Automation

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".
- 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.
  
  Reg, why'd you just stab yourself in the shoulder?
  Ah cmon, ain't ya ever seen a movie?
  Well of course I've seen a movie, but what the hell are ya doing?
  Every time the guy stabs himself in a movie, it's right before he kicks the piss outta the guy he's fightin'!
  Well that don't.. when that happens, the guys gotta plan Reg, what the hell's your plan?
  I dunno, but I'm gonna find out!
  
  Why would you use AI for chess?
  
  It's not wrong
- That's funny because if I was trying to tell the difference between a wolf and a dog I would look for 'is it in the woods?' and 'how big is it relative to what's around it?'.
  
  What about telling the difference between a wolf and grandmother?
- Hot dog. Not hot dog
- While I believe that, it's an issue with the training data, and not the hardest to resolve
  
  Maybe not the hardest, but still challenging. Unknown biases in training data are a challenge in any experimental design. Opaque ML frequently makes them more challenging to discover.
  
  So is the example with the dogs/wolves and the example in the OP.
  As to how hard to resolve, the dog/wolves one might be quite difficult, but for the example in the OP, it wouldn't be hard to feed in all images (during training) with randomly chosen backgrounds to remove the model's ability to draw any conclusions based on background.
  However this would probably unearth the next issue. The one where the human graders, who were probably used to create the original training dataset, have their own biases based on race, gender, appearance, etc. This doesn't even necessarily mean that they were racist/sexist/etc, just that they struggle to detect certain emotions in certain groups of people. The model would then replicate those issues.
  
  Yes, "Bias Automation" is always an issue with the training data, and it's always harder to resolve than anyone thinks.
  
  Old data adage. Garbage in, garbage out.

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??
- 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.
  
  Cover letters fucking make me hateful. I love generating AI cover letters and sending them. Fuck your cover letters in a market where you need to send 100 applications to get 10 bites
  
  We should build an AI that automates researching about a company for applicants
  
  Exactly!
  Applicants are expected to dedicated hours of their time to writing their application and performing background research - both of which are becoming increasingly more tedious over time - so the least a company could bloody do is show some basic respect by paying an actual human being to come interview you!
- That's more like an excuse to keep those stupid 5, 6, and even more interview round processes. Basically making you work an entire week for free in exchange of a chance of getting an offer. Make the first or second rounds with AI and only bother after that.
- I dunno, but if your boss chain contains a machine (literally Amazon warehouse), does it matter?

"Bias automation" is kind of an accurate description for how our brains learn things too.
- 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.
  
  But all the other questions are to find out if they are a good fit for the office culture.
  You know, if they are also white middle class dude bros.
  
  I've just started doing practical interviews. I basically get really young people with little overall experience and I just want to know if they can do common technical tasks.
  So one question is to literally have them explain how to tighten a bolt. One person failed.
  
  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.
  Hol up. ThAt sOuNds LiKe RaCisM!

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.
- Maybe true but your comment is humanizing "dumb" AI.

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.
- Neofeudalism
  
  Technobarbarism
- Yup. AI should be used to automate all of the mundane day-to-day BS, leaving us free to practice art, or poetry, or literature, or study, or just do leisure activities. Because all of the mundane BS is automated, so we don’t need to worry about things like income or where our next meal comes from. But instead, we went down the dystopian capitalist timeline, where we’re automating all of the art so artists are forced to get mundane day-to-day BS jobs.
- Bit it does if you Photoshop a bookshelf in your background?

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.
- 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.

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.
- 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.
  
  I wonder if this still works lol that's brilliant.
- Pretty sure I saw that somewhere actually.
  Edit: Top 5 List - https://www.tomsguide.com/features/i-tested-5-ai-resume-builders-to-help-get-a-job-heres-how-they-fared
  
  I’m looking for a job now, and this is very useful to me. Thank you.
- Do you really want to work for a company that allows their HR department to abuse AI as a tool?
  
  Yes? They've got a million bazillion applicants too; this is a huge market failure all around.
  
  Explain how anyone has a choice, especially in the United States
- That exists

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

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.
- 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.
  
  I'd have hired you. At least I know you'd be honest and not try to hide shit for fear of embarrassment.
- Journalist doing reports in front of their dildo collection: "hold my beer"
- Tennis bag? Oh, right. America.
  
  America? Maybe Britain?

To be fair, this works with humans, too.
- Hence the comment about "bias automation"
  
  AI reflects its training data??? Shocking!
- Yes, contradicting the claim that it's "more objective".

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

I fucking hate that extraversion is a measured trait 🙄
- I hate that they think bookshelves are an indicator for it
- It's from the OCEAN model of personality, which is currently the most widely accepted model. It's received less criticism than myers-briggs and astrology.
  
  It's received less criticism than myers-briggs and astrology.
  That's not a high bar to meat.

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.
- Listening to some Captain Beefheart, huh.... I'll grab my shiny rocks!

During the AI goldrush you can make your fortune selling bookshelves.
- Selling bookshelf large poster, or just jpgs
  
  Bookshelf NFTs? Only possible to buy with crypto?
  
  Having a bookshelf poster behind you is actually a hilarious workaround.

Why are the different scales connected? How exactly does one interpolate between agreeableness and neuroticism? This is the kind of diagram I used to draw as an 8 year old, and they put this crap in a real product...
- They shouldn't be plotted that way technically. The big 5 are independent traits so they should essentially be sliders, not linked like that.
  That said, it's way easier to see the points when you do that. Easy to miss when colors swap, for example, without the lines when you've been looking at this stuff for a few hours.
  
  Yeah, it's interesting that the math pretty much says, that these factors are independent from each other. Then we did even fancier math with "AI", all to ruin the base understanding by connecting them graphically. It bugs me more than it should. Think about your graphics. It is a very interesting result nevertheless.
- https://en.wikipedia.org/wiki/Big_Five_personality_traits
- It's incompetent plot by a company not even interested in what they are selling

"Machine learning" is perfectly cromulent. The bias is what it learned, because that's what it was taught. (Not intentionally, I don't think. It's just hard to get this stuff right sometimes.)
- Job interviews are all bias regardless of whether they're automated 😅
  
  I'm really good at my job.
  But that's not why I got my job, it's just a coincidence.
  I got my job because I'm pretty good at interviews.
- Garbage in garbage out
  
  Garbage all around
- It is bias laundering though. They hide behind an "objective" algorithm, which was trained on a huge dataset of past ~~biased~~ hiring decisions.

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.
- I agree with most of your points, but i don't entirely like the "this is not intelligence" line of thought. We don't even know yet how to define intelligence, and pattern recognition sounds a LOT like what our brains do. The hype is of course ridiculous, and the ways it's being used is just stupid, but i do think pattern recognition could be a solid basis for whatever we end up considering intelligence.
  
  Maybe it is human-like intelligence. It's dumb as shit, but have you met people?
  LMAO
  But yeah, I guess at its core, human intelligence and machine intelligence are both just pattern recognition, but I guess my point is that calling it "AI" gives people this false sense that it is something it is not. AI has been a thing in Sci-fi for so long that we all think of Data from Star Trek or C-3PO from Star Wars and similar. When in reality it is more akin to a robot arm in a factory doing the same task really fast and really precisely, but it isn't some adaptable all-purpose thing yet.
  
  Pattern recognition is one thing that our brains do, it is a very long way away from the only thing our brains do.
  
  All you are saying is, is that intelligence isnt as smart as we think, that human intelligence is actually pretty dumb. That doesnt change anything about the current situation even if thats true though.
  So we all agree its actually human level intelligence now, what then? Can we stop developing it and do something else now?

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.
- I know right? I have seen seen vision systems do some impressive things, but they are carefully calibrated to work in a specific way under certain conditions. Some of the ones my company works with get fed CAD in real time so the robot knows what to look for.

I'm not working right now because I'm putting my daughter through online school. (Also due to an illness) She graduates in five years.
I am never getting another job, am I?
- Just have a bookshelf behind you during the interview, you'll be golden.
  Or maybe have the oval office as a backdrop, that might really make you qualified.
  
  Just get a bookshelf poster.
- I have a MfA from Parsons and 25 years of experience, and I’m having an incredible amount of difficulty finding a job in my field.
  You’re not alone.

This has job descrimination lawsuit written all over it.

I’m amazed that no-one has complained that the graph’s data points are on the borders between categories rather than inside the category bars.
With that out of the way: WTF is wrong with that graph?
- It's not on the border. The specturm line is under each trait. Though it's absolutely ridiculous that they're connected instead of being bars.
- Gross.

I would be interested to see what happens if you lighten up her skin color a bit...
- Conventionally attractive white people, stealing all your jobs!
- Go full albinism

"oooo books he must be really smart"

Anyone have the original link handy? Trying to get to the tweet is uglier than I expected.

It's from 2021. Link to the website: https://interaktiv.br.de/ki-bewerbung/en/
Still pretty interesting though.

"Extraversion"
- Is an alternative spelling to extroversion and more close to the original Latin root.
  
  I've never seen it spelled that way and spellcheck has a red squiggle under it. I looked it up, and you're correct, both spellings are acceptable. TIL! Same with extrovert vs. extravert. It looks wrong to me with an a, though.

I wonder if it's actually interpreting the bookshelf or if having such a busy background is taking a toll on the compression. That would alter the details on the person's face
- Good and interesting question. I bet you could test it by using static (high entropy) as a background vs the control plain color.

fasterthanlime is so cool btw

I don't understand why anyone writing, reading or commenting on this think a bookshelf would not change the outcome? Like what do you people think these ml models are, human brains? Are we still not below even the first layer of understanding?
- The problem is the hysteria behind it, leading people to confuse good sounding information with good information. At least when people generally produce information they tend to make an effort to get it right. Machine learning is just an uncaring bullshitting machine, that is rewarded on the basis of the ability to fool people (turns out the Turing test was a crappy benchmark for practice-ready AI besides writing poems), and VC money hasn't reached the "find out" phase of that looming lesson, when we all just get collectively exhausted by how underwhelming the AI fad is.
  
  Yeah, the hysteria is definitely the problem. Can't say that I agree that the technology is underwhelming, though. It can generate, practically anything fast and with guidance and it's just interesting that nobody really understands how. It's a paradigm shift for creative work. Producing music or art will continue to change a lot from this. Using the technology to analyse personalities during job interviews is so fundamentally idiotic, because a generative system is a brainstorming tool, not analytical nor accurate. And just so wrong that it feels like it's actually the work of someone malicious.

Well, at least they didn’t spend a lot of money on testing it…