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Situation: Men are clicking on job of mechanics, more than women. Consequence: men are now more likely shown mechanics job. What is gained: more accurate cont

by rvnx 1y ago

Situation: Men are clicking on job of mechanics, more than women. Consequence: men are now more likely shown mechanics job. What is gained: more accurate content, more interesting content, more engagement. As a result: men are more likely to be shown jobs interesting for men, and women are more likely to be shown jobs interesting for women. Which means: Increased chances to find a matching job, and to save time doing so.

troupo 1y ago
Nope. What you eventually get is women not getting a variety of jobs they could apply to and a death of men in professions that actually need more men (e.g. nurses, teachers etc.) We already been through this. It's not ancient history
- fastball 1y ago
  Yeahhhhhh, those jobs don't have those ratios due to facebook ads.
- rvnx 1y ago
  Keep in mind that these advertising algorithms are never 100% pushing jobs catered for a specific group, they keep a % of exploration. https://www.tutorialspoint.com/machine_learning/machine_learning_exploitation_and_exploration.htm https://www.tutorialspoint.com/machine_learning/machine_lear... This is exploration vs exploitation dilemma. For example let's say that 10% of ads are thrown randomly, and from these random rolls these patterns are discovered: > [Denver+<40-50> years+men]: mechanics +10% > [Denver+<40-50> years+men]: nurse -5% Then the system can apply these coefficients on 90% of the other traffic. If you are making 100% exploration (so 100% random), then it means the people are going to miss their relevant job opportunity (having a net negative impact on the society). Increasing exploration is a solution that would legally actually reduce biases of previouses patterns, but at the cost of less relevant content. In all cases, if the bias is real, exploration discovers them and the coefficients already naturally adjust. One exception, advertisers can artificially restrict saying "I want only men between 30-40" in their targeting filters. Then what Meta can do ? Not much.
  - troupo 1y ago
    > One exception, advertisers can artificially restrict saying "I want only men between 30-40" in their targeting filters. > Then what Meta can do ? Not much. --- start quote --- “We do not allow advertisers to target these ads based on gender,” Settle said in a 2023 statement. --- end quote --- Meta can start by doing what they claim they are doing?
- rpdillon 1y ago
  I think gendered professions are the norm across ancient history. Algorithmic advertising didn't create this.
  - troupo 1y ago
    Child labor, keeping women uneducated and many other practices were the norm across ancient history. Who are we to question the wisdom of our ancestors.
    - rpdillon 1y ago
      I'm not using ancient history to justify it. I'm saying it's been around longer than algorithmic advertising. The comment I'm replying to suggested that this was caused by algorithmic advertising, which is a non-sequitur.
      - troupo 1y ago
        It didn't even begin to suggest it was caused by algorithmic advertising. What it suggested was people to actually learn something about the world around them. Because we literally have jobs that at one point started as diverse/female dominated and then marketed exclusively at males. For example, IT/programming. Also, a lot of "traditional" roles don't need additional algorithmic biases to stay the same.
        rpdillon 1y ago
        A comment asserted that natural evolution of AI algos would result in women getting fewer ads for mechanic jobs, because society has that bias. You responded with: > Nope. What you eventually get is women not getting a variety of jobs they could apply to and a death of men in professions that actually need more men (e.g. nurses, teachers etc.) "What you eventually get" suggests that using algorithms leads to gender discrepancies. I'm saying gender discrepancies existed long prior to the algorithms. I'm not saying gender discrepancies are good (although I do think they are inevitable), I'm just saying they are the cause, rather than the effect, of the algorithm.
deleted 1y ago
[deleted]
piva00 1y ago
It also means perpetuating the bias, more men will then apply for the job while maybe some women that could get interested didn't get it shown, reinforcing the already existing issue. Why do we want to perpetuate biases without a chance to allow it to potentially be corrected?
- rvnx 1y ago
  Only if the advertiser restricts the audience to only men or only women or certain age groups. If there are no such restrictions, the algorithms self-balance over time naturally. But advertisers don't want that, because it makes them waste money, so instead they prefer to manually add targeting segments.
NoMoreNicksLeft 1y ago
[flagged]

by rvnx 1y ago

troupo 1y ago

Nope. What you eventually get is women not getting a variety of jobs they could apply to and a death of men in professions that actually need more men (e.g. nurses, teachers etc.) We already been through this. It's not ancient history

fastball 1y ago
Yeahhhhhh, those jobs don't have those ratios due to facebook ads.
rvnx 1y ago
Keep in mind that these advertising algorithms are never 100% pushing jobs catered for a specific group, they keep a % of exploration. https://www.tutorialspoint.com/machine_learning/machine_learning_exploitation_and_exploration.htm https://www.tutorialspoint.com/machine_learning/machine_lear... This is exploration vs exploitation dilemma. For example let's say that 10% of ads are thrown randomly, and from these random rolls these patterns are discovered: > [Denver+<40-50> years+men]: mechanics +10% > [Denver+<40-50> years+men]: nurse -5% Then the system can apply these coefficients on 90% of the other traffic. If you are making 100% exploration (so 100% random), then it means the people are going to miss their relevant job opportunity (having a net negative impact on the society). Increasing exploration is a solution that would legally actually reduce biases of previouses patterns, but at the cost of less relevant content. In all cases, if the bias is real, exploration discovers them and the coefficients already naturally adjust. One exception, advertisers can artificially restrict saying "I want only men between 30-40" in their targeting filters. Then what Meta can do ? Not much.
- troupo 1y ago
  > One exception, advertisers can artificially restrict saying "I want only men between 30-40" in their targeting filters. > Then what Meta can do ? Not much. --- start quote --- “We do not allow advertisers to target these ads based on gender,” Settle said in a 2023 statement. --- end quote --- Meta can start by doing what they claim they are doing?
rpdillon 1y ago
I think gendered professions are the norm across ancient history. Algorithmic advertising didn't create this.
- troupo 1y ago
  Child labor, keeping women uneducated and many other practices were the norm across ancient history. Who are we to question the wisdom of our ancestors.
  - rpdillon 1y ago
    I'm not using ancient history to justify it. I'm saying it's been around longer than algorithmic advertising. The comment I'm replying to suggested that this was caused by algorithmic advertising, which is a non-sequitur.
    - troupo 1y ago
      It didn't even begin to suggest it was caused by algorithmic advertising. What it suggested was people to actually learn something about the world around them. Because we literally have jobs that at one point started as diverse/female dominated and then marketed exclusively at males. For example, IT/programming. Also, a lot of "traditional" roles don't need additional algorithmic biases to stay the same.
      - rpdillon 1y ago
        A comment asserted that natural evolution of AI algos would result in women getting fewer ads for mechanic jobs, because society has that bias. You responded with: > Nope. What you eventually get is women not getting a variety of jobs they could apply to and a death of men in professions that actually need more men (e.g. nurses, teachers etc.) "What you eventually get" suggests that using algorithms leads to gender discrepancies. I'm saying gender discrepancies existed long prior to the algorithms. I'm not saying gender discrepancies are good (although I do think they are inevitable), I'm just saying they are the cause, rather than the effect, of the algorithm.

deleted 1y ago

[deleted]

piva00 1y ago

It also means perpetuating the bias, more men will then apply for the job while maybe some women that could get interested didn't get it shown, reinforcing the already existing issue. Why do we want to perpetuate biases without a chance to allow it to potentially be corrected?

rvnx 1y ago
Only if the advertiser restricts the audience to only men or only women or certain age groups. If there are no such restrictions, the algorithms self-balance over time naturally. But advertisers don't want that, because it makes them waste money, so instead they prefer to manually add targeting segments.

NoMoreNicksLeft 1y ago

[flagged]