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>We’re at a tipping point. It’s never been more essential that we create a movement toward trustworthy AI — and this requires collaboration with the brightest m

>We’re at a tipping point. It’s never been more essential that we create a movement toward trustworthy AI — and this requires collaboration with the brightest minds working on AI technology today. Is "trustworthy AI" something we really want? I don't think I'll ever trust a LLM, no matter how many "ethicists" say otherwise.

realce 4y ago
Manufacturing Consent imo
lyu07282 4y ago
You can always just fire the ethicists once something they say will effect your bottom line. This is all just ai ethics white washing, for some reason we have to pretend for-profit corporations will be responsible shepard's of the ai revolution. I'm not exactly sure why we have to pretend though, it's not like we could ever actually do anything about it even if a majority understood it's apocalyptic potential so it really doesn't matter either way. Just look at climate change inaction.
- Jensson 4y ago
  Why hire them in the first place? Only time I hear about those teams is when they get fired.
  - sebzim4500 4y ago
    I guess people hope they might come up with something insightful, and are disappointed because the field is entirely bullshit.
  - krisoft 4y ago
    > Only time I hear about those teams is when they get fired. It is a risk mitigation measure. The company is accused of bad things, and the higher ups want to be able to say that they are doing something about it. They create a team who will investigate such things and make recommendations. For example before elon times twitter had a problem. They had a feature which picked the "most important" part of an image so they can display the images automatically on mobile. The problem they had is that someone found an image where there were two politicians side by side and the algorithm was focusing only on the white one, ignoring the black one. It was quite literally "marginalising" the black politician. Not a good look. Not the end of the world. The walls were not crumbling yet. The advertisers haven't whitdrawn their budgets yet but you know, you don't want to be known as "that racist social network". In a situation like this one possible solution is to start a small team, give them a bit of budget and task them figuring out if the machine is racist and what can be done about it. Preferably you fill the team with well-spoken academic types to give the effort more credence. (without actually, you know, cutting into the profit) This is obviously the cynical view. The less cynical view is that you want a team who prevents issues like that from getting into production. Same way you have legal to tell you what is and isn't legal, you have AI ethics to tell you what is and isn't consistent with the ethics of your organisation. Someone who doesn't do the work itself, but helps other teams by reviewing their proposals for potential issues. For example in the "picking the important part of an image" if they were in the room during the design phase they could have asked why someone thinks this task should be done by the machine? Couldn't we ask a user what they feel is the right cropping of their image for mobile? And only if it must be done at all would they ask if the developers have tested their solution on representative test datasets.

realce 4y ago

Manufacturing Consent imo

lyu07282 4y ago

You can always just fire the ethicists once something they say will effect your bottom line. This is all just ai ethics white washing, for some reason we have to pretend for-profit corporations will be responsible shepard's of the ai revolution. I'm not exactly sure why we have to pretend though, it's not like we could ever actually do anything about it even if a majority understood it's apocalyptic potential so it really doesn't matter either way. Just look at climate change inaction.

Jensson 4y ago
Why hire them in the first place? Only time I hear about those teams is when they get fired.
- sebzim4500 4y ago
  I guess people hope they might come up with something insightful, and are disappointed because the field is entirely bullshit.
- krisoft 4y ago
  > Only time I hear about those teams is when they get fired. It is a risk mitigation measure. The company is accused of bad things, and the higher ups want to be able to say that they are doing something about it. They create a team who will investigate such things and make recommendations. For example before elon times twitter had a problem. They had a feature which picked the "most important" part of an image so they can display the images automatically on mobile. The problem they had is that someone found an image where there were two politicians side by side and the algorithm was focusing only on the white one, ignoring the black one. It was quite literally "marginalising" the black politician. Not a good look. Not the end of the world. The walls were not crumbling yet. The advertisers haven't whitdrawn their budgets yet but you know, you don't want to be known as "that racist social network". In a situation like this one possible solution is to start a small team, give them a bit of budget and task them figuring out if the machine is racist and what can be done about it. Preferably you fill the team with well-spoken academic types to give the effort more credence. (without actually, you know, cutting into the profit) This is obviously the cynical view. The less cynical view is that you want a team who prevents issues like that from getting into production. Same way you have legal to tell you what is and isn't legal, you have AI ethics to tell you what is and isn't consistent with the ethics of your organisation. Someone who doesn't do the work itself, but helps other teams by reviewing their proposals for potential issues. For example in the "picking the important part of an image" if they were in the room during the design phase they could have asked why someone thinks this task should be done by the machine? Couldn't we ask a user what they feel is the right cropping of their image for mobile? And only if it must be done at all would they ask if the developers have tested their solution on representative test datasets.