41–48 of 48 posts
Watch this: https://youtu.be/stHLrBs-_iE (Based off of the Stanford Prof’s example during a TED talk of using <$100 to assassinate people with AI, A CO2 canister, a nail, and a drone).
Can we chill with the throbbing bass though?
For example, they consider deep fakes in general to be awful, because of the potential for abuse. Should we just throw out deep fakes? Should we perhaps restrict their usage to licensed parties?
They also list Tay the chat bot as being awful because some trolls temporally hijacked it and got it to repeat back some racist stuff for a few weeks before it was re-calibrated. What does the author suggest? That Microsoft should never have made Tay public until they could 100% guarantee that no trolls would ever abuse it, even for a little bit?
Gender inference tools are written off as discrimination, because they could be used to discriminate against people. But they could just as well be used against AGAINST discrimination, by helping detect and document systemic discrimination. I think especially tools for analyzing populations present incredible benefits to help people, more so than potentials for abuse.
AI that can be used to detect genetic disease can save countless lives and reduce suffering. But it is bad because potential employers could maybe abuse it??
And a lot of these awful policies don't use the AI directly, they merely use the AI as a justification for what they were going to do already anyway. Indeed, you could go back 50 years and find "AI" being used to justify problematic policies. I'm sure that Oil executives, criminal justice lobbyists, and climate change deniers have all been able to algorithm based evidence for their agendas. Don't blame the algorithms, blame the people.
Earlier quoted context omitted.
>that doesn't mean we give Engineers and Researchers free reign to package, publish, and distribute AI software that falls short of its promise And who is going to monitor and enforce this? You?
Perhaps by "give free reign to [x]" they just mean "not consider morally liable for [doing x]"?
I have worked on crime analysis software to help people. It is important to me to minimize the number of people getting hurt. And when the data shows that most people getting in fights on the subway are black, what then? What would you have us do?
We should dig deeper and find real solutions, not delude ourselves that these problems exist.
And the world isn't as rosy as we might imagine it is. There's are some really uncomfortable truths out there. But I think we should confront and understand these things.
Earlier quoted context omitted.
Perhaps by "give free reign to [x]" they just mean "not consider morally liable for [doing x]"?
Trying to build in safeguards before deploying anything is an unreasonable standard, and would severely cripple the good work that many of us are trying to do. I have worked on crime analysis software to help people. It is important to me to minimize the number of people getting hurt. And when the data shows that most people getting in fights on the subway are black, what then? What would you have us do? We should di…
My comment is not arguing for or against the claim that the software should or shouldn't have whatever safeguards. It was extremely limited in its scope.
So, I'm not sure why you chose my comment to respond to with your "darkly hinting" comment mr. "apostacy".
This list presents an incredibly pessimistic and alarmist view on these technologies, assuming only worst case abuses. And I don't know what solutions are advocated, so it feels like it is just against these technologies in general. And it is not fair to blame these mostly helpful tools for the awful things some people may use them for. For example, they consider deep fakes in general to be awful, because of the pote…
This list presents an incredibly pessimistic and alarmist view on these technologies, assuming only worst case abuses. And I don't know what solutions are advocated, so it feels like it is just against these technologies in general. And it is not fair to blame these mostly helpful tools for the awful things some people may use them for. For example, they consider deep fakes in general to be awful, because of the pote…
This list presents an incredibly pessimistic and alarmist view on these technologies, assuming only worst case abuses. And I don't know what solutions are advocated, so it feels like it is just against these technologies in general. And it is not fair to blame these mostly helpful tools for the awful things some people may use them for. For example, they consider deep fakes in general to be awful, because of the pote…
Your claim of "mostly helpful tools" was not backed up with facts or even an attempt at explanation.
And then I gave several examples and an explanation. But to reiterate, tools that help us increase our understand of society are helpful, and can be used for good.
The list assumes that a tool that can help discern someone's gender will and can only be used to treat someone unfairly. But a researcher could just as well use exactly the same tools to analyze the gender composition of a set of people, for the purposes of advocating for them.
FOR EXAMPLE, in this repo:
https://github.com/waterdatacollaborative/Get-the-Lead-Out
What if a researcher were to use data mining tools to find out more information about the children most impacted by lead in the water, for the purposes of helping them. (And some have)
Is that an "awful" use of AI?
I would assert that actually yes some of these tools are quite helpful.
Earlier quoted context omitted.
Ah, yes, but that's not really the point, is it? COMPAS points out an uncomfortable trend ("violent crime is more prevalent in black communities...") but applies it in a way that is bad ("...and therefore black people should get longer criminal sentences for the same crime"). We both agree, I'm sure, that socioeconomics and race shouldn't meaningfully impact sentence length. We may also agree that it often does. What…
You are deliberately twisting it. The crime stats says "violent crime is more prevalent in black communities...", but no AI/ML will produce the conclusion "...and therefore black people should get longer criminal sentences for the same crime". They are completely irrelevant. The AI model will simply conclude that race would be a factor when you are looking at crime rate, or posterior probability when a violent crime…
Of course math doesn’t have an agenda, but we aren’t talking about the actual algorithm having a human bias. We are talking about the application of math by humans to human problems using data sets curated by humans. Using math doesn’t purge the biases of all those humans from the system.