Employers’ Use of AI Tools Can Violate the Americans with Disabilities Act

https://www.justice.gov/opa/pr/justice-department-and-eeoc-warn-against-disability-discrimination

by pseudolus • 4 years ago

257 133 4 years ago

jaqalopes• 4 years ago

Current headline is a bit misleading, the point of the article as made clear in the very first paragraph is that this is about AI hiring tools causing potential discrimination. This has nothing to do with AI workers somehow replacing disabled humans, which is what it sounds like.

iso1631• 4 years ago

The first paragraph is exactly what I expected from the headline, ever since the amazon AI gender discrimination story a few years back.

https://www.theguardian.com/technology/2018/oct/10/amazon-hi...

sneak• 4 years ago

http://www.tnellen.com/cybereng/harrison.html

alicesreflexion• 4 years ago

This doesn't matter until someone tries suing them for it, right?

And as I understand it, you don't really have a case without evidence that the hiring algorithm is discriminating against people with disabilities.

How would an individual even begin to gather that evidence?

marian_ivanco• 4 years ago

I am not sure, but if I remember correctly employer must prove they are not discriminating. And just because they are using AI they are not immune to litigation.

danarmak• 4 years ago

How can the employer prove a negative?

At most I imagine the plaintiff is allowed to do discovery, and then has to prove positive discrimination based on that.

rascul• 4 years ago

I am not sure, but if I remember correctly employer must prove they are not discriminating.

That seems backwards, at least in the US.

dsr_• 4 years ago

The process of gathering evidence after the suit has started is called discovery.

There are three major kinds of evidence that would be useful here. Most useful but least likely: email inside the company in which someone says "make sure that this doesn't select too many people with disabilities" or "it's fine that the system isn't selecting people with disabilities, carry on".

Useful and very likely: prima facie evidence that the software doesn't make necessary reasonable accomodations - a video captcha without an audio alternative, things like that.

Fairly useful and of moderate likelihood: statistical evidence that whatever the company said or did, it has the effect of unfairly rejecting applicants with disabilities.

pfdietz• 4 years ago

And one could go a step further: run the software itself and show that it discriminates. One doesn't just have to look at past performance of the software; it can be fed inputs tailored to bring out discriminatory performance. In this way software is more dangerous to the defendant than manual hiring practices; you can't do the same thing to an employee making hiring decisions.

jejones3141• 4 years ago

These days, disparate impact is taken as evidence of discrimination, so it's easy to find "discrimination".

mkr-hn4• 4 years ago

What's the difference? Discrimination is an effect more than an intent. Most people are decent and well-intentioned and don't mean to discriminate, but it still happens. If there's a disparate impact, what do you imagine causes that if not discrimination? Remembering that we all have implicit bias and it doesn't make you a mustache-twirling villain.

mkr-hn4• 4 years ago

This is what that demographic survey at the end of job applications is for. It can reveal changes in hiring trends, especially in the demographics of who doesn't get hired. I don't know how well it works in practice.

hallway_monitor• 4 years ago

I am a person, not a statistic. I always decline to answer these surveys; I encourage others to do the same.

supergeek133• 4 years ago

This sort of reminds me of the story about an HR algorithm that ended up being discriminatory because it was trained using existing/past hiring data.. so it was biased toward white men.

Was it Amazon?

Anyway, this feels different to me, IIRC you can't ask disability related questions in hiring aside from the "self identify" types at the end? So how would a ML model find applicants with any kind of disability unless it was freely volunteered in a resume/CV?

Or is that the advisory? "Don't do this?"

padolsey3• 4 years ago

how would a ML model find applicants with any kind of disability unless it was freely volunteered in a resume/CV?

A few off the top of my head:

(1) Signals gained from ways that a CV is formatted or written (e.g. indicating dyslexia or other neurological variances, especially those comorbid with other physiological disabilities)

(2) If a CV reports short tenure at companies with long breaks in between (e.g. chronic illnesses or flare-ups leading to burnout or medical leave)

(3) There are probably many unintuitive correlates irt interests, roles acquired, skillsets. Consider what experiences, institutions, skillsets and roles are more or less accessible to disabled folk than others.

(4) Most importantly: Disability is associated with lower education and lower economic opportunity, therefore supposed markers of success ("merit") in CVs may only reflect existing societal inequities. *

* This is one of the reasons meritocratic "blind" hiring processes are not as equitable as they might seem; they can reflect + re-entrench the current inequitable distribution of "merit".

MontyCarloHall3• 4 years ago

If a CV reports short tenure at companies with long breaks in between (e.g. chronic illnesses or flare-ups leading to burnout or medical leave)

This is a case where it may benefit a candidate to disclose any disabilities leading to such an erratic employment pattern. I don’t proceed with candidates who cannot explain excessively frequent job hops because it signals that they can’t hold a job due to factors I’d want to avoid hiring, like incompetence or a difficult personality. It’s a totally different matter if the candidate justified their erratic employment due to past medical issues that have since been treated.

b65e8bee43c2ed0• 4 years ago

* This is one of the reasons meritocratic "blind" hiring processes are not as equitable as they might seem; they can reflect + re-entrench the current inequitable distribution of "merit".

they are not meant to be "equitable". they're meant to provide equality of opportunity, not equality of outcome

burkaman2• 4 years ago

https://beta.ada.gov/ai-guidance/

For example, some hiring technologies try to predict who will be a good employee by comparing applicants to current successful employees. Because people with disabilities have historically been excluded from many jobs and may not be a part of the employer’s current staff, this may result in discrimination.
For example, if a county government uses facial and voice analysis technologies to evaluate applicants’ skills and abilities, people with disabilities like autism or speech impairments may be screened out, even if they are qualified for the job.
For example, an applicant to a school district with a vision impairment may get passed over for a staff assistant job because they do poorly on a computer-based test that requires them to see, even though that applicant is able to do the job.
For example, if a city government uses an online interview program that does not work with a blind applicant’s computer screen-reader program, the government must provide a reasonable accommodation for the interview, such as an accessible version of the program, unless it would create an undue hardship for the city government.

light_hue_1• 4 years ago

So how would a ML model find applicants with any kind of disability unless it was freely volunteered in a resume/CV?

In machine learning this happens all the time! Stopping models from learning this from the most surprising sources is an active area of research. Models are far more creative in finding these patterns than we are.

It can learn that people with disabilities tend to also work with accessibility teams. It can learn that you're more likely to have a disability if you went to certain schools (like a school for the blind, even if you and I wouldn't recognize the name). Or if you work at certain companies or colleges who specialize in this. Or if you publish an article and put it on your CV. Or if you link to your github and the software looks there as well for some keywords. Or if among the keywords and skills that you have you list something that is more likely to be related to accessibility. I'm sure these days software also looks at your linkedin, if you are connected with people who are disability advocates you are far more likely to have a disability.

Or is that the advisory? "Don't do this?"

Not so easy. Algorithms learn this information internally and then use it in subtle ways. Like they might decide someone isn't a good fit and that decision may in part be correlated with disability. Disability need not exist anywhere in the system, but the system has still learned to discriminate against disabled people.

charcircuit2• 4 years ago

How would this even happen. Why would people put their disabilities on their resume?

hansvm• 4 years ago

The AI learns proxy signals. Name, work experience, skills (e.g., an emphasis on A11Y) ... all have some predictive power for gender, for some sorts of disabilities, ....

You can fix the problem by going nuclear and omitting any sort of data that could serve as a proxy for the discriminatory signals, but it's possible to explicitly feed the discriminatory signals into the model and enforce that no combination of other data amounting to knowledge about them can influence the model's predictions.

There was a great paper floating around for a bit about how you could actually manage that as a data augmentation step for broad classes of models (constructing a new data set which removed implicit biases assuming certain mild constraints on the model being trained on it). I'm having a bit of trouble finding the original while on mobile, but they described the problem as equivalent to "database reconstruction" in case that helps narrow down your search.

zw123456• 4 years ago

Oh, thank you, this was the question floating in my head as well, this explains it perfectly.

treeman79• 4 years ago

Because you can’t always hide it. Nothing like giving a presentation on a whiteboard when all of a sudden your writing turns to gibberish.

People have a limited tolerance. Then they start telling you to take care of yourself and strongly encouraging you to leave.

It’s why I switched to remote work before the pandemic. If a bad episode starts up I can cover for it much more easily.

charcircuit2• 4 years ago

Sorry, but that has nothing to do with AI resume review.

emiliobumachar3• 4 years ago

e.g. if you knew one or two sign languages, wouldn't you list it under languages? What if the job involves in-person communication with masses of people?

Miner49er• 4 years ago

Many (most?) employers ask if you are disabled when filling out a job application. I personally don't consider myself disabled, but I have one of the conditions that is listed as a disability in this question. I never know what to put. I thought it wouldn't matter if I just said, yes, that I'm disabled, since I literally have one of the conditions listed, but people online who work in hiring say I will most likely be discriminated against if I do that. Sure, it's illegal, but companies do that anyway, apparently.

I wonder if the answer to the disability question is something the AI uses when evaluating candidates, and if it has learned to just toss out anyone who says yes?

michaelt• 4 years ago

Skills: Fluent in American Sign Language.

High School: Florida School for the Deaf and the Blind.

Other Experience: President of Yale Disability Awareness Club (2009-2011).

annoyingnoob• 4 years ago

I'll bet the same AI used in hiring decisions could also be biased against older workers.

adolph• 4 years ago

I wonder if this government guidance focuses on imperfections in products that on the whole may be a significant improvement over biases in traditional human screening.

tj_h• 4 years ago

"Using AI tools for hiring"...this is when i like to remind myself that google, basically at some point in the last 12-24 months was like "OH CRAP, we forgot to tell our robots about black people!". Like, I'm not saying google is at the forefront of ML - maybe it is, but it sure as hell is out in front somewhere and more to the point most companies are likely not gonna be using cutting edge technology for this stuff. EVEN GOOGLE, admitted their ML for images is poorly optimized for POC's, i hate to think what some random ML algorithm used by company X thinks about differently abled peoples

temp8964• 4 years ago

This is unreasonable generalization. Dark skin does have direct impact on image processing. Nothing like this exists in hiring.

lmkg• 4 years ago

There are companies selling products which screen hiring candidates based on video of them talking. Ostensibly for determining personality traits or whatever. So yes, this literally exists in hiring.

htrp• 4 years ago

Mate. you ever hear about amazon's hiring ai?

smiley1437• 4 years ago

While image processing dark skin may not be germane to AIs doing hiring, the idea that unintentional discrimination from ML models could occur in the context of hiring is certainly worth considering and I believe it's the entire point of the technical assistance document released today.

httpsterio• 4 years ago

Racial bias does exist in ML based image recognition tools, there's a plethora of evidence to show that.

https://www.theverge.com/2019/1/25/18197137/amazon-rekogniti...

https://www.google.com/amp/s/www.wired.com/story/best-algori...

https://algorithmwatch.org/en/google-vision-racism/

https://time.com/5520558/artificial-intelligence-racial-gend...

jijji• 4 years ago

I encountered this recently on Facebook Marketplace. I post ads for houses for rent, and the ads say "no pets". This has been fine for 20+ years on craigslist, but on facebook marketplace the minute some guy writes that he "has a service animal" and you don't respond the right way, your ad gets blocked/banned.... You basically have to accept these people even though the law allows you to prohibit animals, service animals must be accepted otherwise you violate the ADA. I knew this guy when I was living in Sunnyvale he had a cat that was a registered service animal, and he would get kicked out of every hotel he went to, because they dont allow animals/pets, and then he would sue the owner under ADA laws and collect ~40k from each hotel owner. Its a real racket.

judge2020• 4 years ago

I knew this guy when I was living in Sunnyvale he had a cat that was a registered service animal,
Beginning on March 15, 2011, only dogs are recognized as service animals under titles II and III of the ADA.

https://www.ada.gov/service_animals_2010.htm

golemotron3• 4 years ago

Isn't the entire point of an AI tool 'discrimination'?

theptip9• 4 years ago

Like many words in the English language, “discrimination” has multiple meanings.

From Webster:

1. The act of discriminating.

2. The ability or power to see or make fine distinctions; discernment.

3. Treatment or consideration based on class or category, such as race or gender, rather than individual merit; partiality or prejudice.

You are talking about 2. The article is talking about 3.

3. is illegal in hiring. 2. is not.

golemotron3• 4 years ago

If you make a decision based on 2, you are doing 3.

It's just that simple. 2 creates categories implicitly.

pipingdog• 4 years ago

ML is a technique for discovering and amplifying bias.

Applying ML to hiring shows a profound lack of awareness of both ML and HR. Especially using previous hiring decisions as a training set. Like using a chainsaw to fasten trees to the ground.

theptip9• 4 years ago

One point that I think is under-discussed in the AI bias area:

While it is true that using an algorithmic process to select candidates may introduce discrimination against protected groups, it seems to me that it should be much easier to detect and prove than with previous processes with human judgement in the loop.

You can just subpoena the algorithm and then feed test data to it, and make observations. Even feed synthetic data like swapping in “stereotypically black” names for real resumes of other races, or in this case adding “uses a wheelchair” to a resume. (Of course in practice it’s more complex but hopefully this makes the point.)

With a human, you can’t really do an A/B test to determine if they would have prioritized a candidate if they hadn’t included some signal; it’s really easy to rationalize away discrimination at the margins.

So while most AI/ML developers are not currently strapping their models to a discrimination-tester, I think the end-state could be much better when they do.

(I think a concrete solution would be to regulate these models to require a certification with some standardized test framework to show that developers have actually attempted to control these potential sources of bias. Google has done some good work in this area: https://ai.google/responsibilities/responsible-ai-practices/... - though there is nothing stopping model-sellers from self-regulating and publishing this testing first, to try to get ahead of formal regulation.)

TimPC9• 4 years ago

I don’t think it’s adequate to attempt to prevent discrimination. Discrimination is core to our fundamental human rights. It’s necessary to succeed at preventing discrimination.

“We applied best practices in the field to limit discrimination” should not be an adequate legal defence if the model can be shown to discriminate.

To clarify further, just because you tried to prevent discrimination doesn’t mean you should be off the hook for the material harms of discrimination to a specific individual. Otherwise people don’t have a right to be protected against discrimination they only have a right to people ‘trying’ to prevent discrimination. We shouldn’t want to weaken rights that much even if it means we have to be cautious in how we adopt new technologies.

MontyCarloHall3• 4 years ago

I agree that discrimination would be a lot easier to objectively prove after the fact, but it also would be far easier to occur in the first place, since many hiring managers would blindly "trust the AI" without a second thought.

fshbbdssbbgdd• 4 years ago

From my experience working on projects where we trained models, usually it’s obviously completely broken the first attempt and requires a lot of iteration to get to a decent state. “Trust the AI” is not a phrase anyone involved would utter. It’s more like: trust that it is wrong for any edge case we didn’t discover yet. Can we constrain the possibility space any more?

theptip9• 4 years ago

Definitely could be so, particularly in these early days where frameworks and best-practices are very immature. Inasmuch as you think this is likely, I suspect you should favor regulation of algorithmic processes instead of voluntary industry best-practices.

indymike• 4 years ago

The problem with AI is that when it does make discriminatory decisions on hiring, is that it does so systematically and mechanically. Incidentally, systematic and discrimination are two words you never want to see consecutively on a letter from the EEOC or OFCCP.

TimPC9• 4 years ago

The reason you never want to see those words together is that isolated discrimination may result in a single lawsuit but systemic discrimination is a basis for class action.

slg3• 4 years ago

With a human, you can’t really do an A/B test to determine if they would have prioritized a candidate if they hadn’t included some signal; it’s really easy to rationalize away discrimination at the margins.

Which is part of the reason that discrimination doesn't have to be intentional for it to be punishable. This is a concept known as "disparate impact". The Supreme Court has issued decisions[1] that a policy which negatively impacts a protected class and has no justifiable business related reason for existing can be deemed discrimination regardless of the motivations behind that policy.

[1] https://en.wikipedia.org/wiki/Griggs_v._Duke_Power_Co.

Ferrotin3• 4 years ago

Everything has a disparate impact, so now everything is illegal.

TimPC9• 4 years ago

Justifiable business reason is still a strong bar. For example, with no evidence in either direction for a claim there is no justifiable business reason even if the claim is somewhat intuitive. So if you want to require high-school diplomas because you think people who have them will do the job better you better track that data for years and be prepared to demonstrate it if sued. If you want to use IQ tests because you anticipate smarter people will do the job better you better have IQ tests done on your previous employee population demonstrating the correlation before imposing the requirement.

darawk2• 4 years ago

He didn't say anything about intention, though. He just talked about the counterfactual. Disparate impact is about the counterfactual scenario.

mjburgess• 4 years ago

It's under-discussed as with any discussion of an empirical study of ML systems, ie., treating them as targets of analysis.

As soon as you do this, they're revealed to exploit only statistical coincidences and highly fragile heuristics embedded within the data provided. And likewise, pretty universally discriminatory when human data is inovlved

Manuel_D• 4 years ago

With a human, you can’t really do an A/B test to determine if they would have prioritized a candidate if they hadn’t included some signal; it’s really easy to rationalize away discrimination at the margins.

Not for individual candidates, no. But you can introduce a parallel anonymized interview process and compare the results.

TimPC9• 4 years ago

Actually you kind of can't. You don't have a legal basis for forcing the company to run that experiment.

TimPC9• 4 years ago

There is a very real danger of models being biased in a way that doesn't show up when you apply these crude hacks to inputs. It seems to me we have to be much more deliberate, much more analytical, and much more thorough in testing models if we want to substantially reduce or even eliminate discrimination.

Yes, you can A/B test the model if you can design reasonable experiments. You still don't have the general discrimination test because you have to define what a reasonable input distribution and what reasonable outputs are.

If an employer is looking to hire an engineer with a CS degree from a top-tier university, and they use an AI model to evaluate resumes and it returns a number of successes on black people very similar to the population distribution of graduates from those programs is the model discriminatory?

There are still hard problems here because any natural baseline you use for a model may in fact be wrong and designing a reasonable distribution of input data is almost impossibly hard as well.

theptip9• 4 years ago

Yes, in practice it’s actually way more complex than I gestured at. The Google bias toolkit I linked does discuss in much more detail, but I am not a data scientist and haven’t used it; I’d be interested in expert opinions. (They also have some very good non-technical articles discussing the general problems of defining “fairness” in the first place.)

TimPC9• 4 years ago

I think the general problem is the law says certain correlations are fair to use and others are not. If you can prove the AI model has no way to separate out which is which you have a fairly sizeable amount of evidence the AI is discriminating. Likely enough evidence for a civil case.

Usually showing that input data is biased in some way or contains a potentially bad field will result in winning a discrimination case.

If neither side can conclusively prove what the model is doing but the plaintiff shows it was trained on data that allows for discrimination and the model is designed to learn patterns in its training data then the defendant is on the hook for showing the model is unbiased. For the most part people design input data uncritically and some of the fields allow for discrimination.

thaumasiotes2• 4 years ago

but the plaintiff shows it was trained on data that allows for discrimination

That's all data; there would be no need to show anything.

There was a paper a while ago by a team of doctors who wanted to use classifiers on X-ray images and FREAKED OUT when they realized that the first thing the classifier did was categorize every image by the race of the patient. As they note, it will always do this regardless of whether the race of the patient is present in the input data. (Because obviously, the race of the patient is part of the information conveyed by the structure of their body, which is what an X-ray shows.)

theptip9• 4 years ago

The linked article gives some examples that I think are very useful clarifications:

https://www.eeoc.gov/tips-workers-americans-disabilities-act...

The format of the employment test can screen out people with disabilities [for example:] A job application requires a timed math test using a keyboard. Angela has severe arthritis and cannot type quickly.
The scoring of the test can screen out people with disabilities [for example:] An employer uses a computer program to test “problem-solving ability” based on speech patterns for a promotion. Sasha meets the requirements for the promotion. Sasha stutters so their speech patterns do not match what the computer program expects.

Interestingly, I think the second one is problematic for common software interview practices. If your candidate asked for an accommodation (say, no live rapid-fire coding) due to a recognized medical condition, you would be legally required to provide it.

This request hasn’t come up for me in all the (startup) hiring I’ve done, but it could be tough to honor this request fairly on short notice, so worth thinking about in advance.

alar44• 4 years ago

What if the job requires you to type quickly? Why would someone with arthritis even want a job where you have to type quickly? Is that really discrimination or is that the candidate simply not being able to perform the job?

TimPC9• 4 years ago

If the job actually requires typing quickly like a Court Recorder then there is a basis to require typing quickly. If the job doesn’t actually require it, like for example a programmer then enforcing the requirement anyway is discrimination.

wbl• 4 years ago

Dragon Naturally Speaking is the definition of a reasonable accommodation. Maybe not a court transcriptionist but almost all jobs with typing would be fine with it.

robonerd• 4 years ago

What you are describing is called a Bona Fide Occupational Qualification (BFOQ). The specifics of what sort of attributes might be covered for what jobs is something courts hash out, but broadly: if you're hiring workers for a warehouse it's fine to require workers be able to lift boxes. If you're hiring airline pilots, it's fine to turn away blind people. Etc.

avgcorrection• 4 years ago

Think about what you just wrote. This is a programming job, not something like a transcriptionist gig. Why do you feel that your “what if” is appropriate?

Besides, the point seems to have been about interview practices. You know, those practices which are often quite removed from the actual on-the-job tasks.

What if I was disabled to the degree that I couldn’t leave the house, but I could work remotely (an office job)? That’s what accomodations are for.

scollet2• 4 years ago

When job requirements actually match the job, then you can worry about this.

choppaface• 4 years ago

I once interviewed with a cast and two different YC start-ups gave me speed coding problems. One even made me type with their laptop versus a split keyboard I had where I could actually reach all the keys. They used completion time as a metric even though I asked for an accommodation and it was obvious as I typed in front of them that the cast was major drag on me.

Pretend your colleague had a cast and couldn’t type for a few weeks. Is that person going to get put on the time-sensitive demo where 10k SLOC need to be written this week? Or the design / PoC project that much less SLOC but nobody knows if it will work? Or the process improvement projects that require a bunch of data mining, analysis, and presentation?

It’s not hard to find ways to not discriminate against disabilities on short notice. The problem is, at least in my experience with these YC start-ups who did not, there’s so much naïveté combined with self-righteousness that they’d rather just bulldoze through candidates like every other problem they have.

theptip9• 4 years ago

Amusingly, this might actually be an ADA infraction. See https://www.smithlaw.com/newsletter?item_id=75 - temporary injuries can be a disability. (IANAL)

etchalon4• 4 years ago

If someone presented me with a speed-timed programming exercise, I'd walk out the door.

theptip9• 4 years ago

Any in-person coding exercise with a time-box (say, the standard one-hour slot) is “timed” in some sense. I don’t think we always consider it as such, but if you can’t type fast due to arthritis it could definitely be problematic.

mechanical_bear• 4 years ago

I walk for any code monkey hoop jump exercises. Timed or not.

When you apply to be a carpenter they don’t make you hammer nails, when you apply to be a accountant they don’t have you prepare a spreadsheet for them, etc.

I don’t work (even in interviews) for free.

bombcar• 4 years ago

Even the very requirement to "apply online" has been quite effective at making it very difficult for a sub-section of the working population to succeed at applying.

There are many (and I know quite a few) people who are quite capable at their jobs and entirely computer-ineffective. As they're forced more and more to deal with confusing two-factor requirements and other computer-related things that we're just "used" to, they get discouraged and give up.

For now you can often help them fill it out, but at some point that's going to be unwieldy or insufficient.

david-cako• 4 years ago

for instance, I find mass surveillance intolerable and it makes me completely uninterested in my work.

frankfrankfrank• 4 years ago

It is a bit of an aside, but not only do I find it interesting that 1) this issue is approaching an interesting nexus of computer based efficiency and human "adjustments" (I will just call them) like the ADA that are intentionally and even deliberately inefficient; and 2) that the efficiency and centralization based sector of computer "sciences"/development is so replete with extremely contrary types that demand all manner of exceptions, exemptions, and make special pleadings.

I find it all very interestingly paradoxical, regardless of everything else.

umvi• 4 years ago

Is it actually possible to hire someone without some level of discrimination involved? Seems like this ideal world where candidates are hired purely on technical ability or merits without regard to any other aspects of their life is impossible.

For example, if I were hiring a programmer, and the programmer was technically competent but spoke with such a thick accent that I couldn't understand them very well, I'd be tempted to pass on that candidate even though they meet all the job requirements. And if it happened every time I interviewed someone from that particular region, I'd probably develop a bias against similar future candidates.

throwaway09223• 4 years ago

No, it's not possible. Humans have all kinds of inherent biases.

The big difference is we can prove the bias in an AI. It's a very interesting curveball when it comes to demonstrating liability in the choice making process.

Broken_Hippo• 4 years ago

Probably not simply because we are human, but we can minimize some of it.

You wouldn't screen out a person who cannot speak or who cannot speak clearly due to a disability of some sort. You'd use a different method of communication as would everyone else and it could really be the same for them.

On the other hand, if communication was clearly impossible and/or they needed to be understood by the public (customers), the accent may very well mean they cannot do the job and not in the scope of things to teach someone like you can teach expectations about customer service.

egberts1• 4 years ago

It is a strange twist but when filling out the many prescreening questions at Google, I was immediately sent an email asking for an interview.

Sadly, they insist that they would only call me at an agreed time and not take any incoming call from me, even at their agreed upon timeframe.

Why is this an important stance of AI bias against people with disability? I need to line up a voice interpreter who would do American Sign Language so I can understand what a group of Google interviewers would be saying. And voice interpreters requires a 3-way call that I can help setup.

I am capable of understanding them perfectly through my lipreading given that I lost all high frequency discriminator due to a childhood high fever. I cannot tell the difference between B, V, P, D, Z, or E, but a lipreading skill can nails them all. I am an excellent speaker of the English language given being technically and governmentally assigned as Deaf.

So, have I been wronged? I still think so … to this day.

ordiel• 4 years ago

IMHO people are not cogs, you cannot masure them all with only a few parameters, we are so kuch more complex than that, and there should be a absolute ban in the use of AI and software tools to measure (and spy) employees, only allowing those softare tools that facilitate capturing and keeping record of those observations perfomed by other humans.

I am not saying we humans are perfect to handle that complexity, hence when humans are the ones behind such desition making it is rarely done by a single person

lucidmote• 4 years ago

I've been disabled since 17, finally got approved for SSDI in 2017 after almost two decades of struggling to work and make ends meet. I can say definitively that employment in the US does not follow the guidelines as they exist and those guidelines are too weighted in the favor of the employer in the first place.

A simple example of this is that often part-time hours would allow me to continue working and there is nothing in the ADA/EEO or FMLA that guarantees a worker's right to keep their job at part-time indefinitely. The obligation to perform to the level of a typical worker is squarely on the shoulders of the disabled. Good luck finding an employer generous enough to deal with all of your needs.

85% of the people with my diagnosis are unemployed despite the fact most of us want to work. The algorithms will probably help make sure it's more like 90-95% of us. But at least the stakeholder involvement process makes people feel like they have a voice even as they are categorically excluded from ever being fully-functional human beings.

Employers’ Use of AI Tools Can Violate the Americans with Disabilities Act

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