6 ms·

Teaching yourself about structural racism will improve your machine learning

47 points by joker3 7y ago

weberc2 7y ago
The definition for structural racism according to the article: > Structural racism refers to “the totality of ways in which societies foster [racial] discrimination, via mutually reinforcing [inequitable] systems...(e.g., in housing, education, employment, earnings, benefits, credit, media, health care, criminal justice, etc.) that in turn reinforce discriminatory beliefs, values, and distribution of resources,” reflected in history, culture, and interconnected institutions (Bailey and others, 2017). I think I might be misunderstanding, but given this includes “culture”, is this so sufficiently broad such that hypothetical scenarios such as this (no idea if this is accurate) would be captured “white people are culturally more likely to use crystal meth than other racial groups, ergo they are victims of (a certain kind of) systemic racism”? It seems like this is just a catchall for any kind of error associated with a racial group, and the article is merely cautioning against such errors. If so, it begs the questions “why not just say so?” and “why use such a loaded term like systemic racism?”.
- LegitShady 7y ago
  Modern sociology in no way resembles a scientific study and is heavily politicized. A bunch of nonsense political "researchers" citing each other in drivel papers desperate for relevance. It's now leaking into other fields. I remember when I first heard stem be changed to steam to include "arts" a laughed at how inclusive and utterly useless it is.
  - travisoneill1 7y ago
    They even make up math. I had a sociology prof in college teach us that to mathematically determine that there is a difference between groups, the difference between the means had to be greater than the range in either group (not even any reference to sample size). I replied that by this test you couldn't even determine that there is a height difference between men and women, and the prof said that in fact you can't and that it was a good example of this test.
    - bransonf 7y ago
      That professor was wrong or your understanding is. There are plenty of statistically viable ways to determine differences between groups. Even a simple T-test is usually sufficient. The difference of means does not have to be more than the range in either group. Standard deviation is what’s important here. You use a test statistic to determine the relative value of the real mean within a confidence interval. It’s whether these intervals overlap that you can determine a significant difference between groups.
      - travisoneill1 7y ago
        I know that the professor was wrong. That was the point of the comment. That a professor in a so called science class could get the math so comically wrong.
  - pvarangot 7y ago
    Postmodern sociology is revisionist towards trying to see society only through a lens that is also easily probable to be statistically sound, this is because of how more quantitative socioeconomic theories failed to predict very big crises or events in society. It can be argued that asking for scientific rigor in sociology to the same extent as in other human sciences raises the bar too much because to validate some theories the experiments are either impossible, prohibitively expensive, or so massive that they would bias the whole of society. Also, I think it would marvel you knowing how much things you would call "scientific study" are also heavily politicized. If this bothers you to a big extent I would recommend you try to find comfort in thinking about postmodern sociology as a religion different than yours. They won't be bothered by it and it will probably fit your mindset in a more soothing way than thinking about them as scientists. It's not that they are trying to publish their findings in ACM TOPLAS or something, they have their own community and books and kinda like it.
    - LegitShady 7y ago
      If it was treated as religion instead is science I would be open to that, but the papers churned out by "experts" today become policy tomorrow that effect everyone.
      - pvarangot 7y ago
        Religions dictate and have been dictating policy since forever we had governments and even before that. It's what people understand and mostly everyone seems to be ok with it.
    - weberc2 7y ago
      I do think of it as a religion—one that is state sponsored and masquerades as science.
  - roflc0ptic 7y ago
    Sociology is way more rigorous than you’re making it out to be. Studying people is hard, but it’s making good faith effort in that direction, reproducibility crisis notwithstanding. Take the “Sokal 2.0” affair, where some profs sent obviously bogus research to various journals. Notably, while they were able to get “rape culture among dogs at the dog park” (or maybe it was racism, easy to look up) published in a gender studies journal, they couldn’t get published in sociology journals. Sociology has standards. The absurdities committed by gender studies as an institution don’t falsify racism/other forms of oppression. They might be wrong, but you’re certainly not right.
    - LegitShady 7y ago
      >Sociology has standards. Mostly political and much of it unreproducible. Desperate political academics using non science to argue their opinions and right and citing each other into fake legitimacy. Garbage studies garbage standards garbage journals from people who couldn't hack it elsewhere.
  - dang 7y ago
    Please don't take HN threads on generic ideological tangents. They are boring and repetitive and therefore off topic here. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
    - LegitShady 7y ago
      It wasnt an unrelated tangent. It's directly related to the drivel in op.
      - dang 7y ago
        Tangents are always related at some point. The problem is not where they start, but what they lead to. If they start from drivel but lead to hotter drivel, like internet ideology wars, HN gets much worse. Please just avoid generic ideological battle here.
        LegitShady 7y ago
        Fair enough, although I think it's unavoidable when you're talking about what I think to be essentially made up terms.
        weberc2 7y ago
        It is odd that your comment was “ideological battle” but not the original article. I guess the original was sufficiently jargon-laden.
- hellllllllooo 7y ago
  Expected comments minimizing the article on HN and was not disappointed. Why is it that so many people here find it so hard to accept that there is an actual issue with systematic racial bias with what-abouting it or diluting it to nothing? There's definitely an issue in Silicon Valley and tech but maybe people find it hard to acknowledge because it means admitting some culpability or taking some responsibility.
- whatismypass 7y ago
  It's talking specifically about racial discrimination that results from <long list of interrelated things>. I don't think that means "any kind of error" and I don't think white people are racially discriminated against for having higher meth usage.
  - weberc2 7y ago
    You really misunderstood me. I didn’t claim anything about white people; I gave a hypothetical scenario. And that hypothetical scenario wasn’t about white people facing discrimination for higher meth usage, only that such an inequitable distribution of meth usage seems to satisfy TFA’s definition for structural racism. The fact that it seems implausible to say so suggests the definition is not especially useful.
- Enginerrrd 7y ago
  There are some very real effects that need to be acknowledged in order to design a good system. Here's a hypothetical example I gave in a similar thread here a few months back. It's loosely based (Though not too far removed from reality!) on some real-world systems that failed to address this: Suppose you are designing a facial recognition system for police to use in the field while investigating a recent crime to see if anyone with a criminal history is nearby. (Data taken from: https://en.wikipedia.org/wiki/Incarceration_in_the_United_States#Ethnicity https://en.wikipedia.org/wiki/Incarceration_in_the_United_St...) Because blacks are over-represented in the US criminal justice system (40% of the prison population vs 13% of the population) and because part of what defines "black" is the outward appearance of certain facial features, a facial-recognition algorithm which is trained to recognize criminals, with a cost function based on prediction accuracy alone, and facial features as input parameters is likely going to have false positives that over-represent blacks. It's very important to consider this when you develop a training set. The developer error (who mostly failed to understand Baye's theorem here) might work something like this: They take 100 innocent people's faces at random. (On average it will have only 13 blacks) Then take 100 random criminal faces from inmates. (On average it will have 40 blacks.) Then mix up the groups into your training set and assign a prediction score 1 or 0 depending on whether or not your classifier has correctly predicted whether or not a face was in the criminal group. Then, based on no other feature than race, your neural net can get better performance based solely on guessing more often that black people are criminals. That's not a good thing. In fact, if it's looking at a black face from its training set, the odds are nearly 2 to 1 that it's one of the criminals, even though the odds that are at least 2 to 1 against a random black person having a criminal history. The likelihood of being falsely identified as having a criminal history is much greater based on the only variable of being black. And this type of thing has happened several times already in production systems! Conversely, the same system, trained on the same data in the same training set, can get higher performance than random by simply guessing that any non-hispanic white person does NOT have a criminal history. Thus, it's pretty important to correct your training set to reflect the correct Bayesian prior, and the underlying structures that sometimes go by the label "structural racism" or "institutional racism" are essentially exactly that reality in this case.
  - hello_marmalade 7y ago
opwieurposiu 7y ago
This paper fails to account for (or even mention) genetics. To expand on the breathing capacity example, consider the case of the sherpas. https://www.npr.org/sections/goatsandsoda/2017/05/28/530204187/the-science-behind-the-super-abilities-of-sherpas https://www.npr.org/sections/goatsandsoda/2017/05/28/5302041...
ralusek 7y ago
I think beyond not feeding race in as a feature to any model, this stuff is mostly nonsense. If you include race as a feature, then I think it's likely that the model will become racist, because race is so highly correlated to behaviors and patterns which are in large part the consequence of all sorts of things, including historical racism, that a model could easily mistake race as a causal factor. If you don't feed race in as a feature, however, the outputs are hardly racist. My impression has been that by and large the argument actually being made is that "we have been trying to correct for historical injustices by actively using race and gender as mechanisms for advantaging minorities and women, and an unbiased model is not properly accounting for these particular objectives." Take something like a bank loan. If you had a model at a bank which took credit score, income, wealth, and collateral into account, black Americans would have loans rejected at a higher rate than white Americans. Is this model racist? No, this model doesn't even know what race is, all it knows is credit scores, income, wealth, and collateral. Does the fact that black Americans used to be slaves in the US, or were kept out of certain housing markets, contribute towards the fact that black Americans, on average, have lower credit scores, income, wealth, and collateral? Of course. But is this model racist? Literally not at all. It is completely unbiased, and exactly what the model should be. If the case you're making is that you think that there should be a national effort to correct for historical injustices that were done by the state by actively discriminating by race, that is a completely different discussion. Having all of our decision-making apparatuses factor in the infinite pile of historical injustices that may have contributed to an individual's particular circumstances is not the way to go. Keep models simple and limited to what is relevant for that particular criteria. Fix injustices further upstream, or you make the whole system a convoluted nightmare.
- zbyte64 7y ago
  The article mentions why simply excluding race isn't good enough: "Crucially, incorporating more proximal and predictive variables into models, rather than relying on race variables to act as proxies, will improve transportability of algorithms across contexts." If we want better models then they need to also model structural racism.
- abdullahkhalids 7y ago
bransonf 7y ago
I did research briefly in a lab studying heart rate variability. HRV is a really interesting statistic in predicting heart health outcomes, and very interesting is the racial difference in HRV. Basically, African Americans exhibit much higher heart rate variability, meaning their nervous system is much quicker to react to stimuli (quicker time to fight or flight response, for example) and this still isn’t well understood in the field. A naive understanding is that racial physiology is just different. And plenty of people will stand by this. However, self reported stress scores offer some insight into the difference. High stress African Americans with High HRV lived as long as Low stress, low HRV White/Asian Americans. Most likely, the process by which the nervous system regulates itself is heavily influenced by life course events. Medical science, in my experience, lacks in quantifying these social factors, and too often underplays their significance in determining physiological differences. Humans are incredibly dynamic systems, and the case can be made that we adapt to stimuli in order to survive. It’s certainly possible that the physiological difference we observe in different racial populations is due to survival based on this principal. It’s only recently that I’ve seen research trying to get at these social/physiological mechanisms, but as far as funding is concerned, hard biological sciences are more interesting. Everyone just wants to edit the genome and call it a day, but I think we could get much further if we understood how life events lead to physiological ailments later in life.
- sansnomme 7y ago
  There is also the political implications. Nobody wants to fund research which will only stir up controversy, especially since many higher education institutions are located in liberal areas. Too many medical studies on gender, race, and intelligence would only create unrest. Just take a look at how badly the Stanford ML paper on predicting gender orientation was received. Emphasizing the differences in "fight or flight" response timings may save lives, but at the same time provide ammunition for people to draw lines between metrics and historical events/practices along societal fault lines, which I think everyone can agree is not a good thing.
  - ramblerman 7y ago
    > provide ammunition for people to draw lines between metrics and historical events/practices along societal fault lines, which I think everyone can agree is not a good thing. Putting your head in the sand and trying to deny the existence of potentially uncomfortable facts actually fuels these fringe thinkers more imo. Part of their whole schtick is that the truth is being hidden from them. Look at how the media handled the claim that Serena Williams couldn't beat a top 10 male player. Instead of actually putting it to the test, the whole angle was about how insulting and preposterous that was etc etc. We are not all the same, but we deserve to be treated so. It's as simple as that. Trying to halt scientific progress because it doesn't fit your world view is quasi religious.
kryogen1c 7y ago
> 4. Conclusion "...grounding one’s work in an understanding of structural racism will improve model accuracy..." It is not an interesting result to say models not modeling reality are less accurate; the cogent discussion is to what degree systemic racism exists IN reality. This is textbook begging the question. > Acknowledgements: Conflict of Interest: None declared. > Funding: Whitney R. Robinson is supported by the National Institute of Minority Health I am not familiar with standards of conflict declaration, but this looks like a pretty clear conflict of interest to me.
jkingsbery 7y ago
"Conflict of Interest: None declared." In an article about structural racism, I would have expected more here.
- eranima 7y ago
  A bias is not the same thing as a conflict of interest.
corporate_shi11 7y ago
People of every race find success in technology and in America more broadly. Many of these people's ancestors came to America with nothing. Those groups which find more success than average generally have a cultural focus on education and other behaviors associated with responsible action. Groups that don't succeed generally do not share these qualities. It is these cultural differences which cause most of the group disparity in America, not "structural racism", yet the "critical race theorists" (race hustlers and grievance mongers) and their followers ignore these major factors and replace them with straw men. In order to fix a problem, it's important to understand the actual causes. The sociologists and other assorted race hustlers will only divide us and lead us astray.
whatismypass 7y ago
This post was on the front page 10 minutes ago but now it can't be found anywhere. It's pretty disappointing that it has been removed solely on the basis of being about race or being controversial. Race and racism are a part of society and it presumably made it to the front page because it's a topic that enough people found interesting to vote for...so why remove it?
- Digit-Al 7y ago
  It hasn't been removed. I can see it at position 43 at the moment, but it is showing as flagged for some reason.
ThrustVectoring 7y ago
The real problem is that there are mutually exclusive desiderata from your models. 1. If you have two people with identical relevant behavior and different races, you want the model to score them identically. 2. Each race should receive a comparable distribution of scores. 3. The scores should be as accurate of a predictor of ground facts as possible. Relax the first desiderata and your model is now either explicitly or implicitly (via irrelevant proxy variables) using race to determine results, opening you up to racial discrimination lawsuits. Relax the second desiderata and your model is now creating disparate impact across racial groups, opening you up to racial discrimination lawsuit. Relax the third and you're leaving accuracy, and thus money, on the table.
dublin 7y ago
Disparate impact of results is NOT proof of racism. People are complicated - and some racial correlations are perfectly valid - at least until enough members of a racial group decide to change them...

47 points by joker3 7y ago

The definition for structural racism according to the article: > Structural racism refers to “the totality of ways in which societies foster [racial] discrimination, via mutually reinforcing [inequitable] systems...(e.g., in housing, education, employment, earnings, benefits, credit, media, health care, criminal justice, etc.) that in turn reinforce discriminatory beliefs, values, and distribution of resources,” reflected in history, culture, and interconnected institutions (Bailey and others, 2017). I think I might be misunderstanding, but given this includes “culture”, is this so sufficiently broad such that hypothetical scenarios such as this (no idea if this is accurate) would be captured “white people are culturally more likely to use crystal meth than other racial groups, ergo they are victims of (a certain kind of) systemic racism”? It seems like this is just a catchall for any kind of error associated with a racial group, and the article is merely cautioning against such errors. If so, it begs the questions “why not just say so?” and “why use such a loaded term like systemic racism?”.

LegitShady 7y ago
Modern sociology in no way resembles a scientific study and is heavily politicized. A bunch of nonsense political "researchers" citing each other in drivel papers desperate for relevance. It's now leaking into other fields. I remember when I first heard stem be changed to steam to include "arts" a laughed at how inclusive and utterly useless it is.
- travisoneill1 7y ago
  They even make up math. I had a sociology prof in college teach us that to mathematically determine that there is a difference between groups, the difference between the means had to be greater than the range in either group (not even any reference to sample size). I replied that by this test you couldn't even determine that there is a height difference between men and women, and the prof said that in fact you can't and that it was a good example of this test.
  - bransonf 7y ago
    That professor was wrong or your understanding is. There are plenty of statistically viable ways to determine differences between groups. Even a simple T-test is usually sufficient. The difference of means does not have to be more than the range in either group. Standard deviation is what’s important here. You use a test statistic to determine the relative value of the real mean within a confidence interval. It’s whether these intervals overlap that you can determine a significant difference between groups.
    - travisoneill1 7y ago
      I know that the professor was wrong. That was the point of the comment. That a professor in a so called science class could get the math so comically wrong.
- pvarangot 7y ago
  Postmodern sociology is revisionist towards trying to see society only through a lens that is also easily probable to be statistically sound, this is because of how more quantitative socioeconomic theories failed to predict very big crises or events in society. It can be argued that asking for scientific rigor in sociology to the same extent as in other human sciences raises the bar too much because to validate some theories the experiments are either impossible, prohibitively expensive, or so massive that they would bias the whole of society. Also, I think it would marvel you knowing how much things you would call "scientific study" are also heavily politicized. If this bothers you to a big extent I would recommend you try to find comfort in thinking about postmodern sociology as a religion different than yours. They won't be bothered by it and it will probably fit your mindset in a more soothing way than thinking about them as scientists. It's not that they are trying to publish their findings in ACM TOPLAS or something, they have their own community and books and kinda like it.
  - LegitShady 7y ago
    If it was treated as religion instead is science I would be open to that, but the papers churned out by "experts" today become policy tomorrow that effect everyone.
    - pvarangot 7y ago
      Religions dictate and have been dictating policy since forever we had governments and even before that. It's what people understand and mostly everyone seems to be ok with it.
  - weberc2 7y ago
    I do think of it as a religion—one that is state sponsored and masquerades as science.
- roflc0ptic 7y ago
  Sociology is way more rigorous than you’re making it out to be. Studying people is hard, but it’s making good faith effort in that direction, reproducibility crisis notwithstanding. Take the “Sokal 2.0” affair, where some profs sent obviously bogus research to various journals. Notably, while they were able to get “rape culture among dogs at the dog park” (or maybe it was racism, easy to look up) published in a gender studies journal, they couldn’t get published in sociology journals. Sociology has standards. The absurdities committed by gender studies as an institution don’t falsify racism/other forms of oppression. They might be wrong, but you’re certainly not right.
  - LegitShady 7y ago
    >Sociology has standards. Mostly political and much of it unreproducible. Desperate political academics using non science to argue their opinions and right and citing each other into fake legitimacy. Garbage studies garbage standards garbage journals from people who couldn't hack it elsewhere.
- dang 7y ago
  Please don't take HN threads on generic ideological tangents. They are boring and repetitive and therefore off topic here. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
  - LegitShady 7y ago
    It wasnt an unrelated tangent. It's directly related to the drivel in op.
    - dang 7y ago
      Tangents are always related at some point. The problem is not where they start, but what they lead to. If they start from drivel but lead to hotter drivel, like internet ideology wars, HN gets much worse. Please just avoid generic ideological battle here.
      - LegitShady 7y ago
        Fair enough, although I think it's unavoidable when you're talking about what I think to be essentially made up terms.
        weberc2 7y ago
        It is odd that your comment was “ideological battle” but not the original article. I guess the original was sufficiently jargon-laden.
hellllllllooo 7y ago
Expected comments minimizing the article on HN and was not disappointed. Why is it that so many people here find it so hard to accept that there is an actual issue with systematic racial bias with what-abouting it or diluting it to nothing? There's definitely an issue in Silicon Valley and tech but maybe people find it hard to acknowledge because it means admitting some culpability or taking some responsibility.
whatismypass 7y ago
It's talking specifically about racial discrimination that results from <long list of interrelated things>. I don't think that means "any kind of error" and I don't think white people are racially discriminated against for having higher meth usage.
- weberc2 7y ago
  You really misunderstood me. I didn’t claim anything about white people; I gave a hypothetical scenario. And that hypothetical scenario wasn’t about white people facing discrimination for higher meth usage, only that such an inequitable distribution of meth usage seems to satisfy TFA’s definition for structural racism. The fact that it seems implausible to say so suggests the definition is not especially useful.
Enginerrrd 7y ago
There are some very real effects that need to be acknowledged in order to design a good system. Here's a hypothetical example I gave in a similar thread here a few months back. It's loosely based (Though not too far removed from reality!) on some real-world systems that failed to address this: Suppose you are designing a facial recognition system for police to use in the field while investigating a recent crime to see if anyone with a criminal history is nearby. (Data taken from: https://en.wikipedia.org/wiki/Incarceration_in_the_United_States#Ethnicity https://en.wikipedia.org/wiki/Incarceration_in_the_United_St...) Because blacks are over-represented in the US criminal justice system (40% of the prison population vs 13% of the population) and because part of what defines "black" is the outward appearance of certain facial features, a facial-recognition algorithm which is trained to recognize criminals, with a cost function based on prediction accuracy alone, and facial features as input parameters is likely going to have false positives that over-represent blacks. It's very important to consider this when you develop a training set. The developer error (who mostly failed to understand Baye's theorem here) might work something like this: They take 100 innocent people's faces at random. (On average it will have only 13 blacks) Then take 100 random criminal faces from inmates. (On average it will have 40 blacks.) Then mix up the groups into your training set and assign a prediction score 1 or 0 depending on whether or not your classifier has correctly predicted whether or not a face was in the criminal group. Then, based on no other feature than race, your neural net can get better performance based solely on guessing more often that black people are criminals. That's not a good thing. In fact, if it's looking at a black face from its training set, the odds are nearly 2 to 1 that it's one of the criminals, even though the odds that are at least 2 to 1 against a random black person having a criminal history. The likelihood of being falsely identified as having a criminal history is much greater based on the only variable of being black. And this type of thing has happened several times already in production systems! Conversely, the same system, trained on the same data in the same training set, can get higher performance than random by simply guessing that any non-hispanic white person does NOT have a criminal history. Thus, it's pretty important to correct your training set to reflect the correct Bayesian prior, and the underlying structures that sometimes go by the label "structural racism" or "institutional racism" are essentially exactly that reality in this case.
- hello_marmalade 7y ago

opwieurposiu 7y ago

This paper fails to account for (or even mention) genetics. To expand on the breathing capacity example, consider the case of the sherpas. https://www.npr.org/sections/goatsandsoda/2017/05/28/530204187/the-science-behind-the-super-abilities-of-sherpas https://www.npr.org/sections/goatsandsoda/2017/05/28/5302041...

ralusek 7y ago

I think beyond not feeding race in as a feature to any model, this stuff is mostly nonsense. If you include race as a feature, then I think it's likely that the model will become racist, because race is so highly correlated to behaviors and patterns which are in large part the consequence of all sorts of things, including historical racism, that a model could easily mistake race as a causal factor. If you don't feed race in as a feature, however, the outputs are hardly racist. My impression has been that by and large the argument actually being made is that "we have been trying to correct for historical injustices by actively using race and gender as mechanisms for advantaging minorities and women, and an unbiased model is not properly accounting for these particular objectives." Take something like a bank loan. If you had a model at a bank which took credit score, income, wealth, and collateral into account, black Americans would have loans rejected at a higher rate than white Americans. Is this model racist? No, this model doesn't even know what race is, all it knows is credit scores, income, wealth, and collateral. Does the fact that black Americans used to be slaves in the US, or were kept out of certain housing markets, contribute towards the fact that black Americans, on average, have lower credit scores, income, wealth, and collateral? Of course. But is this model racist? Literally not at all. It is completely unbiased, and exactly what the model should be. If the case you're making is that you think that there should be a national effort to correct for historical injustices that were done by the state by actively discriminating by race, that is a completely different discussion. Having all of our decision-making apparatuses factor in the infinite pile of historical injustices that may have contributed to an individual's particular circumstances is not the way to go. Keep models simple and limited to what is relevant for that particular criteria. Fix injustices further upstream, or you make the whole system a convoluted nightmare.

zbyte64 7y ago
The article mentions why simply excluding race isn't good enough: "Crucially, incorporating more proximal and predictive variables into models, rather than relying on race variables to act as proxies, will improve transportability of algorithms across contexts." If we want better models then they need to also model structural racism.
abdullahkhalids 7y ago

bransonf 7y ago

I did research briefly in a lab studying heart rate variability. HRV is a really interesting statistic in predicting heart health outcomes, and very interesting is the racial difference in HRV. Basically, African Americans exhibit much higher heart rate variability, meaning their nervous system is much quicker to react to stimuli (quicker time to fight or flight response, for example) and this still isn’t well understood in the field. A naive understanding is that racial physiology is just different. And plenty of people will stand by this. However, self reported stress scores offer some insight into the difference. High stress African Americans with High HRV lived as long as Low stress, low HRV White/Asian Americans. Most likely, the process by which the nervous system regulates itself is heavily influenced by life course events. Medical science, in my experience, lacks in quantifying these social factors, and too often underplays their significance in determining physiological differences. Humans are incredibly dynamic systems, and the case can be made that we adapt to stimuli in order to survive. It’s certainly possible that the physiological difference we observe in different racial populations is due to survival based on this principal. It’s only recently that I’ve seen research trying to get at these social/physiological mechanisms, but as far as funding is concerned, hard biological sciences are more interesting. Everyone just wants to edit the genome and call it a day, but I think we could get much further if we understood how life events lead to physiological ailments later in life.

sansnomme 7y ago
There is also the political implications. Nobody wants to fund research which will only stir up controversy, especially since many higher education institutions are located in liberal areas. Too many medical studies on gender, race, and intelligence would only create unrest. Just take a look at how badly the Stanford ML paper on predicting gender orientation was received. Emphasizing the differences in "fight or flight" response timings may save lives, but at the same time provide ammunition for people to draw lines between metrics and historical events/practices along societal fault lines, which I think everyone can agree is not a good thing.
- ramblerman 7y ago
  > provide ammunition for people to draw lines between metrics and historical events/practices along societal fault lines, which I think everyone can agree is not a good thing. Putting your head in the sand and trying to deny the existence of potentially uncomfortable facts actually fuels these fringe thinkers more imo. Part of their whole schtick is that the truth is being hidden from them. Look at how the media handled the claim that Serena Williams couldn't beat a top 10 male player. Instead of actually putting it to the test, the whole angle was about how insulting and preposterous that was etc etc. We are not all the same, but we deserve to be treated so. It's as simple as that. Trying to halt scientific progress because it doesn't fit your world view is quasi religious.

kryogen1c 7y ago

> 4. Conclusion "...grounding one’s work in an understanding of structural racism will improve model accuracy..." It is not an interesting result to say models not modeling reality are less accurate; the cogent discussion is to what degree systemic racism exists IN reality. This is textbook begging the question. > Acknowledgements: Conflict of Interest: None declared. > Funding: Whitney R. Robinson is supported by the National Institute of Minority Health I am not familiar with standards of conflict declaration, but this looks like a pretty clear conflict of interest to me.

jkingsbery 7y ago

"Conflict of Interest: None declared." In an article about structural racism, I would have expected more here.

eranima 7y ago
A bias is not the same thing as a conflict of interest.

corporate_shi11 7y ago

People of every race find success in technology and in America more broadly. Many of these people's ancestors came to America with nothing. Those groups which find more success than average generally have a cultural focus on education and other behaviors associated with responsible action. Groups that don't succeed generally do not share these qualities. It is these cultural differences which cause most of the group disparity in America, not "structural racism", yet the "critical race theorists" (race hustlers and grievance mongers) and their followers ignore these major factors and replace them with straw men. In order to fix a problem, it's important to understand the actual causes. The sociologists and other assorted race hustlers will only divide us and lead us astray.

whatismypass 7y ago

This post was on the front page 10 minutes ago but now it can't be found anywhere. It's pretty disappointing that it has been removed solely on the basis of being about race or being controversial. Race and racism are a part of society and it presumably made it to the front page because it's a topic that enough people found interesting to vote for...so why remove it?

Digit-Al 7y ago
It hasn't been removed. I can see it at position 43 at the moment, but it is showing as flagged for some reason.

ThrustVectoring 7y ago

The real problem is that there are mutually exclusive desiderata from your models. 1. If you have two people with identical relevant behavior and different races, you want the model to score them identically. 2. Each race should receive a comparable distribution of scores. 3. The scores should be as accurate of a predictor of ground facts as possible. Relax the first desiderata and your model is now either explicitly or implicitly (via irrelevant proxy variables) using race to determine results, opening you up to racial discrimination lawsuits. Relax the second desiderata and your model is now creating disparate impact across racial groups, opening you up to racial discrimination lawsuit. Relax the third and you're leaving accuracy, and thus money, on the table.

dublin 7y ago

Disparate impact of results is NOT proof of racism. People are complicated - and some racial correlations are perfectly valid - at least until enough members of a racial group decide to change them...