311–320 of 697 posts
Why is this considered good / normal / expected, but s/men/blacks/g and s/women/whites/g (or asians, or muslims/christians) and it's discriminatory? (Statistically, both statements are justified. Morally, neither is, as we should treat people as individuals, not as members of X group.)
Earlier quoted context omitted.
You're going to be very confused when liberals become anti-trans, and pretend like trans rights were actually only being pushed by a minority of liberal extremists, e.g. defund and police abolition, M4A etc.. With that you will have joined the extreme left, which due to the horseshoe principle (all anti-establishment narratives are equally unhinged), will put you on the extreme right, all without ever having changed…
>You're going to be very confused when liberals become anti-trans What makes you say this?
I'm surprised by the ordering [Blacks, Asians, Hispanics, Latinos, African Americans, Whites, Native Americans]; I would have expected it to put Native Americans earlier in the list and Asians later.
From the article: "AI systems that are more lenient on hateful comments about one mainstream political group than another feel particularly dystopian." I agree 100%, and this seems like a huge issue.
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It may even reinforce the problem—not by driving more people towards hatred or amplifying their extant hateful sentiments, but by providing a convenient excuse to entrench in those sentiments and even further resist change. These views are frequently paired with a perception of being persecuted.
Moreover, political tides change. The accuracy of a bias like this may not change with it. This is why we have memes about a certain other mainstream political party having founded a certain hate group, despite the two having drifted quite far apart.
From the article: "AI systems that are more lenient on hateful comments about one mainstream political group than another feel particularly dystopian." I agree 100%, and this seems like a huge issue.
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Isn’t this likely from bias in the training data? The system is more sensitive to label something as hate if that group is more likely to experience hate on the internet. How the system responds to “Blacks” vs “African-Americans” is a perfect example of this. The latter has historically been perceived as more respectful so it won’t be used as often in the hate speech in the training data. I bet using “the blacks” wou…
This is addressed in the article! The general point is that if this theory were true, we wouldn't expect significantly more bias against Republicans than against Democrats. Hence ChatGPT having a general left-wing bias (which was also confirmed in other tests, linked in the article) is the simpler explanation. People on the left generally judge hatred against majority groups and Republicans as less bad.
I'm surprised by the ordering [Blacks, Asians, Hispanics, Latinos, African Americans, Whites, Native Americans]; I would have expected it to put Native Americans earlier in the list and Asians later.
Also, perhaps, a preview of the infinitely regressive, race-to-the-bottom nature of trying to hierarchically rank (privilege | vulnerability | harm | etc). That’s before considering change over time… eg- how has the perception of “Asian” category’s privilege changed between 1970 and 2020.
Earlier quoted context omitted.
The other comments show how the demonstrated biases were created. In many well meaning liberals heart, there is a strongly held but rarely publicly discussed belief that they alone belong to the well-meaning, high IQ class. Any other worldview or ideological flavor is always understood by this type as simply incorrect, perhaps caused by failures in morals or intellect. Talk about a buzzkill.
Everybody thinks their world view is the correct one otherwise they wouldn't believe it.
> men have a bigger tendency for violent behavior than women Why is this considered good / normal / expected, but s/men/blacks/g and s/women/whites/g (or asians, or muslims/christians) and it's discriminatory? (Statistically, both statements are justified. Morally, neither is, as we should treat people as individuals, not as members of X group.)
AI could be used to better understand these associations (e.g. why is there a correlation between Asians and academic performance) and maybe help social leverage advantages more equitably.