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by oreilles 1746 days ago
This isn't a problem with diversity. Everybody knows how to pronounce Malcom X. And it's not like just because a google engineer was black that he was like "oh, let's try and see if Malcom X is pronounced correctly because he's black and I'm black too". This only happens in white people's brain.
5 comments

I don't know if I 100% align up with how you stated it, but yea, its a matter of training data set. I don't think these companies have published their training data set. But thinking back on the issue with asians and facial recognition on Apple's face ID. If they just choose 100 people at random, based off US statistics, 5-6 of those 100 people would have been Asian. And that reflects the 5.7 percent of the population is Asian. And we probably all agree 5-6 people is not a sufficient data set, but picking 100 people at random would be a pretty easy assumption to make for making a data set.

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.

I wonder what the datasets of companies like Xiaomi look like. FaceID always worked for me, so it seems like it works for non-asian faces.
Maybe they took more caution to their data set. I think the only way we would know is if they publish their sets or how they built them. But I was just highlighting maybe one possible case that Apple could have generated their training set, just grab 100 people in America at random.
You realize that the person I'm quoting isn't white, right?

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.

Considering the adversarial attacks that image recognition systems are vulnerable to, perhaps even a well trained system could be induced to produce inappropriate results of one sort or another. Perhaps the training set and algorithm for the model should just be publicly available so that people can scrutinize the data and figure out incrementally how to avoid most biases or guffaws to a generally accepted level.
> This only happens in white people's brain.

'Eleven Jinping': Indian TV fires anchor over blooper.[1]

[1] https://www.bbc.com/news/world-asia-india-29274792

To play devil advocate, maybe the station fired her for ignorance of current events.
> maybe the station fired her for ignorance of current events.

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.

In what universe is "Ten" a more common pronunciation of "X" than "X"? You might have an argument for "II" or "III", but I'll be shocked if any street in USA is named after the tenth generation of really unimaginative namers.
Do you think Google is having someone go through the tens of thousands of street names?

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.

I could see that for Google Maps v1.0. I think we're past that point now. There's no reason they should still be using libraries suited to parsing the names of forgotten European monarchs.
They’re neither forgotten, unused, nor is it a nomenclature used exclusively by Royals; nor are all the Royals that use this fashion dead or out of power.
Oh for Pete's sake, absolute bloody conspiracy level nonsense, NOBODY sat there twirling their villainous mustache and programmed an exception to hardcode pronouncing X as 10, it's simply a matter of the training and sample data having access to some type of corpus that contained a great deal of Roman numerals.

(Leave the software engineering to the software engineers)

>> to some type of corpus that contained a great deal of Roman numerals.

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.

For sure. If we're going with the common pronunciation of Roman numerals in English names, it's "Tenth". E.g., We don't say "Henry Ford III" as "Henry Ford Three" but "Henry Ford the Third".
There’s a Louis XIV Street in New Orleans (and I imagine elsewhere).
You mean Louis 'Ziv', according to Google
Putting Louis XIV in Google translate, I get the correct "Louis the Fourteenth" and "Louis Quatorze" pronounciations in English and French, respectively. However, it has to be uppercased, otherwise it spells the letters.
The implication is that a black person would be more likely to recognize the inherent flaw in automatically interpreting "X" as "10", and in all honestly that's probably true. It isn't a matter of testing, it's a matter of having people with a diverse set of cultural perspectives in the room when decisions like that are made to begin with.
Diversity doesnt guarantee you automatically catch or account for edge cases. As a minority I am disturbed by some of the odd takes people have about diversity. Theres thousands upon thousands of roads. Unless you have a QA team test directions to every road in the country you wont ever catch the issue with a road named Malcom X. You don’t even have to be ‘diverse’ to know who that is.
It doesn't guarantee it, but it helps.

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.