at 7 and said you have to come in Or Else, and then you came in by 7:45 and they said "eh too many people showed up, nevermind" and you're up shit creek, so now you're poking by your McD's which could always use some extra help with the breakfast rush but wants you to clock out between 10:30 and 11:30 so you're having to call up the hardware store to see if you can get paid there.

That is bad, to be sure. You have to be playing all the angles, checking in with everybody, you have to hustle hard to make ends meet.

But according to this, your job at GigBurger is one where they say "hey if you can work for at least 6 hours today, we'll give you a big bonus," with the caveat that you are auto-clocked-out not just at 10:30 but whenever there's nobody in the checkout line or drive-thru, so that "6 hours minimum wage" has to be accumulated over 10 actual hours at work -- which is fine if you can get that bonus. But the shitty algorithmic part is that when you get the GigBurger App to rack up 5 hours of work, suddenly it says "oh shoot we're overbooked for your current GigBurger Restaurant, but you know there's a big surge in customer demand over on the other side of the city, go there and get 2x wages and you'll also make your last 1h for sure" and they are fuckin' lying to you and leading you to other overbooked GigBurgers in the hopes that they can run you back and forth across the city without paying you until they exhaust your desire for that last hour's work that would get you the bonus. And you have to be able to discern between actual surges and algorithmic lying to determine whether to attempt the journey across the city or just stay put and see if the GigBurger next door has someone clock out early.

The article clearly lays out why this is a difference in quality, not just quantity: it says that the default American story of "hard work and hustle will be rewarded", which you absolutely had in the "unpredictable schedules" world that you are talking about, shifts to one where the psychological story is that "GigBurger is a casino, roll the dice and hope to God that you get lucky today." Any individual unpredictable job might have been a casino, but you knew that your employers weren't all in cahoots to deprive you of a promised lucky payoff that was the only thing that made the job sorta worth it.

That sounds more like a poorly optimized, buggy and unbalanced algorithm.

Would it be fine if there's an algorithm that was able to more accurately predict that if you go to this location at those hours you would be able to make 1.5x more for the several few hours?

There's no reason an algorithm shouldn't be able to do that.

Or an algorithm where you can specify how many hours you plan to work and then it will provide what it calculates the most optimal path for you to take, where perhaps you can even use a slider to quickly test.

We could only know whether the algorithm is competent or incompetent, if we can see what it is and what it is optimizing for and how is it doing at that. Without transparency into GigBurger, you can't tell.

This was the nice thing about working for an MEP* subcontractor, I got to see the unions and the company teaming up, “look the margins are razor thin, we want to get home safe and make ends meet but not if it starves the company and we're all out of a job in 5-10 years.” And in that environment, every pipefitter could know that the algorithm isn't specifically screwing them over. The unions needed our explicit sign-off that our tech to help them track the status of their projects wasn't gonna be able to be used to track how much time their folks spent in the bathroom on a given day. But try telling Uber that they need a driver's union, see how far you get.

*Mechanical, Electrical, and Plumbing. I don't fully understand the contracts side but basically the general contractor will take a big construction job and the biggest margin, then subcontractors will design and do parts of the actual fabrication and installation.

Would it be fine if this algorithm had to be open source?

>That sounds more like a poorly optimized, buggy and unbalanced algorithm.

An algorithm that intentionally sends you to different stores so you can't rack up the last requisite hour to make the bonus? Really?

What is the evidence that anyone is doing that intentionally?

It's a hypothetical, sheesh. Did you read the comment?

Intent is immaterial

> and they are fuckin' lying to you and leading you to other overbooked GigBurgers in the hopes that they can run you back and forth across the city without paying you until they exhaust your desire for that last hour's work that would get you the bonus

Doing this intentionally would require an implausible level of abject stupidity on the part of the people doing it. Anyone in a position to do this intentionally also knows that it would in fact be counter-productive.

I don't think it does. That is, the quasicode algorithm looks something like this:

    def fulfill_order(order):
        range = 3 * miles
        surge = 1
        workers = workers_in_range(order.location, range)
        while len(workers) == 0:
            range *= 2
            workers = workers_in_range(order.location, range)
            surge += 1
        if surge > 2:
            initiate_surge_pricing(order.location, surge)
        
        lowest_cost = min(w.cost for w in workers)
        workers = random.shuffle([w for w in workers if w.cost == lowest_cost])
        for w in workers:
            if worker.propose_order(order): 
                return order.assign_worker(worker)

        # if we're still here no worker has accepted the proposal
        order.raise_bonus()
        return defer_retry_order(order)

This does not read as incompetent pseudocode, to me! But it has the crucial problem.

Just to be clear about how the algorithm is lying, once you are near bonus and thus you're not in that lowest_cost bracket, you need an actual prediction of a place where demand is going to outstrip supply. The incentive system is reactive to actual demand and thus hopelessly noisy as a lagging prediction of demand, and it is being broadcast to try to manipulate driver behavior which means it also secretly forecasts a supply spike. So if we take it as 50% that the surge in demand is real and 50% that the added supply doesn't cover the added demand, then your actual number of surges you have to chase across the city is a geometric random variable with p=25%, and geometric random variables have the frustrating property of being memoryless like a good casino is: if you're exhausted after you've failed to make it after chasing 4 surges across the city, the expected number of surges you have to chase to get your bonus is, well, 4 more. And if you're at your wits' end after those 4 more, the expectation is, well, 4 more.

There was a (now deleted comment) about how there is no proof of wage discrimination for Uber/Lyft drivers, which was posted with no evidence.

This video (https://www.youtube.com/watch?v=OEXJmNj6SPk) was recently published which shows drivers being offered the same gigs, but different payment amounts. Note that I could not find a published version of the data they collected in this video.

That is not explicitly proof of wrongdoing, but clearly algorithmic price setting can be demonstrated as not always offering the same payment to the same drivers for the same work. There may be a valid reason to why this is the case, but as the calculation method is closed source, the individuals being offered the wage are unaware of why they would be paid less than their peers.

This is work that is often considered "low skill" - which should actually make it extremely cut and dry as to why an individual would be paid more or less. Are they making their pickups faster? Are their customers more satisfied? If that's the case, why would they sometimes be offered more money than their peers and sometimes less money?

Almost all workers here are price takers, and suffer greatly from the information asymmetry present. Companies hiding behind "oh but the algorithm says..." is a poor excuse for inequality.

Edit: Because discrimination is in the title of the OP, I feel the need to clarify: in no way is the above saying that the video posted is proof of discrimination. Inequality need not be discrimination. When there is inequality without any measurable source, we need to be skeptical of the reason. Maybe one driver has better customer feedback, therefore they get offered a higher wage. There are many logical explanations for the result, but Uber/Lyft do not seem to engage with the discussion. This should raise red flags. That does not conclude that they are discriminating against anyone, and that would be a poor conclusion to draw without a true investigation.

Not deleted, just (formerly?) flagged to death by other users: https://news.ycombinator.com/item?id=41513943. (The HN software seems to kill newer users’ comments more readily, is my impression.) You can enable “showdead” on your profile page if you want to see such comments.

showdead is essential for Orange Reddit but it will show downvoted comments in unreadable light grey on light grey. So you probably want a user CSS (e.g., with Stylus) like this (italic and the particular color are to taste, of course):

    .c5a, .c73, .c82, .c88, .c9c, .cae, .cbe, .cce, .cdd { color: #222; font-style: italic; }

Thank you! Reading that comment was actually what prompted me to make an account just to reply that, and then when I did it was gone.

I could see an AI trying to hunt out a person's bottom line. I could offer this job for $10 to everyone, but maybe I'll subtract 0 to 4 dollars when I offer it and see who does or doesn't bite. If someone bites on lower pay, I then record that information and offer them further lower pay in the future.

This isn't really abnormal. Every job does this by setting a wage they are willing to pay and seeing who signs up, knowing that person will now need to only be paid that wage. What is different is the scale and the frequency this is being done. Instead of doing this in a way that impacts a person once every job change, it now impacts them multiple times a day, and the data recorded is more detailed and can be acted on more directly.

None of this is discrimination against a protected class, but if there are any reasons one demographic might, on average, accept lower pay than another, it will lead to large scale discrimination.

The problem is that our common discussion on these topics is lacking the rigor, nuance, or depth to handle questions about this, and thus ends up with two large camps. One that looks at the methods, sees no obvious discrimination in the methods, and say it doesn't count as inequality. The other that looks at the outcomes, notices the clear difference in outcome this leads to, and calls it inequality. Both are, by their own metrics, correct.

“Price discrimination” (or in this case “wage discrimination”) as described in microeconomics is exactly this—the same seller/buyer demanding/offering different prices for the same goods depending on their idea of how much the buyer/seller will bear. The term has nothing to do except etymology with what sociologists, lawyers, or politicians mean by the word “discrimination” (not that those three groups mean the same thing by it).

The issue is that many small scale price discriminations on individually reasonable criteria might present itself as a large scale discrimination of the type that lawmakers and others do care about. The way terms are overloaded does no favors, but even if we updated the terminology to resolve this, I think the underlying issue will remain.

Pink tax is an example of this happening, though on a scale needing far invasive technology than is currently available. It is presented as (big) discrimination even though it happens as price discrimination.

It’s more than that, I think: if this paper holds up (or if it doesn’t, but the ideas it covers are valid and the practices it’s concerned with later come into being) then it’s describing a mechanism for pushing down worker wages at the individual level, and within potentially any or all bands of the economy toward the market-clearing rate per worker. A market of many workers becomes many markets of one worker.

This is, um, potentially really bad. It’s several effects that already happen in, if you will, chunkier ways in our economy (especially in the US, with weak or absent unions and poor labor protection laws, compared to many other developed states) becoming applied at a much finer level of resolution (so to speak).

Stay tuned for my new app: Wildcatr

It is installed on gig worker phones and monitors the offered rates. When one worker is offered abusive rates, all other workers have their future offers filtered from view for some period of time unless it exceeds the typical offer by more than the amount the abused worker missed out on.

The issue isn't the "hunt for the bottom line" but the fact that simultaneously multiple parties are offered different price points for an unknown reason (to the workers).

You say it's not discrimination, but you cannot definitively make that claim. That's the issue. Red lining isn't immediately discrimination against a protected class, but silently is it. This is not to say that Uber/Lyft are discriminating against a protected class - it's just that because of the lack of transparency we don't know that they are not.

This is a hard thing for people to accept, but we need to take a deep look at how we implement ML to classify things tied to individuals. It's very easy to de-humanize the humans affected by the systems we build, because "it's just an algorithm."

> it's just that because of the lack of transparency we don't know that they are not.

Is this not the case regardless of whether an algorithm is used or not?

Setting labor price by exchange-like auction is an abusive practice in any context.

Companies get a pass on job interviews because it's basically impossible to prove. But this doesn't make it ok, it just makes it less damaging than the remedy. (Or at least arguably, a lot of people do argue otherwise, and lots of people are looking for better remedies.)

My immediate thought is that it would probably get better results of they intentionally set pay based on social media predictors of wage sensitivity. I expect that you could that there are fingerprints of wage sensitivity. And that could amount to what's basically predictive union breaking via wage increase.

If this outcome is a surprise to you, you have not been paying attention. Managers and Owners dream of reducing wages every single night. Every penny they aren't paying you is a penny they keep, and they, for some reason, think they are rightfully entitled to every penny, while you are a brat for feeling entitled to even a few pennies.

More importantly, if your boss doesn't think like that, you can expect his boss to replace him with a manager that DOES.

This downward force on labor prices is basically the entire point of the gig economy, and even youtubers whose only formal training is in how to write a high school essay figured this out.

For this reason, there is institutional pressure to turn anything they can into gig economies. If you don't have empathy for the uber drivers who sleep in their car to be able to make as many rides as they can and still somehow end up below minimum wage, don't worry, they'll come for you soon. And when they've made the gig economy literally the only gig in town, it doesn't matter how savvy you think you are at "negotiation", you will get fucked too.

Go read up on your labor rights history. None of what we have is a default, and the "haves" HATE it.

The thing that people consistently miss with these types of conversations is that any increase in the sophistication of the tech that exists to measure the world gives a relative benefit to corporations over individuals.

This is because those organizations almost always have more resources to dedicate towards making effective use of that information than do individuals.

Very often you as an individual are up against a team of PhDs and engineers whose job it is to enable the corporation to beat you, and the more data they have, the more likely they are to win.

In this respect, there is basically no tech that does not benefit corporations more strongly than it benefits individuals. This is one of the reasons that regulation is important.

They don't "miss" this fact. It's inconvenient to libertarian la-la land dreams so it's ignored with prejudice, especially here. So many temporarily embarrassed millionaires on HN.

> any increase in the sophistication of the tech that exists to measure the world gives a relative benefit to corporations over individuals.

We are far more able to measure the world than we were in the middle ages, or before the civil war, or even during the world wars.

You can see how strong this claimed relative benefit and it's effects are by how the increasing ability to measure the world over that time has led people to become consistently more oppressed as time goes by.

I'm not sure if you disagree with me or not from this comment. Tech isn't the only thing that affects the relative strength of individuals vs corporations (regulation, social pressures, etc).

Also I think it's not unreasonable to argue that corporations are more powerful today than they were during any of the time periods you've listed here.

"Wage discrimination" as described in the article is not an unfair or illegal practice:

> “Algorithmic wage discrimination” refers to a practice in which individual workers are paid different hourly wages—calculated with ever-changing formulas using granular data on location, individual behavior, demand, supply, or other factors—for broadly similar work.

Surge pricing is a form of "algorithmic wage discrimination". Driving for Uber on a Friday night will net you more than a Monday at noon. Likewise, the fact that wages are higher in expensive metros is another form of "algorithmic wage discrimination." People hired during periods of a labor shortage may have a higher wage than a co-worker hired during an economic downturn. I am skeptical many would point at these scenarios as unfair - but all of these fall under the category of "wage discrimination" as discussed in the article.

I also think this article unnecessarily injects racial messaging and leads readers to think that the algorithms are discriminating on the basis of protected class. That is not alleged in this article.

Not so coincidentally, the EU is mandating salary transparency:

https://fikku.com/111920

This is very apropos after seeing the Pave post.

Off-topic, does anyone know whether the source code for this UI is open source?

"Subordinated racial minority". "Informational capitalism". "how should the law intervene" (no 'if'). "For workers, these practices produce unsettling moral expectations about work and remuneration".

Big hmm. As always, truly objective metrics - such as pay based on output (rather than time spent) is viewed as harmful to minorities.

Is it, though? Or is it actually more fair?

Typically, workers are paid a flat rate, businesses buffer the worker's income generating activities, such that the business owners pocket high income activities (like serving drinks and being tipped) with low income activities (like washing the dishes at the end of the night). Any money left over after wages, is pocketed by the business owner, to be used on a day with low income day (think Friday night vs Sunday night at a restaurant).

Dynamic pricing allows workers more exposure to the value they generate, thus enabling them to capture higher pay.

That might be what dynamic labor pricing implemented by a disinterested third party would do. An interested party can use it to do other things.

What other things?

For decades, restaurants have paid their labor with dynamic “algorithmic” wages: work during peak shifts, get more tips.

Why haven’t people been up in arms about how bar tenders working a Friday night near more than bartenders working a Monday afternoon?

The article is about subjecting workers to discriminated pay rates for reasons: that are not clear to the workers; that may not be within the power of the workers to control; that cannot be predicted in advance; and that may vary per worker rather than being offered the same to all workers at once; with that last also based on factors unknown to the workers—including, potentially, personal information about the worker or about their compensation history.

The paper is explicitly not (as in: the intro outright states this is not what it’s about) traditional forms of variable pay.

> that are not clear to the workers; that may not be within the power of the workers to control; that cannot be predicted in advance; and that may vary per worker rather than being offered the same to all workers at once;

You’re literally describing tipping. When a worker starts their shift, they do not know how much they will earn. Tips vary per worker for sexism, racism, ageism reasons, or just plain luck.

That is similar! But this is the employer doing it, not a bunch of uncoordinated people.

If 5 “employers” per day opaquely compensate an employee, then that’s ok.

But if 1 employer, chooses their wage opaquely, then that’s bad.

I don’t get it.

The paper explains this (and isn’t about quite what you’re suggesting). Tens of pages of explanation, it covers it better than I will.

Most restaurants in the world operate without tips.

But usually these things come down to patterns that people will learn. E.g. they will learn certain location at certain hours will pay more, because there's more demand vs supply, so they will adapt. It allows them the power to decide when and for what money it is worth it for them to work those hours or this location.

Those parts, maybe.

Will you know they’re offing you and Bill the exact same job at the same time, and are willing to pay whichever of you takes it first, but Bill’s offer is 20% higher? Or when they’ve made you a lower-than-usual offer to test if they can start offering you lower rates in the future (but you did just get a past-due notice on your kid’s hospital bill…)?

> Will you know they’re offing you and Bill the exact same job at the same time, and are willing to pay whichever of you takes it first, but Bill’s offer is 20% higher?

Is this any different from than any job ever? More experience airline pilots are paid more than the less experienced for the exact same route.

Two new grads from the same school may get different offers depending on how well they interviewed for the same role.

Where is the problem?

Wait staff paid directly by customers is different from payments processed opaquely by the employer. Consider if a server got paid tips based only on the number of customer smiles detected by the restaurant security cameras.

Tip amounts have always been about how much the customer enjoyed the service, hence the 10-25% tip ranges.

Customers have opaque expectations for service and pay their server based on the server’s gender, race, and age as well as quality of service that the server doesn’t even have control over (like if the kitchen was backed up).

A system counting smiles is basically what we currently have: instead of signaling with a smile, they signal with a tip amount.

Why are you obtusely re-contextualizing everyone's responses?

I feel like these articles are just "tech company = bad" without recognizing that there are thousands of really smart people trying to create an equitable system that supports the needs of the drivers, passengers, and company.

1. Good wages for drivers means more drivers.

2. More drivers means better quality of service at lower cost for passengers.

3. Low cost and high quality service for passengers means more passengers.

4. More passengers means more rides and more money spent on platform.

More drivers and more passengers means more money for company. The argument that Uber/DD whatever is not incentivized to have high wages for drivers is ridiculous.

Have you ever worked a job outside of tech?

Yes, in high school I worked in retail (that had tips) and in college I worked at an tiny hardware engineering firm.

Not anymore.

Now there is pre-tipping, tipping for no discernible service, fake tip jars in places that aren't licensed for it, etc.

More people are becoming aware that, in the US anyway, the wage is reduced commensurate with expected tips, and so customers are more or less obligated to supplement wages, and avoid offending servers, unless we don't want to be served at all.

> Dynamic pricing allows workers more exposure to the value they generate

Now we just need to get this to work with respect to investors generating real value and not just profit and capitalism might actually be cooking something

Your perspective of dynamic pricing is true, _if_ the workers owned the platform(s). But they don’t. So your assumption that dynamic pricing allows workers more exposure to the value they generate falls flat on its face when there are uber drivers making less than they’ve ever made while uber itself is turning into a profitable company

i’m still confused what people are proposing is the solution.

Uber pays a flat hourly rate no matter when the driver works? Drivers working after a football match earned the same pay as drivers working at 4am?

I think this would mean that the drivers that work during peak hours Less than they do now and drivers working during low traffic hours would earn more?

But corporations have access to way more power and data. You aren't going to get to see into the wage algorithm. Quitting because you are unhappy with the wage algorithm means time without pay and potentially having to move in order to get a new job. A corporation, meanwhile, suffers very little when one of its employees quits.

I can't possibly imagine how this ends up producing increased average or median wages for workers.

N passengers need rides after a concert, but there Y drivers.

How do you fairly compensate the drivers without dynamic compensation, while keeping the price low for the passengers?

I.e. workers who produce more get paid more, those who produce less get paid less. It's always been that way, though it is usually difficult to measure accurately.

Technically true, while ignoring all details of how "productivity" is defined. Claiming it's an issue of measurement and not definition implies you believe there's some ironclad and universally applicable definition of productivity, i.e., once again imposing your own ideology without any good faith efforts to include other perspectives.

> Technically true, while ignoring all details of how "productivity" is defined.

There's a specialty profession called "cost accounting" whose sole purpose is to accurately define it. Just like insurance companies do risk assessments.

> implies you believe

You're just making things up.

> without any good faith efforts

Give the rudeness a rest.

It's dishonest to say in one comment that certain workers "produce more" and in the next that you are speaking in terms of "cost accounting" productivity (that is, identifying which workers are likely to accept less pay for the same task).

> It's dishonest

Being rude doesn't make your argument any better.

You know that workers are not perfectly interchangeable, everybody with any sense knows that. You also know that cost accounting isn't an exact science when it comes to the variability of people.

But if cost accountants were worthless, businesses wouldn't employ them.

There's a specialty profession which merely adopts as fact definitions of productivity and optimizes costs against that. Give the denseness a rest.

This introduction appears to describe a lot more going on than that.

This isn't even remotely what the article is about, please try and have at least a cursory read of the content you're commenting on.

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