this post was submitted on 24 Jun 2024
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[–] [email protected] 62 points 3 days ago (2 children)

One of my favorite examples is when a company from India (I think?) trained their model to regulate subway gates. The system was supposed to analyze footage and open more gates when there were more people, and vice versa. It worked well until one holiday when there were no people, but all gates were open. They eventually discovered that the system was looking at the clock visible on the video, rather than the number of people.

[–] Raxiel 15 points 2 days ago

Reminds me of the time a military algorithm was accidentally trained to conclude that tanks are only concealed in tree lines on overcast days.

[–] [email protected] 17 points 3 days ago

Just an expensive timer.

[–] [email protected] 236 points 3 days ago (17 children)

Reminds me of an early application of AI where scientists were training an AI to tell the difference between a wolf and a dog. It got really good at it in the training data, but it wasn't working correctly in actual application. So they got the AI to give them a heatmap of which pixels it was using more than any other to determine if a canine is a dog or a wolf and they discovered that the AI wasn't even looking at the animal, it was looking at the surrounding environment. If there was snow on the ground, it said "wolf", otherwise it said "dog".

[–] [email protected] 136 points 3 days ago* (last edited 3 days ago) (8 children)

Early chess engine that used AI, were trained by games of GMs, and the engine would go out of its way to sacrifice the queen, because when GMs do it, it's comes with a victory.

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[–] kelargo 11 points 3 days ago

Hot dog. Not hot dog

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[–] [email protected] 33 points 3 days ago (26 children)

I really hate that we are calling this wave of technology "AI", because it isn't. It is "Machine Learning" sure, but it is just brute force pattern recognition v2.0.

The desired outcomes you define and then the data you train it on both have a LOT of built-in biases.

It's a cool technology I guess, but it's being misused across the board. It is being overused and misused by every company with FOMO. Hoping to get some profit edge on the competition. How about we have AI replace the bullshit CEO and VP positions instead of trying to replace fast food drive through workers and Internet content.

I guess that's nothing new for humans... One human invents the spear for fishing and the rest use them to hit each other over the head.

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[–] TAG 73 points 3 days ago (1 children)

That reminds me of the time, quite a few years ago, Amazon tried to automate resume screening. They trained a machine learning model with anonymized resumes and whether the candidate was hired. Then they looked at what the AI was looking at. The model had trained itself on how to reject women.

[–] [email protected] 7 points 2 days ago

Another similar "shortcut" I've heard about was that a system that analyzed job performance determined that the two key factors were being named "Jared" and playing lacrosse in high school.

And, these are the easy-to-figure-out ones we know about.

If the bias is more complicated, it might never be spotted.

[–] [email protected] 149 points 3 days ago (3 children)

The idea of AI automated job interviews sickens me. How little of a fuck do you have to give about applicants that you can't even be bothered to have even a single person interview them??

[–] [email protected] 85 points 3 days ago (3 children)

But god forbid the applicant didn't spend hours researching every little detail about a company, writing a perfect letter with information that could have just been bullet points and being able to explain exactly why they absolutely love the company and why it's been their dream to work there since they were a child. Or even worse: Use AI to write the application.

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[–] cley_faye 79 points 3 days ago (6 children)

There's a ton of great small scale things we can do with machine learning, and even LLM.

Unfortunately, it seems the main usages will be crushing people down even more.

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[–] [email protected] 56 points 3 days ago (7 children)

I fucking hate that extraversion is a measured trait 🙄

[–] [email protected] 29 points 3 days ago

I hate that they think bookshelves are an indicator for it

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[–] The_Picard_Maneuver 92 points 3 days ago (1 children)

"Bias automation" is kind of an accurate description for how our brains learn things too.

[–] [email protected] 82 points 3 days ago (9 children)

The base assumption is that you can tell anything reliable at all about a person from their body language, speech patterns, or appearance. So many people think they have an intuition for such things but pretty much every study of such things comes to the same conclusion: You can't.

The reason why it doesn't work is because the world is full of a diverse set of cultures, genetics, and subtle medical conditions. You may be able to attain something like 60% accuracy for certain personality traits from an interview if the person being interviewed was born and raised in the same type of environment/culture (and is the same sex) as you. Anything else is pretty much a guarantee that you're going to get it wrong.

That's why you should only ask interviewees empirical questions that can identify whether or not they have the requisite knowledge to do the job. For example, if you're hiring an electrical engineer ask them how they would lay out a circuit board. Or if hiring a sales person ask them questions about how they would try to sell your specific product. Or if you're hiring a union-busting expert person ask them how they sleep at night.

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[–] [email protected] 51 points 3 days ago (1 children)

One web LLM I was screwing around with had Job Interview as a preset. Ok. Played it totally straight the first time and had a totally positive outcome. Thought the interviewer way too agreeable. The next time I said the most inappropriate stuff I could imagine and still the interviewer agreed to come home with me to check out the rock collection I keep under my bed and listen to Captain Beefheart albums.

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[–] [email protected] 83 points 3 days ago (1 children)

That shit works IRL too. Why do you think therapy practices often have themselves positioned in front of a wall of books? Not that it's a bad thing; it's good for outcomes to believe your therapist is competent and well educated.

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[–] Xanis 63 points 3 days ago* (last edited 3 days ago) (7 children)

I do that shit when I have a web interview. Put up a guitar just visible in the camera, a small bookshelf, a floor lamp, make sure my tennis bag is visible despite not playing in ages...

Whether they realize it or not, people do take this stuff in. Not sure why some algorithm based on these very same interviews wouldn't do the same.

[–] [email protected] 44 points 3 days ago (3 children)

I did the same, but they were not impressed by my Obedience extreme sex bench 5000 with restraint straps. I even told them the sturdy bench is made of durable, heavy-duty steel, capable of supporting up to 400 pounds of weight.

smh.

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[–] [email protected] 68 points 3 days ago (8 children)

Someone should build a little AI app that scrapes a job listing, then takes a resume and rewrites it in subtle ways to perfectly match the job description.

Let your AI duke it out with their AI.

[–] magnolia_mayhem 52 points 3 days ago (2 children)

When I got out of the military, my outprocessing included a briefing about how to get interviews with federal organizations. One thing they taught us was that you can copy the job description, paste it into your resume, and set the font to white. The automated systems at USA Jobs would register a match to the job description and rate you as a better candidate and the human screeners were so overworked that they would just go with what the computer says without checking.

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[–] [email protected] 28 points 3 days ago

This has job descrimination lawsuit written all over it.

[–] magnolia_mayhem 59 points 3 days ago (2 children)

To be fair, this works with humans, too.

[–] [email protected] 47 points 3 days ago (1 children)

Hence the comment about "bias automation"

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[–] [email protected] 58 points 3 days ago* (last edited 3 days ago)

Recruiters: "people are using AI to apply! Shame on those lazy wage slaves!"

Also recruiters:

[–] [email protected] 31 points 3 days ago (1 children)

Answering the question in the image: machine learning arose from the industrial control world. The idea was to teach a machine how to detect defects in supposedly identical objects out of a manufacturing line, most often with “machine vision” (ie. a camera). Applying it to humans was asinine.

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