How convenient that a counterexample can't be named
s3p5r
joined 1 month ago
I feel like Luthor was a better counterexample for this before the model for his billionaire redesign was elected President of the USA.
Even so, Luthor hasn't had quite the same volume of appearances as Iron Man, Batman, Captain America and the other rich superhero tropes.
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.
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.
Some provide screen-reader instructions, but most places barely remember blind people exist. It's another example of people with disabilities being ignored and marginalised.
And then even if they do remember blind people exist, they probably forget there are people who aren't blind who can't do their tests for other reasons, like dyslexia or dexterity impairments.
And then you have hCaptcha who makes disabled people to sign up to their database to use their cookie.
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.