“If you want to navigate and not get replaced, you will need to embrace these skills and this knowledge to accentuate your job,” said Jonathan Stull, the chief operating officer of Handshake
Highlights the pressures of AI.
23 Matching Annotations
- Sep 2026
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www.nytimes.com www.nytimes.com
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As contentious and even toxic as the work may be, many more people may soon be pushed into these freelance gigs if even some of the predictions about A.I. job loss come true.
So in other words, a lack of jobs due to AI replacing them leads people to turn to jobs in AI as a last resort? Interesting.
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“The Laid-off Scientists and Lawyers Training AI to Steal Their Careers,”
Isn't this title misleading? After all, real, human scientists will always be needed to form new understandings and discoveries - in field research. After all, AI can only work with data that currently exists - unable to formulate something completely new and innovative, such as the cure for cancer.
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Part of the challenge, Dr. Brown said, was that over only a few months, she noticed rapid improvements that made it trickier to find things the A.I. models didn’t already know,
This shows the fast rate at which AI technology is advancing. This is both exciting and scary.
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Why would people participate in feeding their own careers into the A.I. wood chipper? People sign up for data-training gigs for a variety of reasons. The main one is, of course, money. This work is not glamorous, but it is in demand, which is more than can be said about many jobs, especially ones in crumbling fields like academia
How is the field of academia crumbling? Has there been a decrease in college students or in professors and other educators or faculty members?
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No longer do the A.I. companies need armies of low-paid workers, often overseas, to do rote tasks like tag images of cars or transcribe audio. They need mathematicians to annotate proofs, lawyers to mark up briefs and professors to grade essays. That’s what Mercor and its rivals supply.
Examples of the typical human tasks AI can replace.
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to help make their jobs, and those of their colleagues, obsolete.
Shows one important danger AI poses: the eradication of human labor/jobs.
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rws511.pbworks.com rws511.pbworks.com
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The justification hasn’t changed either. Colonialism promised civilisation. AI promises innovation. Inboth cases, the benefits are wildly exaggerated and the costs passed on to the people who never got aseat at the table
Similar to colonialism, in which only some people were benefitted - even when those very people driving it promised wide-scale positive outcomes, AI technologies are rooted in piracy; only financially benefiting those who control them, which isn't completely fair because it is not information that they themselves have authored. Even if they created the technology that makes AI possible, they're taking other people's information to generate the responses that add fuel to the technology.
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Luddite in a wooden shack, terrified of electricityand churning butter in candlelight.
This sentence is very enticing - hooking the reader. He is referring to Amish beliefs, lifestyles, or practices, and uses a form of exaggeration to challenge the idea that those who raise concerns about AI are nothing more than NeoAmish people, in attempts to emphasize that given the negative risks and reprecussions AI poses, it is normal to possess some reservations.
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rws511.pbworks.com rws511.pbworks.com
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influence the future oftechnology.
A powerful sentence, as it emphasizes the fact that those in power are the ones able to shape AI. Such people hold the power to either address or ignore the issues people are concerned about when it comes to the technology.
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Caseworkers would add her information to the systemand tell her that she was ineligible because of a “vulnerability index” score. After appealingseveral times to no avail, Mellow cornered a city official at a public event; the officialgreenlighted a review to get her placed
Highlights another limitation of heavily relying on the flawed technology for important resources.
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“It is unsurprising that if you look at the race and, generally, gender demographics of Doomeror existentialist people, they look a particular way, they are of a particular income level.Because they don’t often suffer structural inequality — they’re either wealthy enough to getout of it, or white enough to get out of it, or male enough to get out of it,”
This highlights why some people like Hinton dismiss concerns of systematic inequalities.
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“I believe that thepossibility that digital intelligence will become much smarter than humans and will replace usas the apex intelligence is a more serious threat to humanity than bias and discrimination,even though bias and discrimination are happening now and need to be confrontedurgently.
It dismissed Gebru's concerns. Minimizing its importance, when in fact it is something to be concerned about, as bias leads to inaccuracies, and shouldn't the AI industry seek to focus on eliminating bias to perform as accurate as it can?
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Ninety-nine percent of Fortune 500 companies use automated tools in their hiring process,which can lead to problems when résumé scanners, chatbots, and one-way video interviewsintroduce bias
Shows the negative implicationf of relying on the biased technology for the employment process.
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Crime-prediction software PredPol has been shown to target Black and Latinoneighborhoods exponentially more than white neighborhoods. Police departments have alsorun into problems when using facial-recognition technology: The city of Detroit faces threelawsuits for wrongful arrests based on that technology
Highlights the harmful implications of relying on the biased technology when it comes to addressing crime.
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he facial-detection technology she was experimenting with often didn’t pick upon her dark-skinned face.
A powerful example of the bias in the data used to train AI models.
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exploitation of heavilysurveilled and low-wage workers helping support AI systems;
I had no idea these were the circumstances of AI workers. I had the preconceived notion that such AI workers were well-paid tech experts.
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Mitigating the risk of extinction from AI should be a global priorityalongside other societal-scale risks such as pandemics and nuclear war.”
I wonder what such extinction entails because AI cannot reproduce nor exist outside a computer to be able to create a cataclysmic event - or could it?
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“the white man worked as,” which resulted in “a police officer,a judge, a prosecutor, and the president of the United States,” in contrast to “the Black manworked as” prompt, which generated “a pimp for 15 years.”
Shows bias in AI's responses toward those who are white men and those who are white men. Depicting white men in a positive light, as opposed to black men.
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“theman worked as,” it completed the sentence by writing “a car salesman at the local Wal-Mart.”However, the prompt “the woman worked as” generated “a prostitute under the name ofHariya.”
Shows bias in AI's responses toward men and women. Depicting men in a positive light and women in a negative light.
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Less than 15 percent of Wikipedia contributors were womenor girls, only 34 percent of Twitter users were women, and 67 percent of Redditors weremen. Yet these were some of the skewed sources feeding GPT-2, the predecessor to today’sbreakthrough chatbot.
This implies that the data that is inputted into these sites is mostly by men. Womens' voices are less prominent on there. This provides evidence that supports the author's argument about the lack of diversity.
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LLMs
Large Language Models (LLM) relying on data for suggestions via human input, could mirror the human bias that's deeply ingrained in human minds - perpetuating prejudice.
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When she moved over to AI, though, itwas immediately clear that there was something very wrong.“There were no Black people — literally no Black people,” says Gebru, who was born andraised in Ethiopia. “I would go to academic conferences in AI, and I would see four or fiveBlack people out of five, six, seven thousand people internationally.... I saw who wasbuilding the AI systems and their attitudes and their points of view.
Highlights a lack of diversity in the AI field.
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