Imagine if you had to abandon your social life some years ago for the job and the only people you talk to on a daily basis are your coworkers on Slack.
Thanks for the reminder that my life is garbage, I guess. Unless you count the pleasantries I exchange with the person who makes my coffee in the morning?
I'm not employed by automattic, but this thread still cut deep with similar work culture.
For anyone else also interested, I went and had a look at the links Dessalines kindly provided.
The source on the graphs says "Sources: Daniel Cox, Survey Center on American Life; Gallup Poll Social Series; FT analysis of General Social Surveys of Korea, Germany & US and the British Election Study. US data is respondent’s stated ideology. Other countries show support for liberal and conservative parties All figures are adjusted for time trend in the overall population." Where FT is financial times.
It's not clear how the words "liberal" and "conservative" were chosen, whether they're intended to mean "socially progressive" and "socially traditional" or have other connotations bound with the political parties too, and whether the original data chose those descriptions or if they're FT's inference as being "close enough" for an American audience.
Unfortunately the FT data site is refusing to let me look at them without "legitimate interest" advertising cookies so I can't tell you much more or if there's any detail on methodology.
List of sources quoted in this list of "push back:
So if you were hoping for actual consequences from his base or even just someone new and noteworthy criticizing him, this is not the article for you. I'm glad the Trade Unions are going to spread the word though, that will be a good thing.
I don't toil in the mines of the big FAANG, but this tracks with what I've been seeing in my mine. I also predict it will end with lay-offs and companies collapsing.
Zitron thinks a lot about the biggest companies and how it will ultimately hurt them, which is reasonable. But, I think it ironically downplays the scale of the bubble, and in turn, the impacts of it bursting.
The expeditions into OpenAI's financials have been very educational. If I were an investigative reporter, my next move would be to look at the networks created by venture capitalists and what is happening inside the companies who share the same patrons as Open AI. I don't say that as someone who interacts with finances, just as someone who carefully watches organizational politics.
People have grown up reading comic books and watching movies about generous billionaire superhero saviors. They want to believe that exists because it's what they've been taught justice looks like.
If only all my snark could elicit such absurd perfection.
You're both adorable
So long as you don't care about whether they're the right or relevant answers, you do you, I guess. Did you use AI to read the linked post too?
Joy isn't reserved for the young, but it's sure fucking easier to be joyful when your body hurts less because you're far less likely to have one or more chronic pain conditions in your youth.
Your heart won't harden? It might just with atherosclerosis and enough time.
So go enjoy the joy even more now while it's still easier.
References weren't paywalled, so I assume this is the paper in question:
Hofmann, V., Kalluri, P.R., Jurafsky, D. et al. AI generates covertly racist decisions about people based on their dialect. Nature (2024).
Abstract
Hundreds of millions of people now interact with language models, with uses ranging from help with writing^1,2^ to informing hiring decisions^3^. However, these language models are known to perpetuate systematic racial prejudices, making their judgements biased in problematic ways about groups such as African Americans^4,5,6,7^. Although previous research has focused on overt racism in language models, social scientists have argued that racism with a more subtle character has developed over time, particularly in the United States after the civil rights movement^8,9^. It is unknown whether this covert racism manifests in language models. Here, we demonstrate that language models embody covert racism in the form of dialect prejudice, exhibiting raciolinguistic stereotypes about speakers of African American English (AAE) that are more negative than any human stereotypes about African Americans ever experimentally recorded. By contrast, the language models’ overt stereotypes about African Americans are more positive. Dialect prejudice has the potential for harmful consequences: language models are more likely to suggest that speakers of AAE be assigned less-prestigious jobs, be convicted of crimes and be sentenced to death. Finally, we show that current practices of alleviating racial bias in language models, such as human preference alignment, exacerbate the discrepancy between covert and overt stereotypes, by superficially obscuring the racism that language models maintain on a deeper level. Our findings have far-reaching implications for the fair and safe use of language technology.
For anyone else wondering: