I will vote for any candidate who promises to go scorched fucking earth on every tech company. Break every single one of them up into companies based around a single product and then split those in thirds. Weaponize existing antitrust laws to the hilt and pass the most draconian versions of them ever seen on this planet. Nationalize google search specifically. Pass consumer privacy protections strict enough to kill the data harvesting industry for good. Make all of these fuckers go bankrupt for this rent-seeking shit
HOLY SHIT GUYS, I WAS INSPIRED BY THIS POST TO TRY MAKE THE SONG AND YOU WOULD NOT BELIEVE THE SCREAM I SCRUMPT WHEN I DRAGGED THE TRAINING AUDIO OVER THE BACKING TRACK AND IT LINED UP PERFECTLY
and look up ur rights on what they can and cannot ask u many places ban asking about ur record and transportation status and things like that resources will also tell u how they reword sketchy questions so ur prepared
Hey. Take it from a former HR person… this goes double right now.
I just spent some time putting in some job applications myself (not for HR, lol) and got about 15 interviews. And idk if it’s because of COVID uncertainty or if places just don’t fucking care anymore because they know people are desperate for work, but the amount of straight up illegal shit my interviewers asked me was appalling.
(That’s not even counting the questions that were technically legal but clearly fishing for information they’re not legally allowed to ask.)
A tame example? Two questions into a phone interview, the guy on the other end of the line asked: “How old are you?”
I said “Excuse me?” - giving him a chance to rethink that.
He didn’t. “How old are you?”
“Sir, you are not allowed to ask me that question.”
“Well, I want to know. I’m asking.”
“And you’re legally not allowed to ask me that. I’m not required to tell you my age.”
At that point, I guess he managed to remember an old HR bulletin or something (I hope to god he wasn’t actually HR himself), and he said, “Well, I need to know if you’re over the age of 18.” (Which is what he should have asked in the first place… or not, since that was in the application that he could have read.)
“Yes. I’m over the age of 18.”
And we moved on. Two questions later, he tried another illegal question. I called him on it again and ended the interview, citing that a workplace with such a clear disregard for the law, especially upon first contact with a potential employee, was not going to be a good fit. (They offered me the job anyway, lol. I didn’t send a thank-you or a response.)
At a different interview, the majority of questions were “fishing” questions - just looking for that info they’re not actually allowed to ask. (This person was also either not really HR or an HR person who was exceptionally bad at their job.)
I could tell they were getting frustrated when I dodged answering the personal stuff, and they actually got extremely upset when I mentioned later in the interview (re: less relevant work experience) I had worked in HR. They were super flustered for the remainder of our time, and I watched them skip over questions on their sheet they had clearly planned on asking. They KNEW they were being sketchy and were counting on me not knowing anything about HR - or my rights - and so they got upset when I did.
These were super tame examples. I’m begging you, if you’re job searching right now, PLEASE know your rights. Please know what interviewers are allowed to ask.
Please don’t volunteer information or elaborate more than you’re required to about personal things. Save your words (and everyone’s time) by elaborating why you’re good for the position/what you can do.
I may create a resource list on this shit later but PLEASE PLEASE KNOW THIS STUFF BEFORE YOU TALK TO AN EMPLOYER. This goes for anywhere you’re interviewing as well as your current employer. This also goes for HR. HR may be the person you go to when shitty stuff happens, but that doesn’t mean they’re your friend (or competent).
They don’t need to know your age (beyond 16+, 18+, or 21+, depending on the job). They don’t need to know your medical history. (For the love of god, do NOT answer the “have you been diagnosed with depression?” question.) They don’t need to know if you have kids or whatever. They don’t need to know a LOT of those things that may appear on an application, including your veteran status, whether you’re on/have been on unemployment, etc. They’re not entitled to know specifics about your transportation (unless you’re using that transportation for the job, like Uber/delivery drivers). Look this up for your state/the job’s state.
Beware questions like “What year did you graduate?” if you’re like me and don’t put dates on your resume (I just put amount of time spent at employers, not dates of employment). They’re fishing for your age. It’s “Oh, you know, 100 years ago,” if you feel comfortable making a joke, or “About [generic number, like 5 or 10] years ago” if not.
Also beware things like the “What do you do in your free time?” question, even if you already work there. This is not a friendly getting-to-know-you question. This is a basis for judgement. Not up to an invisible standard? They’re going to be biased against you for pay raises, promotions, etc. Mention kids/lots of family/social engagements? That’s a tick against you for not being the kind of person who lives to work (yes, it’s gross and stupid). Mention lots of solitary things? Cool, that’s their mental note to ask more from you because you’re “not doing anything anyway.” By all means, be friendly with your coworkers/talk about shared interests if you want, but it is none of your boss’s business, and be aware what could get back to them.
Don’t. Tell. Employers. Shit.
Hopefully people already know this by now, but I saw way too often back when I worked in retail. Don’t add your coworkers or boss on social media. Yes, your coworkers too. You don’t want to accidentally say something to them or have them see a post and mention it to your boss. I’ve seen it happen.
The cops very clearly planted evidence on him because they had to make an arrest because all eyes were on them and whoever actually did the deed was making them look stupid.
Why would the real killer hero have kept the weapon on his person and traveled two states over while carrying it and a manifesto in his bag, conveniently turning the crime into a federal matter? The same guy whose bag they found in a park, filled with monopoly money? Why did the police turn off their bodycams, take Luigi's stuff, drive a block away, turn their bodycams back on, go back into the restaurant, and then arrest him?
From the moment of his arrest, even left-of-center media has been presuming his guilt without examining anything (e.g. calling him "the killer" instead of "alleged" or "accused") and then when I say he didn't do it, the nearest person chimes in with some quip that tells me they think he did do it but should go free anyway. Don't get me wrong, I would have the same attitude if he had done it. But he didn't. It makes me feel like the only sane person in the world, even among my staunchly leftist friends.
Text of tweet under the cut because it is loooong.
But... Stochastic Parrots.
Timnit Gebru was fired from Google in December 2020 for refusing to retract a research paper, and every single warning that paper made about large language models has now happened at a scale the industry spent 4 years trying to make people forget about.
Her name is Timnit Gebru.
She co-led the Ethical AI team at Google. She co-wrote a paper called "On the Dangers of Stochastic Parrots" with Emily Bender at the University of Washington and two other researchers. The paper was 14 pages long. It was submitted to a top AI ethics conference. And it was the reason Google decided that one of the most senior Black women in AI research could no longer work there.
The story Google told publicly was that she resigned. The story she told, confirmed by 2,695 of her colleagues in an open letter, was that she was fired by email while on vacation because she refused to either retract the paper or remove her name from it.
The paper had not even been published yet.
Here is what she actually wrote, and why every prediction inside it has now come true.
The first warning was about scale itself. Bender and Gebru argued that training ever-larger models on ever-larger scrapes of the internet would produce systems that appeared fluent but had no actual understanding of language. They called these systems stochastic parrots because they would repeat patterns from training data with statistical confidence and zero comprehension. The paper predicted that this apparent intelligence would fool both users and developers into trusting outputs that were structurally incapable of being reliable.
This was 2020. GPT-3 had just come out. The paper predicted the hallucination problem before anyone had a word for it.
The second warning was about bias amplification. The paper documented in detail that internet-scale training data contains systematic overrepresentation of dominant viewpoints and underrepresentation of marginalized ones. The models would not just absorb this bias. They would amplify it, because the optimization process rewards confident outputs, and confidence in language patterns tracks frequency in the training set.
The prediction was that hiring tools built on these models would discriminate against women. That healthcare triage tools would underperform on Black patients. That loan approval systems would entrench inequality while presenting their decisions as neutral algorithmic judgment.
Every one of those things has now been documented in deployment.
Amazon's hiring algorithm penalized resumes that contained the word "women" in any context. Healthcare risk scoring algorithms used by major US hospitals were found to systematically underestimate the medical needs of Black patients. Apple Card's credit algorithm gave wives credit lines 10x lower than their husbands for the same financial profile.
The third warning was about environmental cost. The paper calculated that training a single large language model produced emissions equivalent to the lifetime output of 5 cars. The prediction was that the race to scale would create an environmental footprint that would eventually rival entire industries.
In 2024, Google's emissions were up 48% from 2019, and the company explicitly blamed AI infrastructure. Microsoft's were up 29%, same reason. Both companies have now quietly abandoned the climate commitments they were publicly celebrating the year Gebru was fired.
The fourth warning was about documentation. The paper argued that the training datasets being assembled were too large for anyone to actually audit. Nobody at Google, OpenAI, Meta, or any other lab could tell you with confidence what was in the data their models were trained on. This was not a temporary problem to be solved later. It was a permanent feature of the approach.
In 2023, researchers discovered that the LAION-5B dataset, used to train Stable Diffusion and other major image models, contained thousands of images of child sexual abuse material. The companies that had trained on the dataset had no way of knowing. The paper predicted that category of failure 3 years before it was found.
The fifth warning was the one Google cared about most.
Bender and Gebru argued that the deployment of these systems would centralize linguistic and cultural power in the hands of the small number of companies that could afford to train them. The internet would become a place where the dominant voice was a statistical average of dominant voices, presented as a neutral assistant. Languages underrepresented in the training data would degrade over time as more web content was generated by these systems and fed back into the next training run.
This is now happening in real time. A 2024 study found that 57% of new web content in English is AI-generated or AI-assisted. Researchers studying low-resource languages have documented active degradation in translation quality, because the synthetic content fed back into training is itself worse in those languages.
The paper Google fired her for predicted the model collapse problem before model collapse had a name.
The mechanism behind why this all happened is the part of her work that nobody quotes.
Gebru's argument was not that AI is dangerous in some abstract sci-fi sense. Her argument was that AI is dangerous in a very specific structural sense. The technology was being built by a small group of researchers who shared similar backgrounds, worked at similar companies, and were rewarded for shipping products faster than competitors. The incentive structure made it impossible for safety, ethics, and bias concerns to slow anything down. Anyone inside the system who raised those concerns was either ignored, sidelined, or removed.
She was making that argument from inside Google.
Then Google proved her right by removing her.
The team Google had built to make sure their AI was safe was dismantled in 90 days because they did the job they had been hired to do. Margaret Mitchell, the other co-lead of the Ethical AI team, was fired two months after Gebru for searching through her own emails for evidence of how Gebru had been treated.
Gebru did not stop. She founded DAIR, the Distributed AI Research Institute, in 2021. The mission is to do AI research outside the control of the companies that have a financial interest in not hearing the answers.
Every prediction in the Stochastic Parrots paper has now been validated by deployment. Hallucinations are an industry-wide problem the largest labs cannot solve. Bias amplification has been documented in hiring, healthcare, lending, and criminal justice. Environmental costs are larger than entire small countries. Training data audits remain impossible. Model collapse is an active research crisis at every major lab.
The question worth sitting with is the one almost no one in the industry will say out loud.
Every researcher with the technical credibility to call out these problems watched what happened to her in December 2020 and made a calculation about their own career. The number of people willing to speak publicly about safety and ethics issues inside the major AI labs collapsed after that firing and has not recovered.
The researcher Google fired for warning about exactly what is now happening was right.
The company that fired her is now the second-largest deployer of the technology she warned about.
And the people inside that company who agree with her are not allowed to say so.
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