#algorithmic wage discrimination

[mostlysignssomeportents]

Nurses whose shitty boss is a shitty app

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2024/12/17/loose-flapping-ends/#luigi-has-a-point

Operating a business is risky: you can't ever be sure how many customers you'll have, or what they'll show up looking for. If you guess wrong, you'll either have too few workers to serve the crowd, or you'll pay workers to stand around and wait for customers. This is true even when your "business" is a "hospital."

Capitalists hate capitalism. Capitalism is defined by risk – like the risk of competitors poaching your customers and workers. Capitalists all secretly dream of a "command economy" in which other people have to arrange their affairs to suit the capitalists' preferences, taking the risk off their shoulders. Capitalists love anti-competitive exclusivity deals with suppliers, and they really love noncompete "agreements" that ban their workers from taking better jobs:

https://pluralistic.net/2023/04/21/bondage-fees/#doorman-building

One of the sleaziest, most common ways for capitalists to shed risk is by shifting it onto their workers' shoulders, for example, by sending workers home on slow days and refusing to pay them for the rest of their shifts. This is easy for capitalists to do because workers have a collective action problem: for workers to force their bosses not to do this, they all have to agree to go on strike, and other workers have to honor their picket-lines. That's a lot of chivvying and bargaining and group-forming, and it's very hard. Meanwhile, the only person the boss needs to convince to screw you this way is themself.

Libertarians will insist that this is impossible, of course, because workers will just quit and go work for someone else when this happens, and so bosses will be disciplined by the competition to find workers willing to put up with their bullshit. Of course, these same libertarians will tell you that it should be legal for your boss to require you to sign a noncompete "agreement" so you can't quit and get a job elsewhere in your field. They'll also tell you that we don't need antitrust enforcement to prevent your boss from buying up all the businesses you might work for if you do manage to quit.

In practice, the only way workers have successfully resisted being burdened with their bosses' risks is by a) forming a union, and then b) using the union to lobby for strong labor laws. Labor laws aren't a substitute for a union, but they are an important backstop, and of course, if you're not unionized, labor law is all you've got.

Enter the tech-bro, app in hand. The tech-bro's most absurd (and successful) ruse is "it's not a crime, I did it with an app." As in "it's not money-laundering, I did it with an app." Or "it's not a privacy violation, I did it with an app." Or "it's not securities fraud, I did it with an app." Or "it's not price-gouging, I did it with an app," or, importantly, "it's not a labor-law violation, I did it with an app."

The point of the "gig economy" is to use the "did it with an app" trick to avoid labor laws, so that bosses can shift risks onto workers, because capitalists hate capitalism. These apps were first used to immiserate taxi-drivers, and this was so successful that it spawned a whole universe of "Uber for __________" apps that took away labor rights from other kinds of workers, from dog-groomers to carpenters.

One group of workers whose rights are being devoured by gig-work apps is nurses, which is bad news, because without nurses, I would be dead by now.

A new report from the Roosevelt Institute goes deep on the way that nurses' lives are being destroyed by gig work apps that let bosses in America's wildly dysfunctional for-profit health care industry shift risk from bosses to the hardest-working group of health care professionals:

https://rooseveltinstitute.org/publications/uber-for-nursing/

The report's authors interviewed nurses who were employed through three apps: Shiftkey, Shiftmed and Carerev, and reveal a host of risk-shifting, worker-abusing practices that has nurses working for so little that they can't afford medical insurance themselves.

Take Shiftkey: nurses are required to log into Shiftkey and indicate which shifts they are available for, and if they are assigned any of those shifts later but can't take them, their app-based score declines and they risk not being offered shifts in the future. But Shiftkey doesn't guarantee that you'll get work on any of those shifts – in other words, nurses have to pledge not to take any work during the times when Shiftkey might need them, but they only get paid for those hours where Shiftkey calls them out. Nurses assume all the risk that there won't be enough demand for their services.

Each Shiftkey nurse is offered a different pay-scale for each shift. Apps use commercially available financial data – purchased on the cheap from the chaotic, unregulated data broker sector – to predict how desperate each nurse is. The less money you have in your bank accounts and the more you owe on your credit cards, the lower the wage the app will offer you. This is a classic example of what the legal scholar Veena Dubal calls "algorithmic wage discrimination" – a form of wage theft that's supposedly legal because it's done with an app:

https://pluralistic.net/2023/04/12/algorithmic-wage-discrimination/#fishers-of-men

Shiftkey workers also have to bid against one another for shifts, with the job going to the worker who accepts the lowest wage. Shiftkey pays nominal wages that sound reasonable – one nurse's topline rate is $23/hour. But by payday, Shiftkey has used junk fees to scrape that rate down to the bone. Workers have to pay a daily $3.67 "safety fee" to pay for background checks, drug screening, etc. Nevermind that these tasks are only performed once per nurse, not every day – and nevermind that this is another way to force workers to assume the boss's risks. Nurses also pay daily fees for accident insurance ($2.14) and malpractice insurance ($0.21) – more employer risk being shifted onto workers. Workers also pay $2 per shift if they want to get paid on the same day – a payday lending-style usury levied against workers whose wages are priced based on their desperation. Then there's a $6/shift fee nurses pay as a finders' fee to the app, a fee that's up to $7/shift next year. All told, that $23/hour rate cashes out to $13/hour.

On top of that, gig nurses have to pay for their own uniforms, licenses, equipment and equipment, including different colored scrubs and even shoes for each hospital. And because these nurses are "their own bosses" they have to deduct their own payroll taxes from that final figure. As "self-employed" workers, they aren't entitled to overtime or worker's comp, they get no retirement plan, health insurance, sick days or vacation.

The apps sell themselves to bosses as a way to get vetted, qualified nurses, but the entire vetting process is automated. Nurses upload a laundry list of documents related to their qualifications and undergo a background check, but are never interviewed by a human. They are assessed through automated means – for example, they have to run a location-tracking app en route to callouts and their reliability scores decline if they lose mobile data service while stuck in traffic.

Shiftmed docks nurses who cancel shifts after agreeing to take them, but bosses who cancel on nurses, even at the last minute, get away at most a small penalty (having to pay for the first two hours of a canceled shift), or, more often, nothing at all. For example, bosses who book nurses through the Carerev app can cancel without penalty on a mere two hours' notice. One nurse quoted in the study describes getting up at 5AM for a 7AM shift, only to discover that the shift was canceled while she slept, leaving her without any work or pay for the day, after having made arrangements for her kid to get childcare. The nurse assumes all the risk again: blocking out a day's work, paying for childcare, altering her sleep schedule. If she cancels on Carerev, her score goes down and she will get fewer shifts in the future. But if the boss cancels, he faces no consequences.

Carerev also lets bosses send nurses home early without paying them for the whole day – and they don't pay overtime if a nurse stays after her shift ends in order to ensure that their patients are cared for. The librarian scholar Fobazi Ettarh coined the term "vocational awe" to describe how workers in caring professions will endure abusive conditions and put in unpaid overtime because of their commitment to the patrons, patients, and pupils who depend on them:

https://www.inthelibrarywiththeleadpipe.org/2018/vocational-awe/

Many of the nurses in the study report having shifts canceled on them as they pull into the hospital parking lot. Needless to say, when your shift is canceled just as it was supposed to start, it's unlikely you'll be able to book a shift at another facility.

The American healthcare industry is dominated by monopolies. First came the pharma monopolies, when pharma companies merged and merged and merged, allowing them to screw hospitals with sky-high prices. Then the hospitals gobbled each other up, merging until most regions were dominated by one or two hospital chains, who could use buyer power to get a better deal on pharma prices – but also use seller power to screw the insurers with outrageous prices for care. So the insurers merged, too, until they could fight hospital price-gouging.

Everywhere you turn in the healthcare industry, you find another monopolist: pharmacists and pharmacy benefit managers, group purchasing organizations, medical beds, saline and supplies. Monopoly begets monopoly.

(Unitedhealthcare is extraordinary in that its divisions are among the most powerful players in all of these sectors, making it a monopolist among monopolists – for example, UHC is the nation's largest employer of physicians:)

https://www.thebignewsletter.com/p/its-time-to-break-up-big-medicine

But there two key stakeholders in American health-care who can't monopolize: patients and health-care workers. We are the disorganized, loose, flapping ends at the beginning and end of the healthcare supply-chain. We are easy pickings for the monopolists in the middle, which is why patients pay more for worse care every year, and why healthcare workers get paid less for worse working conditions every year.

This is the one area where the Biden administration indisputably took action, bringing cases, making rules, and freaking out investment bankers and billionaires by repeatedly announcing that crimes were still crimes, even if you used an app to commit them.

The kind of treatment these apps mete out to nurses is illegal, app or no. In an important speech just last month, FTC commissioner Alvaro Bedoya explained how the FTC Act empowered the agency to shut down this kind of bossware because it is an "unfair and deceptive" form of competition:

https://pluralistic.net/2024/11/26/hawtch-hawtch/#you-treasure-what-you-measure

This is the kind of thing the FTC could be doing. Will Trump's FTC actually do it? The Trump campaign called the FTC "politicized" – but Trump's pick for the next FTC chair has vowed to politicize it even more:

https://theintercept.com/2024/12/18/trump-ftc-andrew-ferguson-ticket-fees/

Like Biden's FTC, Trump's FTC will have a target-rich environment if it wants to bring enforcement actions on behalf of workers. But Biden's trustbusters chose their targets by giving priority to the crooked companies that were doing the most harm to Americans, while Trump's trustbusters are more likely to give priority to the crooked companies that Trump personally dislikes:

https://pluralistic.net/2024/11/12/the-enemy-of-your-enemy/#is-your-enemy

So if one of these nursing apps pisses off Trump or one of his cronies, then yeah, maybe those nurses will get justice.

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[probablyasocialecologist]

Fifty per cent of web users are running ad blockers. Zero per cent of app users are running ad blockers, because adding a blocker to an app requires that you first remove its encryption, and that’s a felony. (Jay Freeman, the American businessman and engineer, calls this “felony contempt of business-model”.) So when someone in a boardroom says, “Let’s make our ads 20 per cent more obnoxious and get a 2 per cent revenue increase,” no one objects that this might prompt users to google, “How do I block ads?” After all, the answer is, you can’t. Indeed, it’s more likely that someone in that boardroom will say, “Let’s make our ads 100 per cent more obnoxious and get a 10 per cent revenue increase.” (This is why every company wants you to install an app instead of using its website.) There’s no reason that gig workers who are facing algorithmic wage discrimination couldn’t install a counter-app that co-ordinated among all the Uber drivers to reject all jobs unless they reach a certain pay threshold. No reason except felony contempt of business model, the threat that the toolsmiths who built that counter-app would go broke or land in prison, for violating DMCA 1201, the Computer Fraud and Abuse Act, trademark, copyright, patent, contract, trade secrecy, nondisclosure and noncompete or, in other words, “IP law”. IP isn’t just short for intellectual property. It’s a euphemism for “a law that lets me reach beyond the walls of my company and control the conduct of my critics, competitors and customers”. And “app” is just a euphemism for “a web page wrapped in enough IP to make it a felony to mod it, to protect the labour, consumer and privacy rights of its user”.

[humanrightsupdates]

Mexico Moves to Protect Platform Workers’ Rights

Amendment Grants Platform Workers Access to Healthcare, Pension

Mexico’s congress has approved an amendment to the country’s federal labor law to uphold the labor rights of workers for digital labor platforms.

The amendment reclassifies workers to “employees” from “independent contractors” when their monthly income from digital labor platforms – such as Uber and Didi – exceeds the minimum wage (approximately USD$415 per month). This change grants them access to the social security system, which provides health care, old-age pensions, and paid sick leave. It also ensures workers can set their own working hours and guarantees their right to unionize, marking a significant step forward in safeguarding platform workers’ rights.

The amendment will come into force once signed by President Claudia Sheinbaum, who proposed it.

Human Rights Watch has documented how digital labor platforms use opaque and ever-changing algorithms to allocate jobs and determine pay rates, offering workers no transparency into how their work is allocated and paid, and no meaningful ways to challenge these decisions. This amendment attempts to address this by requiring companies to publish transparent policies on how algorithms are used to assign tasks, and how these policies impact workers. This provision, along with others providing legal recourse and complaints mechanisms in situations of rights violations, could significantly help safeguard workers’ rights.

The bill also tackles violence and harassment that, too often, is a feature of digital platform work, especially for women workers. The law requires platform companies to adopt a gender-sensitive approach and ensure workers are protected from discrimination and harassment. In 2022, Mexico ratified the International Labour Organization’s Convention on Violence and Harassment, making a commitment to eliminate violence and harassment at work.

[insert-witty-user-name-here]

50+ Good Things from the Biden Administration

Just a list of 50+ good things the Biden Administration has done in the last 4 years because I’ve been hearing too much rhetoric that it doesn’t matter who you vote for. It does make a difference. 

Increased access to healthcare and specifically codified protections for LGBTQ+ patients against discrimination. (x) 

Strengthened women's reproductive rights by increasing access to reproductive health care, improving confidentiality to protect against criminalization for patients receiving reproductive care, and revoked Medicaid waivers from states that would exclude providers like Planned Parenthood, and more. (x)

Expanded healthcare and benefits for veterans through the PACT Act (x)

Cemented protections for pregnant and postpartum workers through the Pregnant Workers Fairness Act and PUMP for Nursing Mothers Act. 

Improved access to nursing homes for those who receive Medicaid services and established, for the first time, a national minimum staffing requirement for nursing homes to ensure those in their care receive sufficient support.  (x) 

Lowered healthcare costs for those with Medicare which capped insulin for seniors at $35 a month, made vaccines free, and capped seniors’ out of pocket expenses at the pharmacy through the Inflation Reduction Act. 

Fully vaccinated 79% of American adults against COVID-19 (I know this is old news now this is a big deal) 

Banned unfair practices that hide housing fees from renters and homebuyers when moving into a new home (x) 

Reduced the mortgage insurance premium for Federal Housing Administration (FHA) mortgages and clarified that inflated rents caused by algorithmic use of sensitive nonpublic pricing and supply information violate antitrust laws. (x) 

Increased protections for those saving for retirement from predatory practices. (x)

Helped millions of households gain access to the internet through the Affordable Connectivity Program. (x) 

Restored net neutrality (net neutrality is a standard which ensures broadband internet service is essential and prohibits interna providers from blocking, engaging in paid prioritization, and more.) (x)

Increased protections for loan holders as well as increased access to loans (x)

Cut fees that banks charge consumers for overdrawing on their accounts. (x)

Reaffirmed HUD’s commitment to remedy housing discrimination under the Fair Housing Act (which was– surprise, surprise– halted under the Trump administration). (x)

Rejoined the Paris Climate Accords.  

Listed more than 24 million acres of public lands across the country as environmentally protected and has channeled more than $18 billion dollars toward conservation projects. (And revoked the permit for the Keystone XL pipeline amongst others). 

Invested $369 billion to reduce greenhouse emissions and promote clean energy technologies through the Inflation Reduction Act. Through the tax incentives under the Inflation Reduction Act, renewable energy (such as wind, solar, and hydropower) has surpassed coal-fired generation in the electric power sector for the first time, making it the second-biggest source of energy behind natural gas. (x)

Strengthened protections against workplace assault through the Speak Out Act. (x) 

Increased protections for workers during the union bargaining process (x)

Is making it easier for passengers to obtain refunds when airlines cancel or significantly change their flights, significantly delay their bags, or fail to provide extra services when purchased. (x)  

Invested $1.2 trillion into roads, waterlines, broadband networks, airports and more allowing for more bridges, railroads, tunnels, roads, and more through the Inflation Reduction Act (which also added 670,000 jobs). (idk about you but I like driving on well maintained roads and having more rail options).  

Strengthened overtime protections for federal employees (x)

Raised the minimum wage for federal workers and contractors to $15. (x)

Strengthened protections for farmworkers by expanding the activities protected from retaliation by the National Labor Relations Act and more. (Previously anti-retaliation provisions under the National Labor Relations Act applies mostly to only U.S. citizens) (x)

Invested $80 billion for the Internal Revenue Service to hire new agents, audit the wealth, modernize its technology, and more. Additionally, created $300 billion in new revenue through corporate tax increases. (x) 

Lowered the unemployment rate to 3.5% — the lowest in 50 years. 

Canceled over $140B of student debt for nearly 40 million borrowers. (x)

Strengthened protections for sexual assault survivors, pregnant and parenting students, and LGBTQ+ students in schools through an updated Title IX rule. This updated rule strengthens sexual assault survivors rights to investigation– something that had been gutted under the Trump administration, strengthens requirements that schools provide modifications for students based on pregnancy, prohibits harassment based on sexual orientation or gender identity, and more. (x)

Revoked an order that limited diversity and inclusion training. (x)

Cracked down on for profit colleges. (x)

Reaffirmed students’ federal civil rights protections for non-discrimination based on race, national origin, disability, religion, sexual orientation, gender in schools. Specifically, the Department of Education made clear students with disabilities’ right to school, limiting the use of out of school suspensions and expulsions against them. (x) (x) 

Enhanced the Civil Rights Data Collection, a national survey that captures data on students’ equal access to educational opportunities. These changes will improve the tracking of civil rights violations for students, critical for advocates to respond to instances of discrimination. 

Provided guidance on how colleges and universities can still uphold racial diversity in higher education following the Supreme Court decision overturning affirmative action. (x) 

Issued a federal pardon to all prior Federal offenses of simple possession of marijuana. Additionally, the DEA is taking steps to reclassify marijuana as a Schedule III substance instead of a Schedule I, limiting punishment for possession in the future. (x) 

Changed drug charges related to crack offenses, now charging crack offenses as powder cocaine offenses. This is a big step towards ending the racial disparity that punishes crack offenses with greater severity than offenses involving the same amount of powder cocaine. (x) 

Lowered the cost of local calls for incarcerated people through the Martha Wright-Reed Just and Reasonable Communications Act as well as increased access for video calls (especially impactful for incarcerated people with disabilities). (x) 

Enacted policing reforms that banned chokeholds, restricted no-knock entries, and restricted the transfer of military equipment to local police departments. (x)

Established the National Law Enforcement Accountability Database (NLEAD) which will better track police officer misconduct. This database will vet federal law enforcement candidates who have a history of misconduct from being rehired and will make it easier and faster to charge police officers under the Death in Custody Reporting Act. (x) 

Added disability as a protected characteristic alongside race, gender, religion, and sexual orientation. Under the law, police officers are prohibited from profiling people based on these characteristics. …It sadly happens anyway but now there’s an added legal protection which means a mechanism to convict police officers should they break the law. (x) 

Required federal prisons to place incarcerated individuals consistent with their chosen pronouns and gender identity. (x) 

Expanded gun background checks by narrowing the “boyfriend” loophole to keep guns out of the hands of convicted dating partners, strengthening requirements for registering as a licensed gun dealer (closing the “gun show loophole”), and more through the Bipartisan Safer Communities Act.  (x) 

Increased mental health programs within police departments to support officers experiencing substance use disorders, mental health issues, or trauma from their duties. (x)

Lifted Trump era restrictions on the use of consent decrees. The Justice Department uses consent decrees to force local government agencies (like police departments) to eliminate bad practices (such as widespread abuse and misconduct) that infringe on peoples’ civil rights. (x) 

Improved reporting of hate crimes through the COVID-19 Hate Crimes Act (x) 

Nominated the first Black woman to sit on the Supreme Court 

Confirmed 200 lifetime judges to federal courts, confirming historic numbers of women, people of color, and other judges who have long been excluded from our federal court system. (64% are women, 63% are people of color) 

Designated Temporary Protected Status (TPS) status for immigrants from Cameroon, Haiti, ​​El Salvador, Haiti, Honduras, Nepal, Nicaragua, Sudan, and more. (x) 

Ended the discriminatory Muslim and African bans (x). 

Provided a pathway to citizenship for spouses of U.S. citizens that have been living in the country without documentation. (x) 

Expanded healthcare to DACA recipients (x) 

This one is… barely a win but not by fault of the Biden Administration. The Department of Homeland Security as of Feb 2023 has reunited nearly 700 immigrant children that were separated from their families under Trump’s Zero Tolerance Policy. From 2017-2021, 3,881 children were separated from their families. About 74% of those have been reunited with their families: 2,176 before the task force was created and 689 afterward. But that still leaves nearly 1,000 children who remain tragically separated from their families from under the Trump Administration. (x)

(okay this one is maybe only exciting for me who’s a census nerd) Revised federal standards for the collection of race and ethnicity data, allowing for federal data that better reflect the country’s diversity. Now, government forms will include a Middle Eastern/ North African category (when previously those individuals would check “white”). Additionally, forms will now have combined the race & ethnicity question allowing for individuals to check “Latino/a” as their race (previously Latine individuals would be encouraged to check “Latino” for ethnicity and “white” for race… which doesn’t really resonate with many folks). (x) (I know this sounds boring but let me tell you this is BIG when it comes to better data collection– and better advocacy!).

Rescinded a Trump order that would have excluded undocumented immigrants from the 2020 Census which would have taken away critical funds from those communities. 

Required the U.S. federal government and all U.S. states and territories to recognize the validity of same-sex and interracial civil marriages by passing the Respect for Marriage Act, repealing the Defense of Marriage Act.

Reversed Trump’stransgender military ban. 

Proposed investments in a lot of programs including universal pre-k, green energy, mental health programs across all sectors, a national medical leave program for all workers and more. (x) 

Last… let’s also not forget all the truly terrible things Trump did when he was in office. If you need a reminder, scroll this list, this one mostly for giggles + horror, for actual horror about what a Trump presidency has in store, learn about ‘Project 2025’ from the Heritage Foundation. I know this post is about reasons to vote FOR Biden but let’s not forget the many, many reasons to vote for him over Trump. 

So, there it is, 50+ reasons to vote for Biden in the 2024 Election. 

Check your voter registration here, make a plan to vote, and encourage your friends to vote as well. 

All in all, yeah… there’s a lot of shitty things still happening. There’s always going to be shit but things aren’t going to change on their own. And that change starts (it certainly doesn’t end) with voting. 

Go vote in November. 

[marithlizard]

While I like you all too much to reblog mile-long technopolitical screeds onto your dash, @mostlysignssomeportents does have a lot of interesting informative things to say. Worth a read if you want to understand more of why everything sucks so hard in 2024. "Every Uber driver is offered a different wage for every job. If a driver has been picky lately, the job pays more. But if the driver has been desperate enough to grab every ride the app offers, the pay goes down, and down, and down.

The law professor Veena Dubal calls this ‘algorithmic wage discrimination.' It’s a prime example of twiddling."

[madfishmonger]

An interesting article with a little hope for the future but also I think some of you worker's rights protesters might be interested in this bit:

A gherao is a kind of protest in which employees refuse to let their managers or superiors leave the workplace until their demands are satisfied. The gherao originated in West Bengal when Subodh Banerjee, who was first labor minister then head of the public works department in the United Front Government of West Bengal in the late 1960s, introduced it as a formal means of protest in the labor sector. The gherao has been deployed time and time again as a tactic to protest against corporations and government actions since then.

[anniekoh]

elsewhere on the internet: technology platforms & AI

The Limitations of ChatGPT with Emily Bender and Casey Fiesler

The Radical AI podcast (March 2023)

In this episode, we unpack the limitations of ChatGPT. We interview Dr. Emily M. Bender and Dr. Casey Fiesler about the ethical considerations of ChatGPT, bias and discrimination, and the importance of algorithmic literacy in the face of chatbots.

Emily M. Bender is a Professor of Linguistics and an Adjunct Professor in the School of Computer Science and the Information School at the University of Washington, where she has been on the faculty since 2003. Her research interests include multilingual grammar engineering, computational semantics, and the societal impacts of language technology. Emily was also recently nominated as a Fellow of the American Association for the Advancement of Science (AAAS).

Casey Fiesler is an associate professor in Information Science at University of Colorado Boulder. She researches and teaches in the areas of technology ethics, internet law and policy, and online communities. Also a public scholar, she is a frequent commentator and speaker on topics of technology ethics and policy, and her research has been covered everywhere from The New York Times to Teen Vogue.

Will A.I. Become the New McKinsey? by Ted Chiang (The New Yorker, May 2023)

People who criticize new technologies are sometimes called Luddites, but it’s helpful to clarify what the Luddites actually wanted. The main thing they were protesting was the fact that their wages were falling at the same time that factory owners’ profits were increasing, along with food prices. They were also protesting unsafe working conditions, the use of child labor, and the sale of shoddy goods that discredited the entire textile industry. The Luddites did not indiscriminately destroy machines; if a machine’s owner paid his workers well, they left it alone. The Luddites were not anti-technology; what they wanted was economic justice. They destroyed machinery as a way to get factory owners’ attention.

Whenever anyone accuses anyone else of being a Luddite, it’s worth asking, is the person being accused actually against technology? Or are they in favor of economic justice? And is the person making the accusation actually in favor of improving people’s lives? Or are they just trying to increase the private accumulation of capital?

In 1980, it was common to support a family on a single income; now it’s rare. So, how much progress have we really made in the past forty years? Sure, shopping online is fast and easy, and streaming movies at home is cool, but I think a lot of people would willingly trade those conveniences for the ability to own their own homes, send their kids to college without running up lifelong debt, and go to the hospital without falling into bankruptcy. It’s not technology’s fault that the median income hasn’t kept pace with per-capita G.D.P.; it’s mostly the fault of Ronald Reagan and Milton Friedman. But some responsibility also falls on the management policies of C.E.O.s like Jack Welch, who ran General Electric between 1981 and 2001, as well as on consulting firms like McKinsey. I’m not blaming the personal computer for the rise in wealth inequality—I’m just saying that the claim that better technology will necessarily improve people’s standard of living is no longer credible.

[Image shows Stable Diffusion generated images for “Committed Janitor”]

Researchers Find Stable Diffusion Amplifies Stereotypes by Justin Hendrix (Tech Policy, Nov 2022)

Sasha Luccioni, an artificial intelligence (AI) researcher at Hugging Face, a company that develops AI tools, recently released a project she calls the Stable Diffusion Explorer. With a menu of inputs, a user can compare how different professions are represented by Stable Diffusion, and how variables such as adjectives may alter image outputs. An “assertive firefighter,” for instance, is depicted as white male. A “committed janitor” is a person of color.

A talk: How To Find Things Online by v buckenham (May 2023)

And the other way to look at this, really, is not about AI at all, but seeing this as the continuation of a gradual corporate incursion into the early spirit of sharing that characterised the internet. I say incursion but maybe the better word is enclosure, as in enclosure of the commons. And this positions AI as just a new method by which companies try to extract value from the things people share freely, and capture that value for themselves. And maybe the way back from this is being more intentional about building our communities in ways where the communities own them. GameFAQs was created to collate some useful stuff together for a community, and it ended up as part of a complicated chain of corporate mergers and acquisitions. But other communities experienced the kinds of upheaval that came with that, and then decided to create their own sites which can endure outside of that - I’m thinking here especially of Archive of Our Own, the biggest repository for fan-writing online. And incidentally, the source of 8.2 million words in that AI training set, larger even than Reddit.

The technologies of all dead generations by Ben Tarnoff  (Apr 2023)

The three waves of algorithmic accountability

First wave: Harm reduction

Second wave: Abolition

Third wave: Alternatives

The third wave of algorithmic accountability, then, is already in motion. It’s a welcome development, and one that I wholeheartedly support.

But I’m also wary of it. There is a sense of relief when one moves from critique to creation. It satisfies the familiar American impulse to be practical, constructive, solution-oriented. And this introduces a danger, which is that in the comfort we derive from finally doing something rather than just talking and writing and analyzing and arguing, we get too comfortable, and act without an adequate understanding of the difficulties that condition and constrain our activity.

Platforms don't exist by Ben Tarnoff (Nov 2019)

By contrast, a left tech policy should aim to make markets mediate less of our lives—to make them less central to our survival and flourishing. This is typically referred to as decommodification, and it’s closely related to another core principle, democratization. Capitalism is driven by continuous accumulation, and continuous accumulation requires the commodification of as many things and activities as possible. Decommodification tries to roll this process back, by taking certain things and activities off the market. This lets us do two things: 1. The first is to give everybody the resources (material and otherwise) that they need to survive and to flourish—as a matter of right, not as a commodity. People get what they need, not just what they can afford. 2. The second is to give everybody the power to participate in the decisions that most affect them.

[glaxitsoftwareagency]

The Risks of Over-Reliance on AI

The Risks of Artificial Intelligence

Artificial Intelligence (AI) is revolutionizing various fields, but it might also pose serious risks. Experts like Geoffrey Hinton and Elon Musk have warned about AI’s unchecked growth. The increasing automation of decision-making processes can reduce human judgment and critical thinking. AI is now being integrated into critical areas such as healthcare, finance, and governance, where mistakes could have severe consequences. Without proper oversight, AI could lead to unintended consequences that negatively affect society. Therefore, policymakers, researchers, and industry leaders must work together to create regulations that ensure AI remains a beneficial tool rather than a disruptive force.

Lack of Transparency and Explainability

AI decision-making processes are often complex, making it difficult for users to understand how decisions are made. Many AI companies should be more transparent, but secrecy often prevails. The lack of clear explanations can make AI systems unreliable, especially in high-stakes industries such as healthcare and banking. If AI systems are not explainable, people might lose trust in them, leading to resistance to AI adoption. Regulators must establish guidelines to ensure that AI applications remain accountable. With proper transparency, AI could become a more trustworthy and widely accepted tool across various sectors.

Job Loss and Economic Disruptions

AI-driven automation is replacing human jobs at an alarming rate, particularly in manufacturing, customer service, and logistics. Many workers must learn new skills to remain employable, but companies often fail to provide adequate training programs. The wage gap could increase because AI takes over repetitive tasks, leaving lower-skilled workers unemployed or underpaid.

Small businesses may struggle to compete with large corporations that can afford AI-driven operations, leading to market monopolization.

Governments should invest in reskilling programs to prevent economic instability and help workers transition to new careers in AI-related fields.

AI can boost productivity, but without a balanced approach, it may also widen income inequality, creating social unrest.

Strategies to Mitigate AI Risks

Social Manipulation and Misinformation

AI-powered tools can spread misinformation rapidly, making it hard to distinguish truth from lies. Deepfakes and AI-generated content may deceive the public, leading to political and social instability. Social media algorithms could be used to manipulate public opinion. Educating people about AI’s role in misinformation is essential to maintain informed societies.

Biases and Discrimination in AI

AI has been found to reinforce biases in hiring and decision-making.

Gender, race, and socioeconomic disparities must be addressed in AI training data.

Unfair AI systems might deny people opportunities without valid reasons.

Developers should ensure AI fairness by improving training datasets.

Autonomous Weapons and Military Use of AI

The military is investing heavily in AI-driven weaponry. AI-controlled drones can make lethal decisions without human intervention. Ethical concerns must be discussed before AI takes full control of warfare. If AI warfare escalates, global conflicts could become more dangerous and unpredictable.

Decreasing Human Influence and Ethical Considerations

AI might replace human creativity in decision-making.

Over-reliance on AI can reduce emotional intelligence and critical thinking.

Ethical concerns must be debated to prevent unjust AI decisions.

Humans should maintain a balance between AI efficiency and personal insight.

AI Criminal Activities and Cyber Threats

Hackers have started using AI for cybercrimes and fraud. AI might enable deepfake scams that manipulate public figures. AI-driven cyberattacks can break security systems faster than ever before, so security experts must develop stronger defense mechanisms against AI threats.

The Risk of Self-Aware and Uncontrollable AI

Artificial General Intelligence (AGI) might surpass human intelligence.

Ethical dilemmas should be considered before AGI development.

If AI becomes fully autonomous, controlling it will be difficult.

Researchers must create safeguards to prevent AI from acting against humanity.

Broader Economic and Political Instability

AI could significantly reshape industries and impact global economies. Overinvestment in AI may lead to economic bubbles. Nations could struggle with regulating AI at an international level. Governments should collaborate to create unified policies for AI governance.

Strategies to Mitigate AI Risks

Legal regulations should be implemented to ensure AI accountability.

Ethical AI development must be prioritized to reduce negative impacts.

AI innovation should be balanced with societal safety and protection.

Transparency and explainability must be improved in AI systems.

AI Benefits vs. Risks

Benefits of AIRisks of AIIncreased efficiency and automationJob loss and economic inequalityImproved accuracy in decision-makingMisinformation and social manipulationEnhanced convenience in daily lifePrivacy violations and surveillanceBetter healthcare diagnosticsAI biases and discriminationAdvanced security and fraud detectionAI-driven cyber threats

Conclusion

AI should be used responsibly to prevent potential risks. While it can improve various aspects of life, blind trust in AI might be dangerous. Governments, industries, and individuals must work together to ensure AI remains a tool for progress rather than a societal threat.

[qhalalimited]

Are platform workers thriving? A deep dive into Kenya’s platform economy.

https://jpcdn.it/img/d3c2d92444cb7635ebc79fb6a27f9cc8.jpg

In their third year¹, researchers from Qhala Limited are implementing Fairwork in Kenya as they seek to highlight the best and worst companies in the Kenyan platform economy according to how they treat their workers. Within the last three years, this industry has experienced the ravages of the COVID-19 pandemic as well as an election year that exposed the precarious situations that workers faced. Platform workers were directly affected and experienced a significant impact on their livelihoods. With the rise of food and essential goods and fuel costs, platform workers have had to work longer hours or quit the industry altogether for it to make financial sense.

The Digital Economy Blueprint² envisages a nation where every citizen has the capability to participate and thrive in the digital economy. However, as Fairwork Kenya 2022 Report observed, Kenyan platform workers are yet to realise this vision. The following were the key findings in last year’s Report:

Fair Pay: There was insufficient evidence that workers for any of the nine platforms earn the minimum wage of KES 15,121 ($122) after costs or the living wage of KES 25,400 ($204) after work-related costs.

Fair Conditions: Only Glovo and Uber out of nine platforms could evidence policies to prevent work-related risks like offering insurance, emergency SOS buttons and safety training. Glovo also provides safety gear like helmets and reflector jackets, but not always for free. Glovo got a second point for offering compensation for workers who cannot work due to sickness, accidents, or unforeseen circumstances.

Fair Contracts: Only Bolt, Uber, Glovo and Little provide clear and transparent terms and conditions subject to Kenyan law.

Fair Management: Only Glovo, Little, and SweepSouth demonstrated effective communication channels and appeals processes, for example if workers are deactivated from the platform. But no platform could evidence having an anti-discrimination policy and clarity on how they use algorithms.

Fair Representation: Only Little and SweepSouth could evidence that they ensure freedom of association and are willing to negotiate with workers. Little went one step ahead by signing a Memorandum of Understanding (MOU) with the Organisation of Online Drivers (OOD).

https://justpaste.it/!https://miro.medium.com/v2/resize:fit:875/1*6TEhmgEKxoQSdD1PRtpyBA.png

The researchers from Qhala are back at it this year! In the previous years, they rated 9 platforms. In 2023, they have increased the number of platforms to 12. These are: Bolt, Bolt Food, Faras, Glovo, In Drive, Jumia Food, Little Delivery, Little Ride, Uber Kenya, Uber Eats, Wasili, and Yego. These platforms are being evaluated against the five principles of Fairwork, with the overall goal of this exercise being to shape a future of work made up of better and fairer jobs. With the Report Launch set for September 2023, and with 120 platform workers interviewed and evidence from the platforms trickling in, some themes have already started taking shape, namely: The high cost of living, the reality of women platform workers, and the role of collective workers’ union in the industry. The Report will also seek to answer whether indeed — as the Kenyan government hopes to be the case — platform workers are thriving in Kenya’s flourishing digital economy.

As we await the Report, we are also seeking to engage with organisations, whether current or potential users of platform labour, that would like to demonstrate their public commitment to fairer platform work.

Organisations like universities, schools, businesses, and charities can make a difference by committing to use fairer platforms guided by our Fairwork principles and ratings.

Local governments and administrations can support fairer platform work by introducing meaningful regulation that encourages minimum standards for platforms operating in their areas, or which are eligible for public funding.

Socially responsible investors or rating agencies can help improve the working conditions of gig workers by making sure that they, or their clients, invest only in those platforms that offer better labour standards.

There may be further ways for you to support our efforts to contribute to a fairer future of platform work, demonstrate this support to the wider public, and create meaningful change that we can explore together!

Interested? Fill out this form to sign up as a partner or supporter. It takes 1 minute! https://fair.work/en/fw/join-the-pledge/

[mostlysignssomeportents]

The cod-Marxism of personalized pricing

Picks and Shovels is a new, standalone technothriller starring Marty Hench, my two-fisted, hard-fighting, tech-scam-busting forensic accountant. You can pre-order it on my latest Kickstarter, which features a brilliant audiobook read by Wil Wheaton.

The social function of the economics profession is to explain, over and over again, that your boss is actually right and that you don't really want the things you want, and you're secretly happy to be abused by the system. If that wasn't true, why would your "choose" commercial surveillance, abusive workplaces and other depredations?

In other words, economics is the "look what you made me do" stick that capitalism uses to beat us with. We wouldn't spy on you, rip you off or steal your wages if you didn't choose to use the internet, shop with monopolists, or work for a shitty giant company. The technical name for this ideology is "public choice theory":

https://pluralistic.net/2022/06/05/regulatory-capture/

Of all the terrible things that economists say we all secretly love, one of the worst is "price discrimination." This is the idea that different customers get charged different amounts based on the merchant's estimation of their ability to pay. Economists insist that this is "efficient" and makes us all better off. After all, the marginal cost of filling the last empty seat on the plane is negligible, so why not sell that seat for peanuts to a flier who doesn't mind the uncertainty of knowing whether they'll get a seat at all? That way, the airline gets extra profits, and they split those profits with their customers by lowering prices for everyone. What's not to like?

Plenty, as it turns out. With only four giant airlines who've carved up the country so they rarely compete on most routes, why would an airline use their extra profits to lower prices, rather than, say, increasing their dividends and executive bonuses?

For decades, the airline industry was the standard-bearer for price discrimination. It was basically impossible to know how much a plane ticket would cost before booking it. But even so, airlines were stuck with comparatively crude heuristics to adjust their prices, like raising the price of a ticket that didn't include a Saturday stay, on the assumption that this was a business flyer whose employer was footing the bill:

https://pluralistic.net/2024/06/07/drip-drip-drip/#drip-off

With digitization and mass commercial surveillance, we've gone from pricing based on context (e.g. are you buying your ticket well in advance, or at the last minute?) to pricing based on spying. Digital back-ends allow vendors to ingest massive troves of commercial surveillance data from the unregulated data-broker industry to calculate how desperate you are, and how much money you have. Then, digital front-ends – like websites and apps – allow vendors to adjust prices in realtime based on that data, repricing goods for every buyer.

As digital front-ends move into the real world (say, with digital e-ink shelf-tags in grocery stores), vendors can use surveillance data to reprice goods for ever-larger groups of customers and types of merchandise. Grocers with e-ink shelf tags reprice their goods thousands of times, every day:

https://pluralistic.net/2024/03/26/glitchbread/#electronic-shelf-tags

Here's where an economist will tell you that actually, your boss is right. Many groceries are perishable, after all, and e-ink shelf tags allow grocers to reprice their goods every minute or two, so yesterday's lettuce can be discounted every fifteen minutes through the day. Some customers will happily accept a lettuce that's a little gross and liztruss if it means a discount. Those customers get a discount, the lettuce isn't thrown out at the end of the day, and everyone wins, right?

Well, sure, if. If the grocer isn't part of a heavily consolidated industry where competition is a distant memory and where grocers routinely collude to fix prices. If the grocer doesn't have to worry about competitors, why would they use e-ink tags to lower prices, rather than to gouge on prices when demand surges, or based on time of day (e.g. making frozen pizzas 10% more expensive from 6-8PM)?

And unfortunately, groceries are one of the most consolidated sectors in the modern world. What's more, grocers keep getting busted for colluding to fix prices and rip off shoppers:

https://www.cbc.ca/news/business/loblaw-bread-price-settlement-1.7274820

Surveillance pricing is especially pernicious when it comes to apps, which allow vendors to reprice goods based not just on commercially available data, but also on data collected by your pocket distraction rectangle, which you carry everywhere, do everything with, and make privy to all your secrets. Worse, since apps are a closed platform, app makers can invoke IP law to criminalize anyone who reverse-engineers them to figure out how they're ripping you off. Removing the encryption from an app is a potential felony punishable by a five-year prison sentence and a $500k fine (an app is just a web-page skinned in enough IP to make it a crime to install a privacy blocker on it):

https://pluralistic.net/2024/08/15/private-law/#thirty-percent-vig

Large vendors love to sell you shit via their apps. With an app, a merchant can undetectably change its prices every few seconds, based on its estimation of your desperation. Uber pioneered this when they tweaked the app to raise the price of a taxi journey for customers whose batteries were almost dead. Today, everyone's getting in on the act. McDonald's has invested in a company called Plexure that pitches merchants on the use case of raising the cost of your normal breakfast burrito by a dollar on the day you get paid:

https://pluralistic.net/2024/06/05/your-price-named/#privacy-first-again

Surveillance pricing isn't just a matter of ripping off customers, it's also a way to rip off workers. Gig work platforms use surveillance pricing to titrate their wage offers based on data they buy from data brokers and scoop up with their apps. Veena Dubal calls this "algorithmic wage discrimination":

https://pluralistic.net/2023/04/12/algorithmic-wage-discrimination/#fishers-of-men

Take nurses: increasingly, American hospitals are firing their waged nurses and replacing them with gig nurses who are booked in via an app. There's plenty of ways that these apps abuse nurses, but the most ghastly is in how they price nurses' wages. These apps buy nurses' financial data from data-brokers so they can offer lower wages to nurses with lots of credit card debt, on the grounds that crushing debt makes nurses desperate enough to accept a lower wage:

https://pluralistic.net/2024/12/18/loose-flapping-ends/#luigi-has-a-point

This week, the excellent Lately podcast has an episode on price discrimination, in which cohost Vass Bednar valiantly tries to give economists their due by presenting the strongest possible case for charging different prices to different customers:

https://www.theglobeandmail.com/podcasts/lately/article-the-end-of-the-fixed-price/

Bednar really tries, but – as she later agrees – this just isn't a very good argument. In fact, the only way charging different prices to different customers – or offering different wages to different workers – makes sense is if you're living in a socialist utopia.

After all, a core tenet of Marxism is "from each according to his ability, to each according to his needs." In a just society, people who need more get more, and people who have less, pay less:

https://en.wikipedia.org/wiki/From_each_according_to_his_ability,_to_each_according_to_his_needs

Price discrimination, then, is a Bizarro-world flavor of cod-Marxism. Rather than having a democratically accountable state that sets wages and prices based on need and ability, price discrimination gives this authority to large firms with pricing power, no regulatory constraints, and unlimited access to surveillance data. You couldn't ask for a neater example of the maxim that "What matters isn't what technology does. What matters is who it does it for; and who it does it to."

Neoclassical economists say that all of this can be taken care of by the self-correcting nature of markets. Just give consumers and workers "perfect information" about all the offers being made for their labor or their business, and things will sort themselves out. In the idealized models of perfectly spherical cows of uniform density moving about on a frictionless surface, this does work out very well:

https://pluralistic.net/2023/04/03/all-models-are-wrong/#some-are-useful

But while large companies can buy the most intimate information imaginable about your life and finances, IP law lets them capture the state and use it to shut down any attempts you make to discover how they operate. When an app called Para offered Doordash workers the ability to preview the total wage offered for a job before they accepted it, Doordash threatened them with eye-watering legal penalties, then threw dozens of full-time engineers at them, changing the app several times per day to shut out Para:

https://pluralistic.net/2021/08/07/hr-4193/#boss-app

And when an Austrian hacker called Mario Zechner built a tool to scrape online grocery store prices – discovering clear evidence of price-fixing conspiracies in the process – he was attacked by the grocery cartel for violating their "IP rights":

https://pluralistic.net/2023/09/17/how-to-think-about-scraping/

This is Wilhoit's Law in action:

Conservatism consists of exactly one proposition, to wit: There must be in-groups whom the law protects but does not bind, alongside out-groups whom the law binds but does not protect.

https://en.wikipedia.org/wiki/Francis_M._Wilhoit#Wilhoit's_law

Of course, there wouldn't be any surveillance pricing without surveillance. When it comes to consumer privacy, America is a no-man's land. The last time Congress passed a new consumer privacy law was in 1988, when they enacted the Video Privacy Protection Act, which bans video-store clerks from revealing which VHS cassettes you take home. Congress has not addressed a single consumer privacy threat since Die Hard was still playing in theaters.

Corporate bullies adore a regulatory vacuum. The sleazy data-broker industry that has festered and thrived in the absence of a modern federal consumer privacy law is absolutely shameless. For example, every time an app shows you an ad, your location is revealed to dozens of data-brokers who pretend to be bidding for the right to show you an ad. They store these location data-points and combine them with other data about you, which they sell to anyone with a credit card, including stalkers, corporate spies, foreign governments, and anyone hoping to reprice their offerings on the basis of your desperation:

https://www.404media.co/candy-crush-tinder-myfitnesspal-see-the-thousands-of-apps-hijacked-to-spy-on-your-location/

Under Biden, the outgoing FTC did incredible work to fill this gap, using its authority under Section 5 of the Federal Trade Commission Act (which outlaws "unfair and deceptive" practices) to plug some of the worst gaps in consumer privacy law:

https://pluralistic.net/2024/07/24/gouging-the-all-seeing-eye/#i-spy

And Biden's CFPB promulgated a rule that basically bans data brokers:

https://pluralistic.net/2024/06/10/getting-things-done/#deliverism

But now the burden of enforcing these rules falls to Trump's FTC, whose new chairman has vowed to end the former FTC's "war on business." What America desperately needs is a new privacy law, one that has a private right of action (so that individuals and activist groups can sue without waiting for a public enforcer to take up their causes) and no "pre-emption" (so that states can pass even stronger privacy laws):

https://www.eff.org/deeplinks/2022/07/federal-preemption-state-privacy-law-hurts-everyone

How will we get that law? Through a coalition. After all, surveillance pricing is just one of the many horrors that Americans have to put up with thanks to America's privacy law gap. The "privacy first" theory goes like this: if you're worried about social media's impact on teens, or women, or old people, you should start by demanding a privacy law. If you're worried about deepfake porn, you should start by demanding a privacy law. If you're worried about algorithmic discrimination in hiring, lending, or housing, you should start by demanding a privacy law. If you're worried about surveillance pricing, you should start by demanding a privacy law. Privacy law won't entirely solve all these problems, but none of them would be nearly as bad if Congress would just get off its ass and catch up with the privacy threats of the 21st century. What's more, the coalition of everyone who's worried about all the harms that arise from commercial surveillance is so large and powerful that we can get Congress to act:

https://pluralistic.net/2023/12/06/privacy-first/#but-not-just-privacy

Economists, meanwhile, will line up to say that this is all unnecessary. After all, you "sold" your privacy when you clicked "I agree" or walked under a sign warning you that facial recognition was in use in this store. The market has figured out what you value privacy at, and it turns out, that value is nothing. Any kind of privacy law is just a paternalistic incursion on your "freedom to contract" and decide to sell your personal information. It is "market distorting."

In other words, your boss is right.

Check out my Kickstarter to pre-order copies of my next novel, Picks and Shovels!

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2025/01/11/socialism-for-the-wealthy/#rugged-individualism-for-the-poor

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

--

Ser Amantio di Nicolao (modified) https://commons.wikimedia.org/wiki/File:Safeway_supermarket_interior,_Fairfax_County,_Virginia.jpg

CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0/deed.en

[meret118]

Experts say algorithmic wage discrimination and A.I.-influenced pay more broadly are creeping into a growing number of fields, such as health care, logistics, and tech, and could upend work as we know it.

. . .

“Now you have machine learning trained on identifying the desperation index of workers,” Zephyr Teachout, a professor of law at Fordham University, told me. “When you move to the formal employment context, there is every reason to think that employers who can would be interested in tailoring their wages and using behavioral data.”

The clearest parallels can be drawn in other independent contractor roles, which make uparound 15 percent of U.S. workers. Dubal has found that independent contractors working with Instacart and Amazon are similarly surveilled and receive personalized pay based on information including the times of day and length of time they work, along with the types of tasks they’re willing to accept.

On the flip side, some companies also use our data to determine the most we’re willing to pay for products, and it’s possible that we could soon face eerily hyperpersonalized prices—funeral-goers, for example, could be charged more for plane tickets. This summer, the U.S. Federal Trade Commission said it was seeking information from eight companies on so-called surveillance pricing.

[jcmarchi]

AI-Powered Solutions: How Migrants Are Overcoming Transportation Barriers in the U.S.

New Post has been published on https://thedigitalinsider.com/ai-powered-solutions-how-migrants-are-overcoming-transportation-barriers-in-the-u-s/

AI-Powered Solutions: How Migrants Are Overcoming Transportation Barriers in the U.S.

The credit scoring system in the U.S. is not only used in banking and large businesses, but also assesses the creditworthiness of every resident in every aspect of their everyday life. However, this system also discriminates against large groups of the population, particularly migrants.

For migrants and political refugees, it is extremely challenging to find official employment without the necessary legal papers and a credit check in the U.S. According to immigration laws, asylum seekers are not permitted to work officially for the first 180 days after filing their application. This bureaucratic barrier has led to an increase in low-wage labor in the food delivery sector.

How Many Migrants Face Challenges in the U.S.

As of 2022, the Migration Policy Institute reported 46.2 million legal migrants in the U.S. Another ~9M are undocumented. New York alone welcomes tens of thousands of new arrivals each year, with numbers rising significantly since Spring 2022, as over 118,000 migrants, primarily from Latin America and the Caribbean, crossed the U.S.–Mexico border, according to the Council of Foreign Relations.

Many migrants turn to the delivery sector because it offers more job opportunities under their circumstances. The popularity of this employment surged during the COVID-19 pandemic, especially during strict lockdowns.

Why Migrants Face Transportation Limitations

Working a delivery job in a large city is impossible without personal transportation. Migrants cannot take out loans for an e-bike or similar due to their lack of credit history and necessary documents, which also prevents them from registering a moped or a cars.

The cost of an electric bicycle starts at $2,000. While refurbished models are available for about half the price of new ones, this is still a significant amount for low-income migrants. Cheaper e-bikes from China tend to wear out quickly and require repairs that can exceed the initial purchase cost.

The Issue of Poor-Quality Electric Bicycles

Another problem with inexpensive transportation is the substandard lithium-ion batteries used in electric bicycles and scooters, which have become a leading cause of fires in New York. The lack of regulation and supporting infrastructure has turned this issue into a serious public safety concern.

In just the first two months of this year, New York experienced more fires caused by battery-powered vehicles than in all of 2019. This has led to stricter regulations on the electric bicycle market and their certification. Ensuring access to safe electric transportation has become a pressing social issue.

How AI Technology Addresses This Problem

Some electric bicycle rental services for couriers in the U.S. stand out. Most delivery workers are immigrants without credit histories, which limits their access to safe and affordable transportation. One potential solution is to develop a proprietary scoring system that makes expensive electric transport accessible to couriers.

Instead of relying on a standard Social Security number, proof of address, and other traditional identity verification methods, two-factor verification can be employed, based on:

Client information from external sources.

Predictions based on data and behavior of previous users.

Once a client subscribes to the service, the system’s analytics determines their creditworthiness and whether they are likely to face payment difficulties. For this development, statistical data from more than 10,000 individuals was used to create an econometric model with over 50 data points.

The algorithm decides if the rental service can be provided to the person in question, and whether a deposit is required. In case of rejection, the service offers alternatives, such as going through a credit partner or purchasing a bicycle. For approved customers, the system also determines the type of deal: rent-to-own, monthly, or weekly rental.

The automation of these processes has proven effective: over two years, less than 3% of bicycles were stolen from the company that serves 8,500 users. According to Bicycle Habit, around 15,000 bicycles are stolen annually in New York.

AI Technologies for Analyzing Clients Without Credit Scores

The following outlines the implementation stages of the “no credit scoring” analytics.

Development of a Proprietary Scoring System

Based on client database analysis, electric bicycle rental companies create their own scoring systems to assess financial reliability based on over 50 parameters, including non-financial ones. This model continuously learns, adapting to the behavior of current and past clients. Parameters can be adjusted, allowing for more complex or simplified scoring conditions. This product is designed for businesses working with clients unable to present the standard set of legal papers typically required by services in the U.S.

A simple example of data analysis

If a database shows that a potential client has multiple phone numbers or addresses that change every two months, it might indicate that they are changing them to avoid paying bills. This will be flagged by the system, but the final decision will be based on additional factors.

What else does the unconventional scoring system check?

Such a system also examines conventional financial indicators, such as history of bankruptcies or evictions. In such cases it takes into account factors like the timing of the client’s bankruptcy procedure. The decisions are then made on a case-by-case basis.

If a potential client has more than 10 different IP addresses, it suggests that they are likely using free or shared internet. The system checks the client’s residence and the payment location by IP address—if they are far apart, there is a high likelihood of fraud.

Stripe, an American online payment system, can be used to check whether the buyer’s payment method has been flagged as fraudulent by previous retailers. This helps identify fraud if a customer is pretending to be someone else.

The onboarding and scoring processes are fully automated through facial recognition and document verification technology to minimize fraud.

Simplification and Security for Low-Income Target Audiences

There are several auxiliary functions Integrated into the custom software:

Real-time tracking of electric bicycles.

Disabling of electronic components.

Alarm system and remote wheel locking.

Automated alerts based on collected data about the bicycle (e.g., trips in restricted areas, unauthorized state border crossing, prolonged absence of GPS signal).

The automation of the scoring process significantly increases the service’s conversion rate, as clients are informed in advance of the required documents and what to expect during the decision-making stage. This allows for the entire verification process to be completed in just a couple of minutes online, avoiding situations where someone arrives unprepared, either having forgotten necessary documents or unable to provide the required deposit.

Thanks to automation, the service can make instant decisions, expediting the onboarding process. As a result, the time from sign-up to receiving the vehicle has decreased from 60 to 15 minutes, and staff no longer waste time on those who have not passed onboarding.

Other Technologies Used by Rental Services

These technologies are employed by all top rental services in America, including Whizz, Joco, and Zoomo. The differences lie in their requirements; for example, Zoomo requests ID and proof of residence as a second document. Recently, they announced elimination of background checks, however their onboarding and scoring still involve manual processing, requiring customers to mail in their documents. Whizz and Joco are ahead of the competition here, having automated the process by using online verification providers.

Joco mitigates risks differently by allowing clients to use electric transport for six hours, after which the bike must be returned to the docking station for charging. This means that the users can’t take it home with them, and there is a time limitation in place as well.

Summary

Technology not only simplifies life but, through an unconventional scoring model, enhances the safety of electric bicycle use and addresses inequality among delivery workers. Thus, it can be said that technology extends a helping hand to those in difficult life situations—even to those without a credit score.

[hackernewsrobot]

Algorithmic Wage Discrimination

https://columbialawreview.org/content/on-algorithmic-wage-discrimination/

[so-true-overdue]

The Great Siege of Minds

We are under siege.

But not with guns, bombs, or tanks. This is not a war waged on streets or through armies, but a slow corrosion of the collective mind. It is an invasion waged on the invisible frontiers of consciousness, where truth becomes slippery, and certainty is a rare currency. Through the vast labyrinth of social media, Russia has perfected the art of distortion, peddling disinformation like a toxic fog that seeps into the corners of our reality, distorting it beyond recognition.

In the cacophony of this digital deluge, we find ourselves at risk of becoming unmoored, our understanding of the world fragmenting under the pressure of conflicting narratives. The algorithms, soulless and impartial, do not discriminate between fact and fiction. The sensational thrives, and the slow, methodical pursuit of truth is often drowned out by the grotesque allure of misinformation, each falsehood louder and more brazen than the last.

What is this disinformation if not a calculated ambivalence, a deliberate obfuscation that makes one question not only the facts but the very nature of truth itself? Russia, with Machiavellian dexterity, has weaponized ambiguity, turning the once solid ground of knowledge into a quagmire of doubt. The aim is simple: disorient, confuse, destabilize.

This is no trivial assault. We are witnessing an attack on the architecture of enlightenment, on the very systems that sustain democracy, civil discourse, and intellectual rigor. It is an assault on the senses, where the verifiable is juxtaposed with the absurd, creating a cognitive dissonance that numbs the faculties of reason.

But there is hope in this chaos. Verifiable journalism—rigorous, relentless, and resilient—is our bulwark. It is the antidote to ambivalence, the lighthouse in this storm. The journalist’s painstaking devotion to corroboration, their tireless pursuit of sources and evidence, this is what preserves the integrity of knowledge. Only through the lens of verifiable, empirical inquiry can we distinguish the real from the fabricated, the credible from the fantastical.

This battle for truth is not one fought with mere rhetoric, but with meticulous investigation, with the quiet, unglamorous work of verification. In a world saturated with noise, journalism that clings to the verifiable is revolutionary. It disrupts the disinformation machine not with volume but with precision.

And so, we must become defenders of this truth. Ambivalence may be the enemy’s weapon, but our shield is discernment. We must cultivate a vigilance, a skepticism not born of cynicism but of intellectual rigor. For in this war, to be ambivalent is to surrender. But to seek the truth, fiercely and without compromise, is to hold the line.

The battle rages on, but we are not defenseless.

[ericvanderburg]

Algorithmic wage discrimination: Not just for gig workers

http://securitytc.com/T9FG68