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How would you expect the computer programmer analogy be completed? I legitimately don’t know what a reasonable answer would be.

mulmen 6y ago
The takeaway is the model has bias. It’s up to humans to decide what to do with that information. Depending on the input “homemaker” may be a technically reasonable output. Should we use such a model to suggest career paths to high school students? Or should we reevaluate the methodology?
- lopmotr 6y ago
  Who cares about ML when we already do that: https://www.slideshare.net/yuyomajadero/jobs-occupations-professions-pictionary-poster-vocabulary-worksheet-1 https://www.slideshare.net/yuyomajadero/jobs-occupations-pro...
  - deleted 6y ago
    [deleted]
  - mulmen 6y ago
    The danger is in thinking ML can magically see past human biases and/or is not subject to it’s own types of bias.
    - lopmotr 6y ago
      Seems like an overhyped danger. Does anyone actually think that? You would have to not even know that the purpose of a language model is to model human language. But if that's the level of your understanding, why would you select a language model to use as a career guidance oracle? Such a negligent career advisor would be just as likely to use those children's posters with pictures of female nurses and male doctors. I'd like to add that there's also a danger in people trying too hard to avoid bias and losing important information. For example, a man who's a homemaker instead of a programmer is a less attractive partner for a woman. So such an occupation might harm both his quality of life and that of his partner. There is some useful information encoded in cultural bias. Even if that information turns out to be entirely socially constructed, it still has real harmful effects on real humans who go against it.
      - zimpenfish 6y ago
        > Does anyone actually think that [ML can magically see past human biases and/or is not subject to it’s own types of bias]? I know some people who, fairly strongly, believe that ML is the future of non-biased decision making, yes. > a man who's a homemaker instead of a programmer is a less attractive partner for a woman That's definitely going to be [CITATION NEEDED].
      - 6gvONxR4sf7o 6y ago
        > For example, a man who's a homemaker instead of a programmer is a less attractive partner for a woman. This is much to sweeping a generalization to have a place here. You might say a man who is a homemaker is less attractive than a programmer to you, but don't speak for everybody else.
- salawat 6y ago
  Hmmm... A Homemaker must balance a myriad of factors in order to create an environment within which a group of people can productively live and work. The Man/Woman link is the more humorous seeing as programning was originally considered women's work.
6gvONxR4sf7o 6y ago
Two independent things might best be analogized as A:B as C:B. So also computer programmer.
- lopmotr 6y ago
  Except that they're not independent and that looks like a fact which the model discovered.
  - 6gvONxR4sf7o 6y ago
    The model should be able to tell the difference between population demographics in a particular country and a definition. Demographically, they're not independent. Definitionally, they are entirely independent.

mulmen 6y ago

The takeaway is the model has bias. It’s up to humans to decide what to do with that information. Depending on the input “homemaker” may be a technically reasonable output. Should we use such a model to suggest career paths to high school students? Or should we reevaluate the methodology?

lopmotr 6y ago
Who cares about ML when we already do that: https://www.slideshare.net/yuyomajadero/jobs-occupations-professions-pictionary-poster-vocabulary-worksheet-1 https://www.slideshare.net/yuyomajadero/jobs-occupations-pro...
- deleted 6y ago
  [deleted]
- mulmen 6y ago
  The danger is in thinking ML can magically see past human biases and/or is not subject to it’s own types of bias.
  - lopmotr 6y ago
    Seems like an overhyped danger. Does anyone actually think that? You would have to not even know that the purpose of a language model is to model human language. But if that's the level of your understanding, why would you select a language model to use as a career guidance oracle? Such a negligent career advisor would be just as likely to use those children's posters with pictures of female nurses and male doctors. I'd like to add that there's also a danger in people trying too hard to avoid bias and losing important information. For example, a man who's a homemaker instead of a programmer is a less attractive partner for a woman. So such an occupation might harm both his quality of life and that of his partner. There is some useful information encoded in cultural bias. Even if that information turns out to be entirely socially constructed, it still has real harmful effects on real humans who go against it.
    - zimpenfish 6y ago
      > Does anyone actually think that [ML can magically see past human biases and/or is not subject to it’s own types of bias]? I know some people who, fairly strongly, believe that ML is the future of non-biased decision making, yes. > a man who's a homemaker instead of a programmer is a less attractive partner for a woman That's definitely going to be [CITATION NEEDED].
    - 6gvONxR4sf7o 6y ago
      > For example, a man who's a homemaker instead of a programmer is a less attractive partner for a woman. This is much to sweeping a generalization to have a place here. You might say a man who is a homemaker is less attractive than a programmer to you, but don't speak for everybody else.
salawat 6y ago
Hmmm... A Homemaker must balance a myriad of factors in order to create an environment within which a group of people can productively live and work. The Man/Woman link is the more humorous seeing as programning was originally considered women's work.

6gvONxR4sf7o 6y ago

Two independent things might best be analogized as A:B as C:B. So also computer programmer.

lopmotr 6y ago
Except that they're not independent and that looks like a fact which the model discovered.
- 6gvONxR4sf7o 6y ago
  The model should be able to tell the difference between population demographics in a particular country and a definition. Demographically, they're not independent. Definitionally, they are entirely independent.