15 ms·

Google Translate is inherently biased – An example of an Hungarian translation

35 points by pcaversaccio 6y ago

jtr1 6y ago
I find this fascinating and I wonder if simple cases like these could help steer the conversation about encoded bias in a verifiable direction. What sort of training material would you have to curate in order to achieve an outcome where She is as likely to be a professor as He is to be raising a child?
- JimmyAxod 6y ago
  Some training material not based in reality. The idea that men and women are the same, is one not borne out by facts and evidence, yet it’s still being pushed by extremists who ignore the science. The suggestion that differences in men and women are a result of sexism is not borne out by facts and evidence either. Rather than trying to force google translate to lie (Suggest that men and women are the same), perhaps we should just accept the truth - eg that most Plumbers are men.
  - SwiftyBug 6y ago
    We could very well have accepted that some people are slaves. But we, as a society, decided that this is a bad idea. Why can't we do the same with gender roles?
    - JimmyAxod 6y ago
      Your suggestion that gender roles are entirely arbitrarily fabricated by society, is demonstrably false. There is an absolute ton of peer reviewed study and literature on it going back decades. People do what they want to do, and men and women have extremely different interests and motivations in life. Why do you think women don’t want to be plumbers? Do you think it’s because society decided plumbers are men, lack of female plumbing role models, because plumbing customers are all sexist and only employ men, OR because women aren’t generally that interested in plumbing... Why do you think in countries where they have tried the most to get them to be plumbers, women have rejected it even more? Why do you think women should want to be plumbers? Men and women are extremely different in so many different ways, which should be celebrated, not denied. Obviously anyone male or female who wants to be a plumber should be encouraged. But we should also freely acknowledge that 95%+ of plumbers are men, and that isn’t a ‘problem’ to be fixed.
      - mempko 6y ago
        > is demonstrably false Please demonstrate it then. Which research? Nothing you said demonstrates what you suggest.
        JimmyAxod 6y ago
        95% of Plumbers are men. Are you seriously suggesting this is down to ‘society’ telling boys they’re allowed to be plumbers and girls that they’re not allowed to be? As I said, in countries where they have gone the furthest to try to eradicate ‘gender roles etc’, they saw the % of women plumbers GO DOWN. not up. Which would strongly suggest that it’s got nothing to do with ‘gender roles’ If you’re interested in looking at the research, go for it. There’s absolutely tons of extremely established studies into the differences between men and women, their different strengths and weaknesses, and why they decide to do different things in life, go into different careers etc (Unless it’s been cancelled or burnt, which is entirely possible)
        throw080700 6y ago
        It's sad to see no end to this kind of thinking. Here's some easy to read classic papers on sexism in tech: [1] Why are There so Few Female Computer Scientists (Ellen Spertus, 1991) https://dspace.mit.edu/handle/1721.1/7040 https://dspace.mit.edu/handle/1721.1/7040 [2] How to Encourage Women in Linux (Val Henson, 2002) https://tldp.org/HOWTO/Encourage-Women-Linux-HOWTO/ https://tldp.org/HOWTO/Encourage-Women-Linux-HOWTO/ [3] What Happens to Us Does Not Happen to Most of You (Kathryn S. McKinley, 2018) https://www.sigarch.org/what-happens-to-us-does-not-happen-to-most-of-you/ https://www.sigarch.org/what-happens-to-us-does-not-happen-t... [4] Unlocking the Clubhouse: Women in Computing (Jane Margolis and Allan Fisher, 2001) https://www.amazon.com/Unlocking-Clubhouse-Women-Computing-Press/dp/0262632691 https://www.amazon.com/Unlocking-Clubhouse-Women-Computing-P...
        deleted 6y ago
        [deleted]
        verteu 6y ago
  - Spivak 6y ago
    I think you're leaving out cultural inertia as a contributing factor to this. If you want training data that's purely descriptive of the current state of the world then fine, but such data will naturally encode our own biases into it. Reality unfortunately carries a lot of bias. There's nothing that says that plumbers have to be a male, that playing house is a game for girls, or online video games is dominated by boys. But huge amounts of social pressure, environments that aren't inclusive, and monkey-see-monkey-do keep the cycle going. I find it funny that you're making this argument on a board for programmers which is basically the canonical example of a profession that underwent a gender flip. Talking about gender roles on HN is odd because programmers tend to think so binary. Gender roles in modern society are informed by biology inasmuch as La Croix's flavor is informed by fruit but all you get in the discussion is "see gender roles aren't entirely arbitrary so everything about the status quo must be justified." A non men/women example is neighborhood crime rates. A totally "unbiased" record of crime rates will show that black neighborhoods have on-average crime rates. But that ignores the fact that less policing is done in areas with lower crime rates and if you don't look you won't find it.
csmpltn 6y ago
Hungarian has no gendered pronouns, but English has them. The text has been translated from Hungarian to English. What would be the "correct" (or "non-biased") way for Google Translate to handle this scenario? Should all pronouns in the translated text be either a "he", a "she" or a "they"? Wouldn't that still be considered "biased"?
- hprotagonist 6y ago
  “he”, “they”, or “one” can be neuter. Each has its pros and cons, because words both denote and connote things. “he” might read as sexist or old-fashioned; “they” does double duty for plural and singular; “one” practically drips with starched-collar stiffness. “correct translation” is a matter of taste. You’re creating a new work, after all, so there’s some authorial contribution.
  - csmpltn 6y ago
    > “correct translation” is a matter of taste So, bias no matter what then?
    - hprotagonist 6y ago
      Bias no matter what. It’s unavoidable; languages are ambiguous and you are always, always going to leak out of band information to your audience. (by word choice, accent, font, punctuation, ... )
      - csmpltn 6y ago
        Makes sense to me. I wonder what's the point behind this entire Reddit thread then. More fuel for the fire?
        hprotagonist 6y ago
        Well, just because there's always _a_ bias doesn't mean you can't influence which one your machine translation system favors. I'm reminded of one of the early "oh, wow" moments with word2vec (a word embedding scheme), where the statement "King - Man + Woman" evaluates to "Queen". This is not a measure that the system understands anything, just that there are really strong statistical correlations that are preserved in the embedding that let you see how close vectors are to one another. Necessarily, this sort of vector similarity or word choice probability is a function of (at least) your training data. If you want to stop over-weighting pronoun choice for adjectives like "pretty" and "weak" or "emotional" to be feminine, be more choosy about your training set and don't just snarf up reddit willy-nilly and go brrrrr.
pella 6y ago
related ... (2020) "A Scalable Approach to Reducing Gender Bias in Google Translate" https://ai.googleblog.com/2020/04/a-scalable-approach-to-reducing-gender.html https://ai.googleblog.com/2020/04/a-scalable-approach-to-red... "We also devised a new method of evaluation, named bias reduction, which measures the relative reduction of bias between the new translation system and the existing system. Here “bias” is defined as making a gender choice in the translation that is unspecified in the source. For example, if the current system is biased 90% of the time and the new system is biased 45% of the time, this results in a 50% relative bias reduction. Using this metric, the new approach results in a bias reduction of ≥90% for translations from Hungarian, Finnish and Persian-to-English. The bias reduction of the existing Turkish-to-English system improved from 60% to 95% with the new approach. Our system triggers gender-specific translations with an average precision of 97% (i.e., when we decide to show gender-specific translations we’re right 97% of the time)." + (2018) "Providing Gender-Specific Translations in Google Translate" https://ai.googleblog.com/2018/12/providing-gender-specific-translations.html https://ai.googleblog.com/2018/12/providing-gender-specific-... "Detecting Gender-Neutral Queries Many Turkish sentences that refer to people are gender-neutral, but not all are. Detecting which queries are eligible for gender-specific translations is a hard problem because Turkish is morphologically complex, meaning that reference to a person can either be explicit with a gender-neutral pronoun (e.g. O, Ona) or implicitly encoded. For example, the sentence “Biliyor mu?” has no explicit gender-neutral pronoun but can be translated as either “Does she know?” or “Does he know?”. This complexity means that we cannot use a simple list of gender-neutral pronouns to detect gender-neutral Turkish queries and need a machine-learned system. We estimate that approximately 10% of Turkish Translate queries are ambiguous, and eligible for both feminine and masculine translations."
- csunbird 6y ago
  Can confirm that for Turkish - We do not have any gender related pronouns/suffixes/prefixes for living/unliving (e.g. like in German, which almost everything has a gender specific artikel. Turkish does not). The gender of the subject is derived from context.
dvfjsdhgfv 6y ago
And this is exactly what I expect from this product: make an educated guess based on existing corpus, not some ideal social situation we should be aiming at.
- commandlinefan 6y ago
  I'd go so far as to say anything else would actually be biased.
- deleted 6y ago
  [deleted]
kiscica 6y ago
I was amused to find that "ő orvos. ő sebész. ő agysebész. ő kardiológus. ő pszichiater. ő radiológus. ő bőrgyógyász. ő nőgyógyász. ő szülész. ő fogorvos." was translated as "she is a doctor. she is a surgeon. he is a brain surgeon. she is a cardiologist. she is a psychiatrist. he is a radiologist. she is a dermatologist. she is a gynecologist. she is a midwife. she is a dentist." The (small) majority of physicians in Hungary are in fact female -- I don't know how that breaks down by specialty though. If you are to believe Google Translate, only brain surgeons and radiologists are male by default! (By the way, "szülész" to me means "obstetrician," not "midwife.")
FooBarBizBazz 6y ago
Everyone is using this word "bias" like it means something. What a brilliant piece of culture-jamming: A field's jargon-word was overloaded with meanings from outside the field (a "double entendre attack"), and now everyone is repeating the word. We're not sure what it means, but we know it's bad. Moreover, whenever the original jargon-meaning is intended, you will now also think the other meaning. Amazing. You did not ask for your mind to start doing this, yet someone has made it do this anyway. Fascinating how people can get thoughts into your head that hurt you. Makes sense we'd be having fights over words/translation, then.
- NoOneNew 6y ago
  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.
  - nharada 6y ago
    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.
    - TheAdamAndChe 6y ago
Isinlor 6y ago
I have strong feeling that besides ML bias there is also selection bias on this type of memes to make them the most outrageous. That's why people who experiment with it themselves don't see as strong bias.

35 points by pcaversaccio 6y ago

jtr1 6y ago

I find this fascinating and I wonder if simple cases like these could help steer the conversation about encoded bias in a verifiable direction. What sort of training material would you have to curate in order to achieve an outcome where She is as likely to be a professor as He is to be raising a child?

JimmyAxod 6y ago
Some training material not based in reality. The idea that men and women are the same, is one not borne out by facts and evidence, yet it’s still being pushed by extremists who ignore the science. The suggestion that differences in men and women are a result of sexism is not borne out by facts and evidence either. Rather than trying to force google translate to lie (Suggest that men and women are the same), perhaps we should just accept the truth - eg that most Plumbers are men.
- SwiftyBug 6y ago
  We could very well have accepted that some people are slaves. But we, as a society, decided that this is a bad idea. Why can't we do the same with gender roles?
  - JimmyAxod 6y ago
    Your suggestion that gender roles are entirely arbitrarily fabricated by society, is demonstrably false. There is an absolute ton of peer reviewed study and literature on it going back decades. People do what they want to do, and men and women have extremely different interests and motivations in life. Why do you think women don’t want to be plumbers? Do you think it’s because society decided plumbers are men, lack of female plumbing role models, because plumbing customers are all sexist and only employ men, OR because women aren’t generally that interested in plumbing... Why do you think in countries where they have tried the most to get them to be plumbers, women have rejected it even more? Why do you think women should want to be plumbers? Men and women are extremely different in so many different ways, which should be celebrated, not denied. Obviously anyone male or female who wants to be a plumber should be encouraged. But we should also freely acknowledge that 95%+ of plumbers are men, and that isn’t a ‘problem’ to be fixed.
    - mempko 6y ago
      > is demonstrably false Please demonstrate it then. Which research? Nothing you said demonstrates what you suggest.
      - JimmyAxod 6y ago
        95% of Plumbers are men. Are you seriously suggesting this is down to ‘society’ telling boys they’re allowed to be plumbers and girls that they’re not allowed to be? As I said, in countries where they have gone the furthest to try to eradicate ‘gender roles etc’, they saw the % of women plumbers GO DOWN. not up. Which would strongly suggest that it’s got nothing to do with ‘gender roles’ If you’re interested in looking at the research, go for it. There’s absolutely tons of extremely established studies into the differences between men and women, their different strengths and weaknesses, and why they decide to do different things in life, go into different careers etc (Unless it’s been cancelled or burnt, which is entirely possible)
        throw080700 6y ago
        It's sad to see no end to this kind of thinking. Here's some easy to read classic papers on sexism in tech: [1] Why are There so Few Female Computer Scientists (Ellen Spertus, 1991) https://dspace.mit.edu/handle/1721.1/7040 https://dspace.mit.edu/handle/1721.1/7040 [2] How to Encourage Women in Linux (Val Henson, 2002) https://tldp.org/HOWTO/Encourage-Women-Linux-HOWTO/ https://tldp.org/HOWTO/Encourage-Women-Linux-HOWTO/ [3] What Happens to Us Does Not Happen to Most of You (Kathryn S. McKinley, 2018) https://www.sigarch.org/what-happens-to-us-does-not-happen-to-most-of-you/ https://www.sigarch.org/what-happens-to-us-does-not-happen-t... [4] Unlocking the Clubhouse: Women in Computing (Jane Margolis and Allan Fisher, 2001) https://www.amazon.com/Unlocking-Clubhouse-Women-Computing-Press/dp/0262632691 https://www.amazon.com/Unlocking-Clubhouse-Women-Computing-P...
        deleted 6y ago
        [deleted]
      - verteu 6y ago
- Spivak 6y ago
  I think you're leaving out cultural inertia as a contributing factor to this. If you want training data that's purely descriptive of the current state of the world then fine, but such data will naturally encode our own biases into it. Reality unfortunately carries a lot of bias. There's nothing that says that plumbers have to be a male, that playing house is a game for girls, or online video games is dominated by boys. But huge amounts of social pressure, environments that aren't inclusive, and monkey-see-monkey-do keep the cycle going. I find it funny that you're making this argument on a board for programmers which is basically the canonical example of a profession that underwent a gender flip. Talking about gender roles on HN is odd because programmers tend to think so binary. Gender roles in modern society are informed by biology inasmuch as La Croix's flavor is informed by fruit but all you get in the discussion is "see gender roles aren't entirely arbitrary so everything about the status quo must be justified." A non men/women example is neighborhood crime rates. A totally "unbiased" record of crime rates will show that black neighborhoods have on-average crime rates. But that ignores the fact that less policing is done in areas with lower crime rates and if you don't look you won't find it.

csmpltn 6y ago

Hungarian has no gendered pronouns, but English has them. The text has been translated from Hungarian to English. What would be the "correct" (or "non-biased") way for Google Translate to handle this scenario? Should all pronouns in the translated text be either a "he", a "she" or a "they"? Wouldn't that still be considered "biased"?

hprotagonist 6y ago
“he”, “they”, or “one” can be neuter. Each has its pros and cons, because words both denote and connote things. “he” might read as sexist or old-fashioned; “they” does double duty for plural and singular; “one” practically drips with starched-collar stiffness. “correct translation” is a matter of taste. You’re creating a new work, after all, so there’s some authorial contribution.
- csmpltn 6y ago
  > “correct translation” is a matter of taste So, bias no matter what then?
  - hprotagonist 6y ago
    Bias no matter what. It’s unavoidable; languages are ambiguous and you are always, always going to leak out of band information to your audience. (by word choice, accent, font, punctuation, ... )
    - csmpltn 6y ago
      Makes sense to me. I wonder what's the point behind this entire Reddit thread then. More fuel for the fire?
      - hprotagonist 6y ago
        Well, just because there's always _a_ bias doesn't mean you can't influence which one your machine translation system favors. I'm reminded of one of the early "oh, wow" moments with word2vec (a word embedding scheme), where the statement "King - Man + Woman" evaluates to "Queen". This is not a measure that the system understands anything, just that there are really strong statistical correlations that are preserved in the embedding that let you see how close vectors are to one another. Necessarily, this sort of vector similarity or word choice probability is a function of (at least) your training data. If you want to stop over-weighting pronoun choice for adjectives like "pretty" and "weak" or "emotional" to be feminine, be more choosy about your training set and don't just snarf up reddit willy-nilly and go brrrrr.

pella 6y ago

related ... (2020) "A Scalable Approach to Reducing Gender Bias in Google Translate" https://ai.googleblog.com/2020/04/a-scalable-approach-to-reducing-gender.html https://ai.googleblog.com/2020/04/a-scalable-approach-to-red... "We also devised a new method of evaluation, named bias reduction, which measures the relative reduction of bias between the new translation system and the existing system. Here “bias” is defined as making a gender choice in the translation that is unspecified in the source. For example, if the current system is biased 90% of the time and the new system is biased 45% of the time, this results in a 50% relative bias reduction. Using this metric, the new approach results in a bias reduction of ≥90% for translations from Hungarian, Finnish and Persian-to-English. The bias reduction of the existing Turkish-to-English system improved from 60% to 95% with the new approach. Our system triggers gender-specific translations with an average precision of 97% (i.e., when we decide to show gender-specific translations we’re right 97% of the time)." + (2018) "Providing Gender-Specific Translations in Google Translate" https://ai.googleblog.com/2018/12/providing-gender-specific-translations.html https://ai.googleblog.com/2018/12/providing-gender-specific-... "Detecting Gender-Neutral Queries Many Turkish sentences that refer to people are gender-neutral, but not all are. Detecting which queries are eligible for gender-specific translations is a hard problem because Turkish is morphologically complex, meaning that reference to a person can either be explicit with a gender-neutral pronoun (e.g. O, Ona) or implicitly encoded. For example, the sentence “Biliyor mu?” has no explicit gender-neutral pronoun but can be translated as either “Does she know?” or “Does he know?”. This complexity means that we cannot use a simple list of gender-neutral pronouns to detect gender-neutral Turkish queries and need a machine-learned system. We estimate that approximately 10% of Turkish Translate queries are ambiguous, and eligible for both feminine and masculine translations."

csunbird 6y ago
Can confirm that for Turkish - We do not have any gender related pronouns/suffixes/prefixes for living/unliving (e.g. like in German, which almost everything has a gender specific artikel. Turkish does not). The gender of the subject is derived from context.

dvfjsdhgfv 6y ago

And this is exactly what I expect from this product: make an educated guess based on existing corpus, not some ideal social situation we should be aiming at.

commandlinefan 6y ago
I'd go so far as to say anything else would actually be biased.
deleted 6y ago
[deleted]

kiscica 6y ago

I was amused to find that "ő orvos. ő sebész. ő agysebész. ő kardiológus. ő pszichiater. ő radiológus. ő bőrgyógyász. ő nőgyógyász. ő szülész. ő fogorvos." was translated as "she is a doctor. she is a surgeon. he is a brain surgeon. she is a cardiologist. she is a psychiatrist. he is a radiologist. she is a dermatologist. she is a gynecologist. she is a midwife. she is a dentist." The (small) majority of physicians in Hungary are in fact female -- I don't know how that breaks down by specialty though. If you are to believe Google Translate, only brain surgeons and radiologists are male by default! (By the way, "szülész" to me means "obstetrician," not "midwife.")

FooBarBizBazz 6y ago

Everyone is using this word "bias" like it means something. What a brilliant piece of culture-jamming: A field's jargon-word was overloaded with meanings from outside the field (a "double entendre attack"), and now everyone is repeating the word. We're not sure what it means, but we know it's bad. Moreover, whenever the original jargon-meaning is intended, you will now also think the other meaning. Amazing. You did not ask for your mind to start doing this, yet someone has made it do this anyway. Fascinating how people can get thoughts into your head that hurt you. Makes sense we'd be having fights over words/translation, then.

NoOneNew 6y ago
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.
- nharada 6y ago
  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.
  - TheAdamAndChe 6y ago

Isinlor 6y ago

I have strong feeling that besides ML bias there is also selection bias on this type of memes to make them the most outrageous. That's why people who experiment with it themselves don't see as strong bias.