Google Has a Striking History of Bias Against Black Girls - <AUTHOR> http://time.com/5209144/google-search-engine-algorithm-bias-racism/ <comment><USER2> All: we're aware that this article may have an ideological slant that is either positive or negative depending on your own views, but it also has interesting content. Please react to the factual information and steer well clear of any ideological yay-nay combat.

</comment><comment><USER3> I think the thesis is wrong here. Google has a striking history of removing bias against black women.

People make content for the web. People are racist, and make lots of racist assumptions in their writing. Society is racist. This results in Google's algorithms reflecting the corpus they scanned, and the searches that are made. But the search is just a reflection of us, and how terrible we all are.

Google gets embarrassed by the results, and exercises editorial control over search -- which leads to them actively removing racist systemic biases. Sure it's reactive and not proactive, but it's movement in a positive direction. Google likely spends more money on editorial control for issues of racism than for any other thing that doesn't make money.

<comment><USER4> I agree that there's too much blame-the-algorithm sentiment here, but if I had to guess, I'd think the author would argue that these racist biases should and could have been caught before going into production -- i.e. it doesn't have to be an inevitable cycle of ad hoc public shaming and repentance. These biases could be identified just as other SERP problems are identified before each algorithm update.

Just like the HP "racist" webcams [0] might have been caught had the CV trainers been more aware of what is/isn't in the training data, and/or if HP had a few more testers of darker complexion.

And perhaps Facebook's "Year in Review" rare tendency to be "cruel" [1] would have been mitigated with a broader group of devs and testers.

[0] [http://www.cnn.com/2009/TECH/12/22/hp.webcams/index.html](http://www.cnn.com/2009/TECH/12/22/hp.webcams/index.html)

[1] [https://meyerweb.com/eric/thoughts/2014/12/24/inadvertent- al...](https://meyerweb.com/eric/thoughts/2014/12/24/inadvertent-algorithmic- cruelty/)

<comment><USER5> > I'd think the author would argue that these racist biases should and could > have been caught before going into production

I think people who believe this significantly underestimate the difficulty of solving these problems.

<comment><USER4> I think that's likely. But the people tasked to solve these problems aren't always given the right priorities. Detecting/classifying the faces of dark- skinned humans is inextricably more complicated than it is with light-skinned humans. It requires significantly more training data, more computational power, and more testing time to reach the same accuracy as a light-skin-only camera and classifier.

We would deride Uber's self-driving vehicles if it turns out their systems can't tell the difference between harmless (plastic bags) and dangerous (jaywalkers, wildlife) objects on the road. Likewise, we can judge a company for releasing a general consumer webcam that fails to fully function for 10-15% of the American population.

<comment><USER6> >Likewise, we can judge a company for releasing a general consumer webcam that fails to fully function for 10-15% of the American population.

But then you get into an even deeper question 'are minorities/blacks 10% of said consumers of products?'. Poverty, for example, could mean that the product doesn't work for 5% of the buyers, which then begs the question 'how much effort do you put in fixing the problem for a small percentage of the buyers?', especially when the amount of effort is going to be very large/time consuming/expensive. If you are a person looking for racism, you will judge google as racist. If you are looking at it from a position of a business attempting to make a profit on a product, you will not see it as racist.

<comment><USER7> > But then you get into an even deeper question 'are minorities/blacks 10% of > said consumers of products?'.

Maybe run that question by legal first! Protected classes exist for a good reason (IMO). What percentage of a restaurant's business is from people in wheelchairs, yet the law mandates ramp access.

</comment></comment></comment></comment></comment></comment><comment><USER8> This is a much harder problem that it looks to a casual observer. Just imagine what kind of people would type "black girls" to Google search. Not "black girls outfit", not "black girls social bias", just "black girls".

I'll bet at least 50% of the searchers are looking for porn.

So even if Google had infinite resources, its choices are: (1) act as a moral authority and deny pornographic contents to those who are looking for them, or (2) show pornographic results to people searching for innocent stuff.

...Or maybe (3) built a perfect profile of every user and just show them what they want. But do we want to go there?

(You might be thinking that "black girls" is such an innocent term that Google should be able to determine that it's non-porn, but then the question merely shifts to less popular queries.)

<comment><USER9> I wish the article had included screen shots of search results for "white girls" and "Asian girls".

Would there be any less porn? I strongly doubt it.

<comment><USER10> "white girls" returns stuff about the movie white girl

"Girls" is the HBO show

"Asian girls" is porn lite

"Black girls" has no porn for me. Various sites about black girls (black girls code for example)

<comment><USER11> It depends on your search history, actually.

I tried "black girls", "white girls", "asian girls" \- and also "asian boys" etc. - in various accounts, some of which were used when browsing porn (i.e., home accounts vs accounts used at work), and in both google and bing.

In accounts where porn was browsed in the past, porn results were over 50% for all of the above. In others, porn was absent.

<comment><USER12> Excellent research! You should post this as a root comment so it has a chance of rising to the top.

</comment></comment></comment></comment></comment><comment><USER13> Machine learning systems are good at finding the unconscious biases of large populations. Any change to force notions of political correctness on top of that is very complicated, and makes the algorithm work worse for its intended purpose. Literally, failing to accept the discrimination inherent in the data loses you money directly or indirectly.

This is well-known, and not Google's fault. Getting offended at Google for a reality they didn't create and can't control seems silly to me. If you don't like the result, work to change the incentives. Or work to change people's biases.

This kind of problem is not new. For example insurance companies have long known that where you live affects how much they are likely to pay out. If they base insurance rates on the data, the result is that your zip code becomes a bigger determinant of insurance rates than your driving record. Which results in very large effective racial discrimination. There are laws limiting that, for example prop 109 in California. However it is an eternal struggle because, in fact, competing insurance companies have a good motivation to have the cost of insurance reflect their best estimate of the expected cost of insuring you, and their cost really is a lot higher if you're in a "black neighborhood".

</comment><comment><USER14> I'm always amazed how often the "surprise" that digital technology is in fact not unbiased and robotic in nature keeps getting written about. Algorithms that optimize for click through rate for ads and search relevancy will inevitably be a reflection of ourselves and all of the shitty things various people believe.

>> What we know about Google's responses to racial stereotyping in its products is that it typically denies responsibility or intent to harm, but then it is able to "tweak" or "fix" these aberrations or "glitches" in its systems.

Only Google knows the fate of the code base that has workarounds for all of these edge cases. I think the author is wrong that all of these edge cases could've been caught beforehand. Some sure, but I think others would always slip through.

<comment><USER15> > I'm always amazed how often the "surprise" that digital technology is in > fact not unbiased and robotic in nature keeps getting written about. > Algorithms that optimize for click through rate for ads and search relevancy > will inevitably be a reflection of ourselves and all of the shitty things > various people believe.

What you just observed and described is that technology _is_ unbiased and robotic. The bias is in the humans. You can't remove it with a software bandage; the software is working as intended.

<comment><USER16> > What you just observed and described is that technology _is_ unbiased and > robotic.

Just to get calibrated: what is an example-- real or imagined-- of technology that _is_ biased?

<comment><USER17> For example, a search algorithm with an override that removes all links of sexual nature for certain hardcoded queries (say, "black girls") could be an example of a biased technology.

If I'd have to make a definition, then it would probably be a technology that somehow encodes an assumption that doesn't match reality. In this context, saying that "black girls" is an innocent search term and users searching for it don't expect to get sexual results is such an assumption - it would be polite, politically correct and possibly socially desirable; but it seems likely this is simply not true in the reality we live in.

<comment><USER18> I had a person on my team preparing a presentation and for whatever (reasonable) reason was looking for a stock image of a rabbit in winter with frozen precipitation around.

Just as our (very straight laced) CIO walked up behind, employee hit image search on "snow bunny". Hilarity ensued...

</comment></comment></comment></comment></comment><comment><USER19> It seems like the main crux of the argument is that being reflective of the culture is also reinforcing it - the fact that say there aren't as many stock photos of 3 black teens while there is a lot more "mug shot" style photos is probably reflective of the usual portrayal in media, but most people generally agree that the culture shouldn't be that way.

The question is, should search algorithms show what currently is (and therefore reinforce what is), or what the culture aspires to (which in fact more accurately matches the culture in terms of desire and movement)? I think this is a pretty smart example of how the technology we use every day can be passively malevolent - creating hurdles for change rather than enabling better information transfer.

<comment><USER20> > should search algorithms show

radical thought (and goes for social media as well) -

how about making the results tunable based on user preferences & filters?

oooh wow.. user control! what a concept..

<comment><USER19> I think that might make for a more powerful and useful search engine for sure. A Universal perspective as we've seen over the past few years simply doesn't exist - a search engine equivalent of stating a perspective would be interesting to think about. We already have location-based services, but we don't have cultural perspective based services. News media (Huffpost, Gawker etc) seem to be filling this role but only for news.

</comment></comment></comment><comment><USER21> > Images of white Americans are persistently held up in Google's images and in > its results to reinforce the superiority and mainstream acceptability of > whiteness as the default "good" to which all others are made invisible.

I think that implying intent on Google's part is going way too far.

Obviously search results, to a large extent, are going to reflect the society and culture of search engine users. If our society and culture are shitty, should search results pretend otherwise? I'm pretty sure that our society and culture are rife with institutionalized racism and sexism and a whole lot of other badness, and badness of search results seems to me to be a symptom rather than a cause.

</comment><comment><USER22> I like the underlying question that the author brings up - what's google algorithm, and who's responsible for it?

In the old days it was "most linked page with those keywords," right? So if you searched "gay man" and got a bunch of gay porn, is it necessarily google's fault that the internet is more gay porn that it is resources for gay men to discuss LGBT issues? Is it google's fault that news agencies more typically report on crime by black people than white (or that black people are more likely to be convinced/arrested in the first place?)

I think Google _is_ responsible in 2018, now that they offer extremely tailored results. Duckduckgo, maybe not. But if Google is going to say "we're going to show you listings for restaurants in SF in your simple 'restaurants' search because we know you live in SF," I think they should also say "we're going to show you results for LGBT resources when you search for 'gay men' because nothing about your query indicates a desire for pornographic content."

<comment><USER23> >I think Google is responsible in 2018, now that they offer extremely tailored results. Duckduckgo, maybe not. But if Google is going to say "we're going to show you listings for restaurants in SF in your simple 'restaurants' search because we know you live in SF," I think they should also say "we're going to show you results for LGBT resources when you search for 'gay men' because nothing about your query indicates a desire for pornographic content."

Are you are saying that, in a scenario where there are more results for one sub-query than for another, Google has an obligation to assume someone is searching for the sub-query it finds more politically acceptable? This seems like a bad idea to me. We should want to _reduce_ the political/social influence of Google, rather than think of ways to give them more tools of influence and assuming they will have a positive effect.

These two things are completely different

"Because you live in SF, if you search restaurants you probably want results pertaining to restaurants close to SF"

"Because subject X-A is socially unacceptable, if you search for subject X we will only show results pertaining to subject X-B"

<comment><USER24> Political correctness and affirmative action are based on the idea that pretending the world is an ideal version of itself will eventually make it that way.

In reality though, the world is a complex place and the ideal pretend version can only be implemented in a carefully controlled environment such as a movie, a theatrical presentation, a video game or a situation where all participants agree to or are pressured into behaving in a way in which that pretend world is real. When the rest of the world leaks in, it is impossible to maintain that pressure on everyone.

About the best we have so far is "safe search" since pornography and obscenity follow fairly regular patterns. Political correctness though is constantly evolving and requires a trained academic to determine if each piece of information should be censored or allowed. Ideally in the future we'll have google glass and advanced AI classifiers constantly scanning our vision and providing us with tape delayed audio of the outside world in order to present the world to us and filter any politically incorrect content 24/7.

For now we have to do it ourselves and ignore any inconvenient facts that may make maintaining the illusion difficult. This constant struggle to deal with cognitive dissonance can be tiresome and one should restrict oneself to heavily moderated news feeds and not using search features for now. To create the carefully controlled virtual world in an interface to the rest of the world such as Google is an overwhelming task because you would need a highly sophisticated trained AI agent to maintain that illusion and to even invent information, such as lists of Nobel award winners from disadvantaged peoples, in order to maintain the illusion.

<comment><USER25> >Political correctness and affirmative action are based on the idea that pretending the world is an ideal version of itself will eventually make it that way.

That is the opposite of how it works. Affirmative action is accepting that the world has bias against certain groups, and attempting to take that into account. Political correctness is about realizing that certain groups have been marginalized or traumatized and some words perpetuate that. In a perfect world neither are necessary.

<comment><USER24> The proof that a group has been marginalized is that their numbers are not representative of their presence in the population. Thus, we pretend that the ideal world exists by adjusting those numbers in situations where merit selection is the criteria in the hopes that the numbers will converge by themselves. We don't interview each participant to ask them how they were traumatized, we only look at the statistics. People from strong well adjusted minority families that value education and have protected their kids from most of the harsh realities that poor minority families are subject to receive the same special treatment with affirmative action. The reason that the inequity exists is immaterial means that we don't even have to check if a bias exists, we just assume that since the world is not ideal that the numbers need to be fixed first and then the rest of it will follow.

At least that's the way it works in reality. Maybe this reality is politically incorrect too and you are saying that we need to implement meta-political correctness in which the means of creating an ideal world must be hidden to instead pretend that the implementers know the exact and particular circumstance of each person they are selecting based on facts other than merit and are weighing all of them appropriately in correcting injustice. By pretending that this ideal world in which knowledgeable administrators skillfully and in each individual case correct injustices, this will somehow make it become a reality.

<comment><USER26> [https://www.theatlantic.com/education/archive/2017/08/why- me...](https://www.theatlantic.com/education/archive/2017/08/why-men-are-the- new-college-minority/536103/)

Statistics show that man are the new minority in the campus. But it is surely will be frown upon by some AA activists if a that program is extended to cover male. If AA is said to what it is trying to accomplish, then that shouldn't be controversial at all.

<comment><USER22> >But it is surely will be frown upon

I think this is presumptuous. We can try to find out, why not?

</comment></comment></comment></comment></comment></comment></comment><comment><USER27> Google search results reflect what's in use on the web via PageRank and modern PageRank-like approximations. Google and its human staff does not apply human intellect to the problem of sorting, picking, and ranking each search result. Moreover, Google has included "Safe Search" features for several years that would remove these types of results from search.

Before we condemn Google for the collective actions of the broader Internet community of websites, we should take a moment to understand this point.

Now, it is possible to create a search engine curated by humans or filters that remove objectionable content, and perhaps that approach might be desirable to some - a "MyGoogle" experience with search results customized based on Google's interpretation (or explicit settings) of the visitor's demographics, political beliefs, trigger words, and purchase history.

<comment><USER28> > Google search results reflect what's in use on the web via PageRank and > modern PageRank-like approximations.

PageRank is only a fraction of the total inputs to Google search. Once PageRank was described it was subject to being gamed at such a scale that it essentially destroyed the web, ironically making Google that much more a necessity.

> Google and its human staff does not apply human intellect to the problem of > sorting, picking, and ranking each search result.

Yes they do. By tweaking the weights of certain output categories (such as evidenced in the article, a clear drop in the number of pornographic or semi pornographic results as a result of such a tweak) there is a large amount of influence exerted on the results.

> Moreover, Google has included "Safe Search" features for several years that > would remove these types of results from search.

Safe search always was a weird one: You'd expect the opposite, a 'smut search' (Tom Lehrer would have a field day with that one).

> Before we condemn Google for the collective actions of the broader Internet > community of websites (and the author's step of disabling Safe Search), we > should take a moment to understand this point.

Before we invalidate the authors point by handwaving and purposefully injecting chaff into the conversation let's try to understand the actual point they are trying to make: That a query for an innocent term such as 'black girls' even with 'safe search off' should not result in a bunch of porn.

> Now, it is possible to create a search engine curated by humans or filters > that remove objectionable content, and perhaps that approach might be > desirable to some - a "MyGoogle" experience with search results customized > based on Google's interpretation (or explicit settings) of the author's > demographics, political beliefs, trigger words, and purchase history.

That's nothing to do with the authors point.

<comment><USER27> > That a query for an innocent term...

I take strong issue with the "obvious" conclusion that Google knows which terms are innocent. Disclaimer: In this specific case, I agree with you that "black girls" has an innocent connotation and am not suggesting otherwise. Please do not misinterpret my thoughts below.

Shall we require Google to be ever vigilant about the meaning of words in use at various times by the various communities of the world, and to entrust them with the responsibility for determining the innocence or guiltiness of words or phrases for all mankind?

If we shall require such effort of Google, ought we not elevate Google to the role of judge over other matters of humankind given their good stewardship over matters of innocence and guilt?

Taken to the limit the argument advocates the establishment of an echo chamber to wrap tightly around each one's subjective interpretation of their reality. Isn't this the exact opposite of what we should be trying to achieve?

Have we not had enough of this Brave New World?

<comment><USER28> > Shall we require Google to be ever vigilant about the meaning of words in > use at various times by the various communities of the world, and to entrust > them with the responsibility for determining the innocence or guiltiness of > words or phrases for all mankind?

Google aims to 'organize the worlds information', how it does that concerns all of us so yes, this makes them responsible with determining whether a certain set of words has an innocent or negative interpretation.

It's not the world I want to live in but I live in it nonetheless. That Google should not have this power to begin with is obvious but here we are.

> If we shall require such effort of Google, ought we not elevate Google to > the role of judge over other matters of humankind given their good > stewardship over matters of innocence and guilt?

Definitely not, why make things even worse? They already have _too much_ power we will not make things better by compounding the problem.

> Taken to the limit the argument advocates the establishment of an echo > chamber to wrap tightly around each one's subjective interpretation of their > reality. Isn't this the exact opposite of what we should be trying to > achieve?

It is, but again, the filter bubble is real and the more customized Google search results are for an individual the worse this gets.

> Have we not had enough of this Brave New World?

I do, and so does the author, but clearly you are either missing the point or you have not had enough yet.

<comment><USER27> You're right! I reread the article, and the author aligns ideologically with most of the commenters in this thread, including myself.

</comment></comment></comment></comment></comment><comment><USER29> I tried replicating the searches described in this article, in an incognito window. Most of the searches described inthe article are quite dated; they're also spread over a significant amount of time. None of the searches I tried came out the way the article described. There was no porn in the results for "black girls"; the third result for "professor style" was a black man, and there was a black woman further down on the first page. Search results for "three white teenagers", "three black teenagers", "professional hairstyles for work" and "unprofessional hairstyles for work" were dominated by links to the very discussion this article is reporting on, which sort of suggests they weren't queries anyone was making to begin with.

<comment><USER30> How do you know the algo/search results weren't tweaked after these critiques went public but before your tests?

<comment><USER31> Obviously they were. The point the parent post is making is that some of these results are old (like, 10 years old). Of course the algo would have changed, and the article even says that it did.

But if no one is searching it, then of course it's just going to be semi- random results.

[https://trends.google.com/trends/explore?geo=US&q=%22three%2...](https://trends.google.com/trends/explore?geo=US&q=%22three%20black%20teenagers%22)

The top related query? "Three white teenagers". It's obvious almost no one searches this term unless they've read the article.

</comment></comment></comment><comment><USER32> What I took from the article were a few points:

* Taking a neutral position when building something (its just a tool, it's making decisions based on an aggregate) IS in fact making a decision. State can be -1, 0, or 1 and neutrality yields a certain result.

* The local optima of these algorithms are likely a product of local optima to the people and teams who built them. The neutral position seemed like the correct answer.

* These articles serve to reinforce the idea that the next frontier is context within algorithmic results. This global optimum can only be achieved through diversity of perspective. Perspectives are a product of one's experience, so the value of diversity can be directly connected to the goal of desiring a optimum solution towards a hard problem.

FWIW, I am a black heterosexual engineer and my experiences inform my perspective on these type of problems and blindspots affecting people not like me, especially women.

For those wanting to go deeper on the technical, scientific, and mathematical basis for what I'm referring, google 'diversity local optima'.

<comment><USER33> My takeaway was that algorithmic solutions alone will never be enough since they operate at the core on user intent.

Males searching for "FOOBAR girls" have, on average, different intent than women. If they represent the majority of searches, algorithms will naturally weigh the results they click more highly.

Hyper personalization is seen as an answer, but comes with the downside of a reinforcing bubble and drift to extremes. Human intervention and editing are only a partial solution, bringing up further questions about censorship and which ideology is correct.

No easy answers to all of this.

</comment></comment><comment><USER34> What did she expect for "professor style"? If I were hand-delivering results and knew it was from a black, asian, or white person in the US, why would I return different results? Someone entering a general query like that probably wants what the common interpretation is. Which is not going to be a black professor. Searching "professor style for black women" returns the results she presumably thinks should be the default for her.

As much as I hate Google, they seem to be delivering exactly what they should. Their job isn't to try to change people's minds, it is to find what they are looking for. What's next? Search for "geek guy" and it's all white. Should we be upset? Someone searching for "geek guy" is probably looking for exactly what Google returns in this case and all the others she highlights.

As far as "black girls"... What kind of results are people expecting? Who is actually searching for black girls? Probably people looking for porn... Why should Google return suboptimal results because you got offended?

Same for "three black teens". It's not Google's fault that so much news is reporting on crime committed containing that phrase. Did she actually check crime statistics? Maybe "three black teens" get mugshots and commit crimes together at a vastly higher rate than "three white teens". Outside of porn, who is searching for this phrase? If you want "clean" and friendly results, try searching "stock photo three black teens".

If anything, this article shows that Google's personalization should detect people that want to search things (that they wouldn't really search for in earnest) in order to be offended then display poor quality results to avoid this "issue".

In truth though, I would imagine that if she and other black women often searched "professor style" then didn't click any results and immediately searched for "professor style for black women" then Google would pick up on their results being suboptimal and change. My guess is that no one actually makes these searches outside of making a political point, so personalization cannot fix it.

</comment><comment><USER4> It's always bothered me when people, (justifiably) frustrated with the bubble effect that personalization can effect upon search results, want to see Google return to "objective" results. But PageRank/BackRub was never an objective metric, it was always affected by what webmasters chose to link to and the semantic markup they wrote. It seemed to be a good metric for a majority of these things, but assuming few webmasters in the early years were black women or black, then the "objective" metric of PageRank/BackRub is going to be dismal.

So yes, I agree that more pressure needs to be put on the algorithm-makers, so that there isn't complacency about accepting the results of "pure" computation. But I feel too much weight is given toward the sentiment of " _If Google isn't responsible for its algorithm, then who is?_ ", as if the problems could be wholly or even substantially fixed through "modifications to its algorithm". The other side of the equation is the _data_ \-- and diversity is as important to have in media as it is to tech, even if tech feels like the stronger, more immediate lever in changing things.

Now that it's been a long time (in tech time) since 2010/2012, it'd be interesting to hear exactly what modifications/improvements Google made to its algorithm to return such different results for "black girls". Was it a de- emphasizing of negative/outdated sources? Or an arbitrary boost for such entities as "Black Girls Code"? Or was BGC not given an arbitrary boost, but found to have been unjustly ignored/under-weighted when it came to determining SERP? I understand not wanting to reveal details of search engine tweaks the day/month/year after they've been implemented. But half a decade later, hopefully learning more details of these "tweaks" won't leave Google vulnerable to black-hat SEO.

</comment><comment><USER35> Try searching Google Images for "brazilian".

Her point is quite valid, and also well recognized in at least some part of the tech industry: when you "blindly" optimize for a certain audience, you risk picking up the biases of that audience.

So, if you want to appeal to a broader audience than your current one, you might need to manually tune your system to remove some of the biases from your original audience.

This is particularly important, if not from a human perspective, at least from a business perspective, when the bias of your current audience is about the larger audience.

<comment><USER36> Wow, those results are so different from Bing Images for the same search.

<comment><USER37> That's really amazing. There's a similar situation when you search "American scientists." Interestingly the regular search results are very different, but the image search is similar.

</comment></comment></comment><comment><USER38> I think the problem is that we're turning the 'learner' around in these situations. It used to be that computer interfaces were static, any shortcuts/quirks it had were learned by the human who then used to their advantage.

These days we have systems that is not as smart as us trying to figure us out, with predictable results. Tricks and quirks are ever shifting. A query that used to produce the results yesterday might not function the same two weeks from now. Any skill gained in navigating the system needs to be constantly trained and updated.

I believe something similar happened to Hawking, where he had a keyboard that was not smart, but was predictable so that he was the one learning to use the system. He disliked a new version of the software that would not behave in a predictable way because it 'learned'. I can't find the link anymore sadly.

</comment><comment><USER39> Isn't this basically the same phenomenon (and result) as instant retweeting and the like button?

If you simply reflect and amplify the behavior of the general population, you can get some pretty ugly results — which is because the general population has some actual ugly tendencies that are being accurately depicted. So the conversation needs to be about how we should actively _bias_ the algorithm to damp out the ugliness, which is already being done by Twitter, FB, Google, etc.

I think we've done the experiment and proven pretty conclusively that a totally unbiased algorithm or information-sharing network is not a good thing for society, unless you want society to be like 4chan. Of course, that immediately opens the can of worms — who gets to decide how to bias the algorithm?

</comment><comment><USER40> Search for 'white man and white woman.' The reason I mention this is that the article implies this is some sort of result of social bias and stereotyping. As the result of that search shows (it's entirely interracial couples), it most certainly is not. No, it's a result of the fact that Google's search is not particularly smart. It's arguably the best there is, but it still comes down to correlating words to pages and that correlation is far from intelligent.

And as an aside, I think the term of bias in algorithms is misused when they are operating as intended. You'd call a poll biased if it implied it was polling group 'x', but did not actually do so due to some inadvertent bias. You wouldn't call it biased if it polled the group it stated it was going to poll and then gave the results - even if those results were not what you personally would want to see. If people are mostly searching for interracial couples when they search for 'white man and white woman' or they are mostly searching for porn when they search for 'black girls' then a biased algorithm would be one that actually returned white couples or non-pornographic results.

</comment><comment><USER41> I really appreciate the point: as much as the content of what's on google has nothing to do with google, the prioritization of search results is on them. Whether it's hard or not to avoid perpetuating stereotypes doesn't seem to obviate their responsibility to not perpetuate stereotypes, any more than the fact that Facebook's having so much content flow through their feeds could remove Facebook's responsibility to not help the spread of fake news.

Google's search results is really the oldest analog we have for the "machine learning learns racism" quandary, too. This question is just going to get bigger, and its effects much more pernicious.

</comment><comment><USER42> Several of the searches given as examples of racial bias are already in a feedback loop; if everyone on the Internet starts writing articles saying 'OMG search for _unprofessional hairstyles for work_ and look racism' then it shouldn't come as a surprise that the first results for otherwise innocuous phrases become skewed, and removing this so-called bias actually requires direct intervention.

Although if one actually compares the results for _[un]professional hairstyles for work_ there doesn't seem to be any negative bias; black people are well- represented in both result sets.

</comment><comment><USER43> I'm usually very critical of Google for other reasons (privacy, android etc.) but I don't see them at fault in this case, at least not of being voluntarily racist. Their algorithms "evolution" is based on what people searches and find useful, which means if say someone clicks on a link and stops searching for a while it could mean the user found what he/she was looking for. Now if thousands of people search for "black girls", the search returns say some porn links among others and most users click on them, could we expect the algorithms to ignore porn or rather to slowly adapt to what most users considered the right result?

The other points look also valid to me, but again, I don't see why Google should be labeled racist when their engine adapts to what news sources publish. Somewhere in the code there could be an association like 3 teens -> gang and a piece of code skimming news sources that reacts to all articles containing the word "gang"; now just mix the two and what you get? Just try searching for "gang" and look at the colors predominance. Search engines aren't easy to write. If I was an Eiffel language expert I would write a book titled "A tour on the Eiffel language" just to prove that. Try searching that phrase without getting submerged by images of the famous tower. Incidentally, a fun search for "a tour on the Eiffel schnitzel kraut" yielded about 90% food related results and only about 5% tower images although it still contained 100% of the terms for both, but having the word Eiffel not immediately following tour could mislead the search engine, so I changed it to "the tour Eiffel on a schnitzel kraut" and results slightly changed with more towers but also more unrelated stuff like Stonehenge.

To me a search engine should return results based on harsh reality if necessary, not church choir dreams; policing search engines results in pursuit of politically correctness would be very dangerous. We won't see that day, nor will our grand-grand-grand-grand-kids, but one day eventually racism will start vanishing from society by itself and search engines will follow, and/or we'll be socially mature enough to ignore anything that could resemble racism to a today's biased mind, giving it even less exposure.

</comment><comment><USER44> Back in the 90s, search engines were notorious for serving back lots of porn links interspersed with whatever thing you were looking for. I was unusual (apparently) in that my searches tended to be really specific and I rarely got a lot of porn results. Except one time. I was looking for information on gun violence in Europe and I was getting back not just a few porn results, but lots and lots of them. I was using really simple queries, so I was able to quickly isolate the offending term.

It was: "Sweden".

(Most likely this was on Alta Vista, not Google, but I don't remember for sure.)

<comment><USER45> This is because marketing weasels had just discovered the hottest new tech of the day: meta tags. And immediately set about polluting them. At one point in the mid 90s about half the web that existed at the time was tagged "Anna Kournikova naked".

(Probably many on HN are too young to remember her... imagine Taylor Swift x10, that was her popularity back then)

</comment></comment><comment><USER46> The headline should be "Google Search has a striking history of bias against black girls," to clarify between Google the search engine and Google the company that makes the search engine.

</comment><comment><USER47> "What we need now, more than ever, is public policy that advocates protections from the effects of unregulated and unethical artificial intelligence."

Artificial Intelligence has become an alias for "shit I have no knowledge of but would like to pretend to have expertise on that is, at least tangentially, related to a computer"

</comment><comment><USER28> So Google now gives her different results when she makes the same queries. Makes me wonder if this is when she is a logged in user, and what differences there exist between logged in users one to another and non logged in users.

When I try it in both logged in and non-logged in mode I get reasonably similar results, the differences are mostly in the ordering. When I do the same on Bing I get about 20% or so pornographic images for both 'black girls' and 'white girls'.

<comment><USER27> I only get wholesome results for "black girls", so maybe Google already puts us in our own echo chambers regardless of the SafeSearch settings.

<comment><USER28> No, Google has adjusted the weights of that particular output category, see the article linked.

</comment></comment></comment><comment><USER48> There are some excellent ways of framing this problem already covered in the comments. I'd like to add another. As time goes on, people seem to be treating google searches less as database queries and more as a question/answer system. Google is moving this direction too (e.g. "how tall is the eiffel tower" gives an answer above the web pages).

When google was just an excellent database index and relevance ranker, then it was ok for its results to simply reflect the underlying data. If the internet is racist, then looking up things on the internet will find racist things.

As time goes on and google purports to give answers and facts and gets more information-ey, they're kinda taking an editorial stance that the results aren't simply relevant webpages, but correct answers in some loose sense. When google tells me the Eiffel tower is 984' tall, and 1063' to the tip, they are endorsing that as The Right Answer. Endorsements come with responsibility.

As Google pushes to give correct answers, and people increasingly expect it, it's an endorsement of search results that comes with responsibility to not just reflect the huge corpus that is the internet.

</comment><comment><USER49> Incidentally I think - this is how you debias an algorithm: you marginalise on all the discrimination criteria and check to see if it is balanced and respectful on each subdomain. Google should have a set of automated tests for that, and it's not that hard - a team of AI and sociology experts could do it. The same type of problem is the capital sin of FB - they amplify bias intentionally, selling us to the highest bidder.

</comment><comment><USER50> A Google search for "American inventors": [https://i.imgur.com/qw5kfQp.png](https://i.imgur.com/qw5kfQp.png)

A Google search for "American women scientists": [https://i.imgur.com/o6mxG56.png](https://i.imgur.com/o6mxG56.png)

Can the media stop doing this thing where they p-hack reality for proof of racist/sexist conspiracies?

<comment><USER28> You are missing the point: there is no reason why an innocent query such as 'black girls' should bring up a bunch of porn. And Google seems to agree with this because they have since tweaked things so that that no longer happens.

<comment><USER51> No, the point is that the author selectively presents information that bolsters the point she wants to make.

I'm pretty certain that if she searched for "<blank> girls" \-- white girls, asian girls, etc. -- with safe search turned off, a good number of the results would be NSFW, because the internet is 75% porn (and 25% cat videos).

<comment><USER28> See the paragraphs titled 'beyond black girls' in TFA.

<comment><USER51> Yes, I read the article. If anything, those paragraphs support what I just wrote.

<comment><USER28> You wrote "No, the point is that the author selectively presents information that bolsters the point she wants to make." and then claim the author supports _your_ point?

At best you are supporting hers.

She made the case for the query 'black girls' and to pre-empt comments such as yours bolstered her argument by extending it to a general case. So in no way did she 'selective present information to bolster her point', she was as even handed as she could have been (but apparently not even handed enough for some).

<comment><USER51> No, I'm saying that in the paragraph in question, she's half-admitting that she is selectively presenting information. That is all.

</comment></comment></comment></comment></comment></comment></comment><comment><USER52> Google is absolutely at fault here. They are much more involved in tweaking search results than they admit.

They are especially slanted on an ideological basis. Try searching "American inventors" \- nearly all the people listed are African Americans.

I doubt all of this is inadvertent, and its definitely dangerous, given the power of Google. Today they are undoubtedly influenced by "left-wing" ideology, but what about tomorrow?

</comment><comment><USER53> This title is a bit misleading. The article opens with:

> My first encounter with racism in search was in 2009 when I was talking to a > friend who causally mentioned one day, "You should see what happens when you > Google 'black girls.'" I did and was stunned.

but then later on:

> Although I focus mainly on the example of black girls to talk about search > bias and stereotyping, black girls are not the only girls and women > marginalized in search. The results retrieved two years into this study, in > 2013, representing Asian girls, Asian Indian girls, Latina girls, white > girls, and so forth reveal the ways in which girls' identities are > commercialized, sexualized or made curiosities within the gaze of the search > engine. Women and girls do not fare well in Google Search — that is evident.

So it's not racism, it's sexism. Or is it? What would have happened if you searched for black boys, white boys etc. in 2009? I bet it wouldn't have been PG friendly...

</comment><comment><USER54> It's a difficult discussion because if you look at the literature regarding algorithmic fairness, there really is no measure of equality that satisfies all notions of fairness. If you force representation of seemingly underrepresented patterns in the data then you implicitly engage in social engineering.

This might be legitimate and reasonable, but you probably should be transparent about the fact that you "unbiased" your data by externally imposing a certain view of what the "fair" data should look like.

Ultimately it's a discussion for social scientists or laywers concerned with discrimination, it's not really in the realm of being fixable by engineering or computer science imho.

</comment><comment><USER55> Debiasing signals is a common procedure that signal processors are interested in. Not saying it's an easy or well defined problem, or that the solution will be legal, but dispassionately there is an engineering problem there to be solved.

</comment><comment><USER56> Um, it's not "Google", it's "the content of the internet" that's biased - right?

<comment><USER57> If Google was still concerning itself with representing the content of the internet, this would be the case, but increasingly Google is tailoring its results for whatever other varied ends.

If it is curating the data, then how it curates matters. In this case, they've curated most of the porn from the first page of results, from the looks of it.

Not sure how that makes me feel.

</comment></comment><comment><USER58> Without delving too deeply in to it, it seems google is reflecting existing biases society-wide.

This is problematic in the same way as facebook's echo chamber effect, that it can cause a feedback loop that reinforces and heightens bias and division.

Beyond that though, I think it gets gnarly how much we want Google to _fix_ the world by tweaking their algorithms. We obviously want something thoughtful. At the same time I don't think we should lay all the world's problems at google's feet.

</comment><comment><USER46> I don't think there's a clear answer as to what Google SHOULD show for "unprofessional hairstyles." The article shows a screenshot of it showing a lot of normal-looking black women with natural hair, which of course shouldn't be considered unprofessional. But it's definitely true that society has a racist approach to black women's hair, and doesn't consider it "beautiful" unless it's straightened. Hence nearly all famous black women straighten their hair.

Should Google show black women's natural hair in the results for "unprofessional hairstyles" to accurately reflect society's unfair attitudes towards black women's hair? Or should they show actual unprofessional hairstyles like giant mohawks etc.? Or should they show a message saying "No hairstyle is unprofessional. Be who you want to be."?

</comment><comment><USER59> I want an algorithm to filter out any responses to this that talk about "political correctness".

</comment><comment><USER60> There's an interesting concept - __Machine Bias __discussed in one episode of You are not so smart[https://youarenotsosmart.com/2017/11/20/yanss-115-how-we- tra...](https://youarenotsosmart.com/2017/11/20/yanss-115-how-we-transferred- our-biases-into-our-machines-and-what-we-can-do-about-it/)

Developers who train these models or algorithms should be very well aware that the training data is nothing but a download of a sexist, capitalist, racist - society and that bias if is carried forward - irrespective of anything the future isn't going to be clean!

</comment><comment><USER61> DuckDuckGo:

[https://duckduckgo.com/?q=black+girls&t=h_&ia=web](https://duckduckgo.com/?q=black+girls&t=h_&ia=web)

</comment><comment><USER62> Seems like the algorithms just surface already existing patterns in society. They have no inherit bias of their own, they are merely reporting the reality it sees.

Is introducing an anti-bias at the search engine level the appropriate solution? It seems a bit too much like Western medicine alleviating the symptoms without addressing the root cause. An anti-bias is just masking it.

Also, if the author is a feminist, why she writing for a magazine called "Bitch"?

</comment><comment><USER63> If you do a search for "three black teenagers" you now see all the top results are screenshots of the mug shots that people saw when they previously searched for the term. So basically the discussion around it makes it more prominent not less. Not saying this is right or wrong, just pointing out the results are basically being reinforced.

Now when you do a search for "three white teenagers" you mostly get mug shots of black teens.

</comment><comment><USER64> This is ridiculous.

This just means that people on the internet who write about black teenagers write about the ones who get arrested. People who create pages about "black girls" create porn content, and most people who search for "black girls" most likely are looking for porn and click on links that talk about porn.

It's amazing how people can see racism everywhere.

</comment><comment><USER46> The world is an unfair place with a striking history of bias against black girls, and Google is built with trillions of data points from this world. Society thinks that black women's hair is ugly and white women's hair is beautiful, and Google, with the power of their machine learning, reflects this unpleasant societal truth back to the user.

</comment><comment><USER65> Searching for "Asian girls" or "Mexican girls", etc, produces similar results.

I can see the rationale for altering the algorithm for words like "girls".

It's also interesting that, for example, the results for "swedish girls" are much tamer. Even though that's sort of a long standing phrase that was very sexual.

</comment><comment><USER66> With all due compassion, don't "black girls" generally have a hard-enough time with broader acceptance, and this might be what is reflected in google search results?

In other words, this is not Google's fault and is mostly just an ugly reflection of our collective problematic values.

</comment><comment><USER67> I see a lot of comments about whether Google results should be reflective of society or unbiased, but little discussion of who gets to define what is unbiased. Since that itself is a judgement call, I don't see how they won't be accused of introducing their own bias.

</comment><comment><USER68> "We're only reproducing society's most harmful biases" is not much of defense.

</comment><comment><USER69> Apologies for being slightly off topic.

While trying to read to article, my browser (Safari on iPhone) was redirected to a scammy looking amazon gift card website. Did anyone else have this problem? I am trying to figure out if it is a problem with Time.com or my phone.

<comment><USER70> Likely your phone, given that no-one else has complained.

Sometimes I miss the HN of 2011-12, where literally 80% of the comments were about the design of the site, and how it didn't work on Safari/IE/Firefox/Chrome/Lynx.

Not often, though.

</comment></comment><comment><USER71> I'm often reminded of the Oscar Wilde quote:

"There is no such thing as a moral or an immoral book. Books are well written, or badly written. That is all."

Replace "book" with "algorithm", and you have my sentiments on the issue.

</comment><comment><USER4> I thought it'd be worthwhile to see how DuckDuckGo handles things since it's ostensibly the search engine _without_ personalization. And it has a different scope and expectations from Google. One thing that comes to mind is how it dealt with the "did the holocaust happen"-type problems by hard coding the instant answers [a], something which Google doesn't admit to doing outright, and wouldn't be scalable anyway.

DDG's results for "black girls" is pretty different from Google present-day, though definitely a lot cleaner compared to what the author saw in 2009:

[https://duckduckgo.com/?q=black+girls&t=hb&ia=web](https://duckduckgo.com/?q=black+girls&t=hb&ia=web)

(sidenote: it's not clear if the author disabled SafeSearch in her 2009 search or not. SafeSearch was definitely part of Google by then, and I can't imagine "sugaryblackpussy.com" getting past that filter. If you turn DDG's Safe Search to "Moderate" \-- "Off" returns the same results as "Strict" \-- you will get a lot of very NSFW results. I guess this sidenote raises a new set of issues about the author's methodology but will ignore it for the sake of brevity here.)

The first result is an article titled "Black Girls Only" in Ebony magazine [0]. Which isn't a bad article (or publication). Maybe people would object that the first result is actually about sexualizing black women (albeit positively). The 2nd result is a lot less promising: "Hot Black Girls (45 pics)" at acidcow.com, which has a higher Alexa ranking [1] than Ebony.com (22K vs 63K), but basically looks to be a clunky imageboard. blackgirlscode.com is #6, followed by blackgirlsrun.com (a running club). The rest of the top results are black girl image sites (photobucket, a Facebook group for Big Beautiful Black Girls). The most notable difference between DDG and Google Results, besides what's #1, is that Google results have a lot more news articles in which "black girls" are in the headline (via NPR, nytimes, and theroot). DDG is a lot more sporadic in comparison

DDG for "white girls" is not terribly better in terms of being female- friendly:

[https://duckduckgo.com/?q=white+girls](https://duckduckgo.com/?q=white+girls)

The first result is to the Amazon listing of a book titled "White Girls", by a well regarded New Yorker critic [2]. But the #2 result goes to urbandictionary.com, and #3 hilariously goes to the Wayans Brothers' classic, "White Chicks". There's a bunch of results relating to "White Girl", the mediocre 2016 film (Wikipedia, rogerebert.com, rottentomatoes.com, etc). And then a bunch of results about white females with men of other races.

[a] [https://github.com/duckduckgo/zeroclickinfo- goodies/blob/b7a...](https://github.com/duckduckgo/zeroclickinfo- goodies/blob/b7a73754210185594d945716aedde5cc8486fcba/share/goodie/historical_events/events.yml)

[0] [http://www.ebony.com/news-views/black-girls- only-503](http://www.ebony.com/news-views/black-girls-only-503)

[1] [https://www.alexa.com/siteinfo/acidcow.com](https://www.alexa.com/siteinfo/acidcow.com)

[2] [https://www.amazon.com/White-Girls-Hilton- Als/dp/194045025X](https://www.amazon.com/White-Girls-Hilton- Als/dp/194045025X)

</comment><comment><USER72> It's interesting how the article tries to 'blame' an algorithm while it's basically just working fine and simply reflecting the output of culture/country/people. It's not that the software decided that one thing should be the results, and others should not, it just takes what we feed it, and gives it back to us.

<comment><USER73> I find the concept fascinating that anyone would think an algorithm is "racist". More or less begging human interference with the algorithm in order to make it less racist, anything anyone does can then be viewed as racist.

<comment><USER4> "Racism" involves prejudice and discrimination predicated on the belief that one race is superior/inferior to another. If a face-detection algorithm fails to easily recognize black or Asian faces, such that people of that ethnicity/race have to go through a more manual/friction-laden process (think manual pat-downs and searches from TSA) to be verified as "human" or "citizen", then how is that algorithm _not_ responsible for discriminatory treatment?

I do agree, though, that it is wrong to infer that the algorithms _themselves_ are evil or malicious -- it's possible to be racist without having negative intentions.

But what does it say about a society if it continues to optimize algorithms (and related infrastructure) for one group over another?

<comment><USER72> Of course those systems 'discriminate', that is what they are designed for. The problems aren't with the system, but with how they were set up, implemented or tested.

Say you make a sensor that is supposed to tell the difference between blue, green and purple, but you only test with one shade of blue and maybe two shades of green, you are going to have trouble actually matching your design goals.

In the case of the face detection system: they didn't specify and/or test is well enough, which can be due to a number of factors, but will most likely lie with the employees of the company that did the development. If they only have the classic 'pasty white guys' to work with, then it's going to be crap at actually doing face detections for all humans. On one hand you could setup a proper test protocol, on the other hand they shouldn't have taken broad or vague terms when developing/presenting the technology. If you don't have a broad selection of faces to test with, you shouldn't claim you have 'face detection', since you merely have 'detection of faces of the people that work on the project plus anyone who looks like them'.

This would be a completely different story if someone writing the face matching code specifically programmed code or wrote configuration data that targets skin tone or geometry of specific groups of people.

Some people would like to extend this type of technological issue into the area of HRM and race/gender-bias in society in general, but that is not a technology-only discussion and hardly something the people involved are qualified to argue about.

Also: >But what does it say about a society if it continues to optimize algorithms (and related infrastructure) for one group over another?

It says that society is imperfect, and that certain levels of xenophobia, bias and true racism exist. Doesn't say much about technology though.

<comment><USER4> > _If you don 't have a broad selection of faces to test with, you shouldn't > claim you have 'face detection', since you merely have 'detection of faces > of the people that work on the project plus anyone who looks like them'._

Yeah, but that's what happened here with HP in 2009. I'm not a huge fan of their products these days but I don't think they would intentionally be deceptive here, i.e. I think there's a lot of room to blame incompetence before malice. If HP is a company with very few black employees, this kind of consideration may be completely off their radar. It's super unfortunate, but I don't see the company as evil or maliciously racist, per se (I think we can skip retreading the hiring for diversity debates for now).

> _This would be a completely different story if someone writing the face > matching code specifically programmed code or wrote configuration data that > targets skin tone or geometry of specific groups of people._

Why does it matter? What's the difference between an algorithm that fails to perform because of programmer incompetence, or programmer malice? What's the difference to the end-user if the programmer was plain ignorant of good testing coverage, vs. a programmer who thought _" Fuck it, minorities are a minor part of our user base. Not worth the extra engineering effort!"_?

Technology is an unavoidable part of the problem. Because it is the technology that allows us the power and freedom to create and apply scalable algorithms to machinery and computers. This automation allows for efficient and reliable decision-making, and we as a society decide where that automation is appropriate and worthwhile, i.e. where human agency is no longer needed.

But technology and its fundamentals are still a key factor. Creating a multi- racial face classifier is fundamentally more work and difficulty than one trained for just one race. The math and physics are unavoidable. And every engineered system and product has to make tradeoffs between production cost and feature set.

In the case of the light-skin-optimized HP web cam, I think it's important, and fine, to call it "racist" \-- a black HP customer will have an inferior experience fundamentally because he is racially black. But this isn't just a way to quickly assign blame. Recognizing that tech is fundamentally limited is the first step in understanding that systemic racism (e.g., all the decisions that led to the "racist" camera) could be a contributing factor to the camera's substandard performance.

Much harder to get to that thinking if we have a mentality of, "how could the computer be wrong/flawed?"

</comment></comment></comment></comment></comment><comment><USER74> They have a lot fewer crayons in their box than they like to project.

</comment><comment><USER75> _Why are white men stockpiling guns?

Why are so many white men so angry?

White men must be stopped: The very future of mankind depends [...] The future of life on the planet depends on bringing the 500-year rampage of the white man to a halt. For five centuries his ever more destructive weaponry ..._

My first three DDG-results on searching ' _white men_ '.

I shall now proceed to get over it. Suggest others do likewise.

</comment><comment><USER76> I'm not sure how the fact that many web users, many of whom are white, find black girls attractive, is somehow construed to be "bias against black girls"? Unless your job is to see bias everywhere...?

Oh.

</comment><comment><USER77> This article feels like bait for smart people to ruin their careers with honest responses.

<comment><USER78> I certainly hope not, there are a lot of great comments above that read as both honest and smart.

</comment></comment><comment><USER22> > "p-ssy," as a noun

You are allowed to say fuck on the internet.

Also, does it really count if you skip out _one_ letter? I never understood this. You're still all but saying the word. Nobody is being protected here lol. A kid can cycle through the five vowels in about half a second to figure out what the word is, and one of them is also kinda a swear - pissy.

EDIT: "n 2012, I wrote an article for Bitch Magazine" now I'm very confused. It's ok if it's a proper noun, I guess?

<comment><USER79> Different publications have different style books. This is Time, which, given it's history as a mainstream magazine, likely has a more conservative editorial style than more recent, online-only publications.

<comment><USER22> I believe you, I'm just curious why the style guide ever said "swear words are fine as long as you blank out a single letter."

Meh, likely the answer is unknown, mostly I'm just commenting

</comment></comment></comment><comment><USER80> Do we know if Google or tech in general hires black women less than proportional to the US population?

<comment><USER81> We do, yes.

[https://www.usatoday.com/story/tech/news/2016/06/30/google-d...](https://www.usatoday.com/story/tech/news/2016/06/30/google- diversity-numbers-2016/86562004/)

> Women made up 31% of Google employees in 2015, up one percentage point since > 2014, according to statistics released by the Internet giant on Thursday. > One in five technical hires were women in 2015, raising the number of women > in technical roles to 19% from 18% in 2014 and 17% in 2013. In 2015, women > held nearly a quarter of leadership posts at Google, up from 22% in 2014 and > 21% in 2013.

> Google says it's also hiring more black and Hispanic workers: 4% of hires in > 2015 were black and 5% were Hispanic. Hispanic employees in technical roles > increased to 3% from 2%. But the increased hiring did not budge the overall > percentage of underrepresented minorities in the Google workforce as total > hiring rose, with Hispanics making up 3% of the work force and African > Americans 2%.

Given that women are half the population, and African Americans and Hispanics each make up about 12%, we can state categorically that Google's hiring doesn't match the general US population.

<comment><USER82> > Given that women are half the population, and African Americans and > Hispanics each make up about 12%, we can state categorically that Google's > hiring doesn't match the general US population.

But if you account for demographics _within the industry_ do the numbers remain biased?

For example: men account for less than 10% of nurses so if you were to go to a hospital with 50% male nurses they would be _way_ overrepresented. Statistically speaking of course, I'm in no way trying to give the impression we need to do something about the lack of diversity within the nursing profession.

\--edit--

...or maybe we need to do something about the lack of diversity in the nursing profession? Don't actually know how this ball rolls?

<comment><USER80> From what I know there is push for more male nurses and some issues with doscriminatory attitudes towards male nurses.

</comment></comment></comment></comment><comment><USER83> Now do "white couple", or "american inventors".

</comment><comment><USER84> > In 2012, I wrote an article for Bitch Magazine

Seems ironic.</comment>


Show HN: Another 2048 clone (sorry): 2048+-/* - <AUTHOR> http://frankh.github.io/2048/

<comment><USER2> Fun variation. Darn difficult and more luck based, though.</comment>