To start, how to confirm data is not biased?
I think there has been good progress on attributing feature input value to the downstream prediction of the model, for black-boxy models like deep nets. However I’m not sure what people do with that information to reduce bias. Removing biased features, and strongly correlated features to those seems to be a common approach.
I also had a question around these I would it could get asked I’ll repeat:
Some friends in Mexico does not believe the COVID due to some Facebook adds that have been spreading disinformation. Is it really technology responsibility to fix itself (fixing the disinformation with another AI model) would that then control what people want to see? Should people be more involved or how can it help to try to detect and prevent disinformation?
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This is a real issue. Also a lot of times if you are in minority it is genuinely hard to raise issues even if you had the domain knowledge to do so. However, being aware of issues and possible blind spots arms you with the right questions to ask when you’re able to!
The onus really must lie with the organisation to train its developers and data scientists or hire an inter-disciplinary team to mitigate ethical issues.
I think FB should flag this as misleading. They should have some responsibility.
I think this requires human inspection, preferably someone who has domain knowledge on the dataset.
Is there a resource to get a quick glance of ethical issues/debacles companies have had per company? Think BBB
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Sometimes you could try and write the formula that comes for instance from your linear regression model that’s done by looking at the intercept and the slope e.g House Price = 100 + 50 * (Number of rooms). Then you can describe how the decision boundary has been that is the least squares line. It could get hard for multiple regression since the formula is long but it’s your responsibility to look into it more.
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Is ethics different from physics or philosophy, in that consensus may be more important for ethics than extreme outliers?
Wow. Isn’t this what happened with the 5G conspiracy on #covid-19
Can I post this image on twitter? @jeremy
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https://botnik.org/content/harry-potter.html
Is another example, although it uses much simpler AI - markov chains. https://en.wikipedia.org/wiki/Markov_chain
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yes. 
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What happens when there is so much AI trolling that most of what gets scraped from the web is AI generated text, which is then used to generate even more AI generated text?
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Feedback loop!
Or you know … Inception v4. /joking
I believe they call this phenomenon “Amazon product reviews.”
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What is the citation for this, I’d like to read the paper. (If posted, I missed it)