Facebook, like a lot of tech companies, has long had problems with diversity in engineering. Here's an article from April that discusses specific incidents and the broader background: https://www.washingtonpost.com/technology/2021/04/06/faceboo...
So yea, I think it is an issue with generating a data set and not hitting a sufficient amount of test cases. Because in this instance, asians would be an edge case where creating a small data set to train an algorithm on with a group with a lower representation in the population.
Let's separate the general case from the specific. Generally, we know that representation in the people who make things changes what they make. This is obvious and undeniable. For example, look at ASCII vs Unicode. The Chinese invented movable type 500 years before Gutenberg, so it's not like the idea of printing non-roman characters was novel. In the age of telegraphy, Europeans developed encodings that included umlauts and accents; by 1851 they were merged into International Morse Code.
So why in 1963 was ASCII codified without any of that? And why did that become the dominant standard for an extended period? Because it was mainly Americans in the rooms where the technology was being created.
Similarly, we know that standard color films were developed by white people to represent white people well: https://www.vox.com/2015/9/18/9348821/photography-race-bias
And we all know how this happens. It's the same reason a lot of open-source software is good for a developer audience, not an end-user one: making things means iterating on them until they're good enough for the people involved.
That's the general case, so let's return to the specific case. If you want to prove that ML systems doing racist stuff has nothing to do with who made it, then you can't just handwave it away. You have to show why that specific project was set up so carefully and so well that it would avoid the natural pitfalls of any technology project. And then despite that it went on to do racist stuff. For reasons that you'd then have to explain.
'Eleven Jinping': Indian TV fires anchor over blooper.[1]
That would be a valid reason, but I suspect a more culturally appropriate one: loss of reputation. We are sensitive to that.
My point was this isn't something that only goes on in 'white' brains but more of a cultural issue. Most people in the West are incapable of pronouncing Asian names. I don't see people making a big issue out of it.
Or do you think they had a team (on a completely different project or perhaps company) write a text to speech function that wasn't well suited for directions.
Streets have lots of numbers after all. People frequently have numbers in their name.
(Leave the software engineering to the software engineers)
I wager that there is more text online about Louis XIV than of Malcom X. Certainly there are many more books on that epic corner of French history than one modern US leader. Then there are all the British kings. Point an AI at the internet and it likely would decide that roman numerals are most often pronounced as number than letters. Malcom X would be rare an exception that might need to be hard coded.
I personally have gotten bugs fixed at Google. How? Because I, a white man, spotted a bug, cared about it, and talked to white men of my acquaintance at Google who had enough power to get things done. How did I know them? From other tech companies created, run, and majority staffed by other white men.
Why am I in these networks at all? Well, my dad was a software developer and he introduced me early on. How did he get his start? His dad, an insurance company exec, brought him in to deal with this newfangled computer thing they had just gotten. That was in Milwaukee in the mid-1960s. I promise you that although Milwaukee had a significant black population, exactly zero of them were insurance company executives in the mid-1960s.
So what Allie Bland knew when she wrote her tweet was that she did not have any connection to Google where she might be able to get a to-her glaringly obvious pronunciation issue fixed. That in her estimation no black person did. And I see no reason to think she was wrong.
I've struggled with people telling me that these FAANG companies have "diversity problems," as a person of color myself. A majority of software engineers are female and male immigrants from East Asia and South Asia. These population centers are some of the most diverse regions of the world. The engineers who have been hired by preparing for and passing these companies' selective merit based coding tests had to overcome adverse conditions in their home countries as well, including extreme poverty, starvation, and totalitarian regimes.
Why do they not count toward diversity, to some white and white-adjacent critics? What message are we sending to people who are ethnic minorities from certain groups who earned their spots through merit and have also been targeted in recent newsworthy attacks, just as others have, when we make these kinds of accusations? What does a non problematic ethnic composition look like? What are these companies doing right toward some minority groups and wrong towards others?
Long ago I learned that it was rarely worth my time to try to argue online people out of their ignorance. A rando with a throwaway account, a strident tone, and a fair bit of ignorance on the topic is almost a guarantee that that's no point.
If you're interested in knowing something about the topic, you'll do some work. If you aren't, no amount of me spoon-feeding you summaries of serious scholarly works will change that.
If you do end up learning something and have questions, feel free to email me. I'm glad to discuss the topics with people who are serious about it.
Put more frankly, the success of recent immigrants does not erase America's long history of brutality and exploitation toward blacks and Latin Americans. The latter is a problem that we have to solve regardless.
And I think it's worth noting that some of the immigrants have brought their own biases with them, such that caste discrimination is now also a problem in Silicon Valley: https://www.washingtonpost.com/technology/2020/10/27/indian-...
But given that America was far more brutal and exploitative towards Chinese immigrants than towards Latin Americans, why are Latinos so prioritized by these initiatives to favor certain racial groups?
> And I think it's worth noting that some of the immigrants have brought their own biases with them, such that caste discrimination is now also a problem in Silicon Valley: https://www.washingtonpost.com/technology/2020/10/27/indian-...
Ironic that in a discussion about diversity, you believe in a prejudiced stereotype about a major ethnic group in Silicon Valley. Casteism is pretty much a nonissue in Silicon Valley, if only for the simple reason that most Indian-Americans tend to be ignorant about the castes of most other Indian-Americans.
You might not share the beliefs of others that are gainfully rallying behind diversity as a cause to justify penalizing some minority groups for "doing too well" and bolstering others (the literal definition of discrimination), but it IS happening -- and certainly more people than "nobody" are backing it, provoking my original statements. Someone had to put Prop 16 on the ballot, for example (which was thankfully voted against by a large margin of fellow CA Democrats).
Turning it back on you, what should the point of a diversity program be? What's meant to be achieved outside those three goals?
You should also look up the extensive critiques of meritocracy as a concept. There's a lot of literature there.
Further, I know of no major tech company who uses a nominally "objective coding test" as the only criterion for hiring. And they shouldn't, because being good at taking coding tests is not the job and not what we should be hiring for.
Coding tests examine the type of work actually required to be done on the job (as coders), and they have been correlated with post-hire performance successfully. Someone who is not familiar with efficient data structures will not write scalable code and will end up creating a burden on their teammates during on-call, for example. Asking someone to solve an engineering problem with a provably correct answer is an objective test for hiring engineers, and I will have a difficult time continuing to engage with anyone who counteracts this basis of reality and truth.
When I was hired there were three coding test rounds and one interpersonal round. You might argue that the latter is where racial discrimination seeps in, as well as the recruiter outreach step itself, but somehow I am optimistic that a bunch of tolerant Californians have moved past applying a Literacy Test here already by hiring a majority immigrant / minority workforce. In my situation, my recruiter was also an Asian-American minority.
Since my comments here don't seem to be making any sense to you, I'm not seeing the point in trying again.
The companies are then righting the wrongs on the shoulders of innocents, that most likely never were racists to begin with. In short, just committing to another mistake.
South Asia and SE Asia, maybe. But East Asia (NE China, Korea, Japan) has actually one of the most ethnically "pure" populations in the world.
Northeast China–usually defined as the provinces of Liaoning, Jilin, and Heilongjiang–does not belong on your list. According to the 2000 Chinese census, about 10% of the population of Northeast China comes from ethnic minorities – the majority of whom are Manchus, but also including significant numbers of Mongols and Koreans. That is far from being 'one of the most ethnically "pure" populations in the world'-especially when compared to Japan or Korea.
Indeed, even though Northeast China was (in 2000) approximately 90% Han, prior to the 19th century Han were a minority in the region, and Manchus were the numerically (and politically) dominant ethnic group.
According to the 2000 Census, the most ethnically homogenous part of China is not the North or Northeast, but rather Eastern China, which is over 99% Han (and, as well as being over 99% Han overall, 4 of its 7 provinces are over 99% Han too.) By contrast, North China is about 94% Han and Northeast China is only around 90% Han.
(There have been two Chinese censuses since, in 2010 and 2020, but I can't find ethnicity figures for them.)
Or how about this one: Yes, all black engineers on the maps team live in New York.
Truth is that it is just an example one of the thousands of edge-cases that exist in these types of complex products, and some of them will look like they have some sinister basis.
If that is the case, why is it that Google voice nav routinely butchers the names of places and roads in India in spite of having thousands of Indian engineers on staff?
Could we blame the intractability of the problem, or just plain old incompetence, before we blame every single problem in the world on racism and lack of 'diversity'?
It forces a worldview where malice is the default assumption and encourages the "enemies all around us" mindset.
But it is an excellent question why Google Maps is still terrible at Indian place names even though they have plenty of people internally who not only could help, but would be delighted to. The answer to that will be essentially sociological. If you think that answer in no way includes structural inequity despite it being pervasive in America since its founding, you will have to explain how you think Google managed to eliminate that in the Maps division and then managed to re-introduce some sort of structure that leaves a wealth of internal knowledge untapped.
America is not unique in this. And African-Americans are not the only people in the world who were enslaved. What is unique is that America and Americans are so good at controlling narratives and sucking oxygen out of rooms that other stories and catastrophes are forced into irrelevance.
Sure it is. But if Facebook, Google and other American companies want to indulge their Americentric proclivities to the detriment of everyone else, they should voluntarily withdraw from the rest of the world.
Silly Google TTS, the proper pronunciation is obviously "Malcolm the Tenth" there.