4 ms·

Why is the ethics question important? It is a new feature for an audio codec, not a new material to teach in your kids curriculum.

The_Colonel 3y ago
Imagine you release a codec which optimizes for cis white male voice, every other kind of voice has perceptibly lower fidelity (at low bitrates). That would not go well...
- shrubble 3y ago
  [flagged]
  - p1esk 3y ago
    An ML model might be able to, even if you can’t.
    - GaggiX 3y ago
      Achieving the gaydar, do not give this technology to Saudi Arabia.
  - Edman274 3y ago
    What people have historically called a "gay lisp" is actually a hyper-articulation of /s/ or /z/, and as you might expect, /s/ and /z/ have a lot of high frequency sounds in them. Weird as it sounds there is a possible scenario where an audio codec does a worse job reproducing the audio content of gay male speech compared to straight male speech.
  - stevage 3y ago
    https://en.wikipedia.org/wiki/Gay_male_speech?wprov=sfla1 https://en.wikipedia.org/wiki/Gay_male_speech?wprov=sfla1 HTH.
- panzi 3y ago
  Yeah, imagine a low bitrate situation where only English speaking men can still communicate. That would create quite a power imbalance.
- dist-epoch 3y ago
  [flagged]
  - astrange 3y ago
    ^- https://knowyourmeme.com/memes/conservatives-have-one-joke https://knowyourmeme.com/memes/conservatives-have-one-joke
  - gcr 3y ago
    Questions of "which users can use my product and which can't" certainly encompass political views to be sure, but they also extend further beyond. I don't see why you feel the need to argue from the position of "woke devil's advocate" here. For a politically-neutral example of why poor DEI practice can lead directly to worse products, see my sister comment about faucet sensors and black skin.
- overstay8930 3y ago
  Meanwhile G.711 makes all dudes sound like disgruntled middle aged union workers
- numpad0 3y ago
  No offense/taken, but Codec2 seem to be affected a bit for this problem.
unethical_ban 3y ago
I get your point, but the questioner wasn't being rude or angry, only curious. I think it's a valid question, too. While it isn't as important to be neutral in this instance as, say, a crime prediction model or a hiring model, it should be boilerplate to consider ML inputs for identity neutrality.
gcr 3y ago
This is a great question! Here's a related failure case that I think illustrates the issue. In my country, public restroom facilities replaced all the buttons and levers on faucets, towel dispensers, etc. with sensors that detect your hand under the faucet. Black people tell me they aren't able to easily use these restrooms. I was surprised when I heard this, but if you google this, it's apparently a thing. Why does this happen? After all, the companies that made these products aren't obviously biased against black people (outwardly, anyway). So this sort of mistake must be easy to fall into, even for smart teams in good companies. The answer ultimately boils down to ignorance. When we make hand detector sensors for faucets, we typically calibrate them with white people in mind. Of course different skin tones have different albedo and different reflectance properties, so sensors are less likely to fire. Some black folks have a workaround where they hold a (white) napkin in their hand to get the faucet to work. How do we prevent this particular case from happening in the products we build? One approach is to ensure that the development teams for skin sensors have a wide variety of skin types. If the product development team had a black guy for example, he could say "hey, this doesn't work with my skin, we need to tune the threshold." Another approach is to ensure that different skin types are reflected in the data used to fit the skin statistical models we use. Today's push for "ethics in ML" is borne out of this second path as a direct desire to avoid these sorts of problems. I like this handwashing example because it's immediately apparent to everyone. You don't have to "prioritize DEI programs" to understand the importance of making sure your skin detector works for all skin types. But, teams that already prioritize accessibility, user diversity, etc. are less likely to fall into these traps when conducting their ordinary business. For this audio codec, I could imagine that voices outside the "standard English dialect" (e.g. thick accents, different voices) might take more bytes to encode the same signal. That would raise bandwidth requirements, worsen latency, and increase data costs for these users. If the codec is designed for a standard American audience, that's less of an issue, but codecs work best when they fit reasonably well for all kinds of human physiology.
- cma 3y ago
  What if it is a pareto improvement: better improvement for some dialects but no worse than the earlier version for anyone. Should it be shelved or tuned down so all improvement for each dialect see gains by an exactly equal percentage?
nextaccountic 3y ago
Because this gets deployed in real world, affecting real people. Ethics don't exist only in kids curriculum.
deleted 3y ago
[deleted]
samus 3y ago
This is actually a very technical question since it means the audio codec might simply not work that well in practice as it could and should.

The_Colonel 3y ago

Imagine you release a codec which optimizes for cis white male voice, every other kind of voice has perceptibly lower fidelity (at low bitrates). That would not go well...

shrubble 3y ago
[flagged]
- p1esk 3y ago
  An ML model might be able to, even if you can’t.
  - GaggiX 3y ago
    Achieving the gaydar, do not give this technology to Saudi Arabia.
- Edman274 3y ago
  What people have historically called a "gay lisp" is actually a hyper-articulation of /s/ or /z/, and as you might expect, /s/ and /z/ have a lot of high frequency sounds in them. Weird as it sounds there is a possible scenario where an audio codec does a worse job reproducing the audio content of gay male speech compared to straight male speech.
- stevage 3y ago
  https://en.wikipedia.org/wiki/Gay_male_speech?wprov=sfla1 https://en.wikipedia.org/wiki/Gay_male_speech?wprov=sfla1 HTH.
panzi 3y ago
Yeah, imagine a low bitrate situation where only English speaking men can still communicate. That would create quite a power imbalance.
dist-epoch 3y ago
[flagged]
- astrange 3y ago
  ^- https://knowyourmeme.com/memes/conservatives-have-one-joke https://knowyourmeme.com/memes/conservatives-have-one-joke
- gcr 3y ago
  Questions of "which users can use my product and which can't" certainly encompass political views to be sure, but they also extend further beyond. I don't see why you feel the need to argue from the position of "woke devil's advocate" here. For a politically-neutral example of why poor DEI practice can lead directly to worse products, see my sister comment about faucet sensors and black skin.
overstay8930 3y ago
Meanwhile G.711 makes all dudes sound like disgruntled middle aged union workers
numpad0 3y ago
No offense/taken, but Codec2 seem to be affected a bit for this problem.

unethical_ban 3y ago

I get your point, but the questioner wasn't being rude or angry, only curious. I think it's a valid question, too. While it isn't as important to be neutral in this instance as, say, a crime prediction model or a hiring model, it should be boilerplate to consider ML inputs for identity neutrality.

gcr 3y ago

This is a great question! Here's a related failure case that I think illustrates the issue. In my country, public restroom facilities replaced all the buttons and levers on faucets, towel dispensers, etc. with sensors that detect your hand under the faucet. Black people tell me they aren't able to easily use these restrooms. I was surprised when I heard this, but if you google this, it's apparently a thing. Why does this happen? After all, the companies that made these products aren't obviously biased against black people (outwardly, anyway). So this sort of mistake must be easy to fall into, even for smart teams in good companies. The answer ultimately boils down to ignorance. When we make hand detector sensors for faucets, we typically calibrate them with white people in mind. Of course different skin tones have different albedo and different reflectance properties, so sensors are less likely to fire. Some black folks have a workaround where they hold a (white) napkin in their hand to get the faucet to work. How do we prevent this particular case from happening in the products we build? One approach is to ensure that the development teams for skin sensors have a wide variety of skin types. If the product development team had a black guy for example, he could say "hey, this doesn't work with my skin, we need to tune the threshold." Another approach is to ensure that different skin types are reflected in the data used to fit the skin statistical models we use. Today's push for "ethics in ML" is borne out of this second path as a direct desire to avoid these sorts of problems. I like this handwashing example because it's immediately apparent to everyone. You don't have to "prioritize DEI programs" to understand the importance of making sure your skin detector works for all skin types. But, teams that already prioritize accessibility, user diversity, etc. are less likely to fall into these traps when conducting their ordinary business. For this audio codec, I could imagine that voices outside the "standard English dialect" (e.g. thick accents, different voices) might take more bytes to encode the same signal. That would raise bandwidth requirements, worsen latency, and increase data costs for these users. If the codec is designed for a standard American audience, that's less of an issue, but codecs work best when they fit reasonably well for all kinds of human physiology.

cma 3y ago
What if it is a pareto improvement: better improvement for some dialects but no worse than the earlier version for anyone. Should it be shelved or tuned down so all improvement for each dialect see gains by an exactly equal percentage?

nextaccountic 3y ago

Because this gets deployed in real world, affecting real people. Ethics don't exist only in kids curriculum.

deleted 3y ago

[deleted]

samus 3y ago

This is actually a very technical question since it means the audio codec might simply not work that well in practice as it could and should.