Comment by NoOneNew | Hacker News Reader

Comment by NoOneNew | Hacker News Reader

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The real bias here is the cherry picking to showcase a narrative. The point that ML is just a statistical machine would be apparent if they put beautiful and handsome side by side. 51%+ of the time, beautiful is associated with women. 51%+ of the time, handsome is associated with men. Yea, clever is used for guys. Sharp is usually used for women. Same meaning, but you use it for different genders unknowingly. Not a big deal. It's just as bad as arguing the difference between a kilt and a skirt. Same damn thing. My only real surprise is, "he teaches". I'd assume that'll have a more female connotation since women are typically associated as teachers. But it depends on the learning data set as well. Maybe the set just happened to accidentally be guy centric regarding "teaches". Hell, if you have a data set based solely on metaphysical new age books, you'd have an ML pump out which crystal to keep in your pocket to cure polio and to stay away from vaccines. Doesn't mean the AI has any special insight.

Theres nothing special here. Its human pattern recognition over fitting fishing for attention and a stamp on their simp card using political hot topics.

Even the examples seem hand picked.

Ő takarít is translated as he cleans.

Ő takarító is translated as she is cleaning (the correct translation here would be she's a cleaner, also ő egy takarító would be the most used way...the original sentence was clearly modified to invoke controversy).

Guess which one the Reddit example contains from the two..also it was modified on purpuse, you can see from the sentences.

Even if you think the example presented here isn't a big deal, it still exposes a larger issue in these large language models. These models learn from historical data and that history may not be the behavior we want in the future.

Who is the "we" you're talking about?

I'm not sure I take your point here. Broadly, humans. More specifically, a company, a government, a country, an open source community, a family.

Is your point that there be disagreement on ML policy? I don't think that makes any difference to the fundamental research problem.

There was no point, just a request for clarification which you provided. Thank you.

I want our future to be more focused on getting rid of class warfare and inane divisive rhetoric. Political red herring lip service crying about the statistical chances of a pronoun being used by a company that randomly created their data not only is not my concern, but I and society shouldn't be lumped in with their mistake. Google made their text language models, not "society" or "culture". Google is not the English speaking world, nor should their actions become a guilty by association for anyone that speaks English. Grow up. There are more important things to worry about. Ecological deterioration. Desert expansion. Droughts. Climate change. Water contamination. General air pollution. Deterioration of the working class. The college class looking down on the working class, creating a further divide in society. Financial elites running the show. Over reliance on the media. Family farming falling out the wayside. Birth rates tanking. Corporate corruption. Social isolation based depression/anxiety rates. Corporate take overs of everyday life. Opioid crisis. Plus some more that I can't think of. All more important than worrying about why the fuck Google says, "she cooks" instead of "he/it cooks". Google was not your lord and savior. No tech company was. Get over it.

So? Censor history to keep us from making its mistakes? Nothing down that road is workable even if you could convince yourself it was justified.

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