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So what happens if any of the humans listed below is an attacker? And the system they're attacking is the very important real-world system which they are all nominally working together to automate? The criminal justice system or the healthcare system?https://twitter.com/qntm/status/1030837348630708224 …
Mickens gives a high-level goal of computer security as "ensuring that systems do the right thing, even in the presence of malicious inputs". In a machine learning scenario, inputs come from a whole lot of places which are not the user
Or, of course, you can secretly replace the "A.I."/"machine decision-maker" with a highly biased human or collection of humans Yeah, you were randomly selected by this button which I press when I want the machine to randomly select you
* Machine learning is money laundering for bias * Machine learning is money laundering for responsibility * People do not launder their money by ACCIDENT * Assign responsibility to humans
Machines are going to be given control of the world so that they can more effectively and deniably implement the biases of the people who create and install them
So to sum up, generally I agree with James Mickens but I prefer to read less incompetence and more malice into the machine learning situation. I think this is a sound and necessary defensive strategy, regardless of the actual amount of malice involved
"No, I'm not paranoid! I'm just rigorously going through the *motions* of paranoia in case your machine learning algorithm *inadvertently* goes through the *motions* of drilling a hole in the keel of human civilisation"
Passive-aggressively assume good faith. "How did you ensure that this system does not reflect your own biases? How did you ensure that this system can't be used for abuse? ...You're looking uncomfortable. Don't worry, we can extend this meeting for as long as necessary"
This is also a good one, neglected to add it to the thread. Reason 2.5 for not replacing humans with machines in important decision-making roleshttps://twitter.com/nyanotech/status/1030898183369457664 …
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