4 ms·
You keep missing the GP's point. His point is: - computers are fast and cheap - humans are slow and expensive - slow and expensive = rarely used t
by mattmanser 4y ago
You keep missing the GP's point.
His point is:
- computers are fast and cheap
- humans are slow and expensive
- slow and expensive = rarely used technique
- rarely used technique = less chance of privacy invasion
Therefore forced human processing protects privacy.
It's a privacy concept that's quite often discussed. Pre-computers we had a certain level of privacy afforded to us that was due to the cost/speed of humans processing large amounts of data. Computers have stripped that away.
It doesn't matter if there are human processing errors as that comes out at court time.
Everything else you're saying is also kinda wrong, unfortunately. You aren't looking at the problems caused by computer efficiency, just somehow computers are magically better because they follow the same rules every time.
Firstly, the data is usually bad and messy. Like super bad and messy. Computers can't tell when data is obviously wrong, so innocent people can get caught in "computer says no" trap. So you're wrong computers are better because of that. They have no common sense.
Secondly, there ARE 100x more crime than get prosecuted. You're dead wrong about that. Most of the time that low level law breaking is skipped. Allowing mass processing means you can politically target people if you so desire with ease. Because all you have to do is look them up on the computer.
Third, computers don't forget. In the human world, when task force 1 flags you, you'll probably be forgotten. In the computer world you get a few black marks and that's it, you become ostracised from society. e.g. US's no fly list, China's social credit system.
Fourth, the computer rules can be bad. A human "black box" can (and will) explain itself. A lot of computers cannot. The Dutch recently had a big scandal because they flagged anyone with a foreign name. The UK prosecuted thousands for fraud because of a computer glitch (yes, thousands, see point 1). Any rules generated from ML is generally racist and bigoted. Etc.
- jjk166 4y agoI get GP's point, I'm arguing it's incorrect. Specifically slow and expensive != rarely used. Once you accept that your privacy is going to be violated either way, the computer is the obviously preferable option. Human processing errors are not guaranteed to come out at court time, and humans can and will hide their mistakes. Getting caught in a "computer says no" trap fundamentally requires the human using the computer to also not be able to tell when the data is obviously wrong. Computers are not supposed to be the source of common sense in either system, they are a tool. There isn't 100x more crime that isn't being prosecuted due to lack of resources. There are lots of crimes like jaywalking that our legal system leaves to discretion. 99% of the time, a person crossing the street is a non-issue. Even if you do it right in front of a cop and it would take zero resources to prosecute, it doesn't get done because we as a society don't believe it should be. We make it a crime because there is that 1% of cases where it is a problem, and we need to be able to deal with those cases, but distinguishing which is which can not be readily codified in law. The only way that AI will change this is that the decision on whether to prosecute jaywalking will be consistent. I don't see why computers not forgetting is a bad thing. We already have the means of preserving data for long periods of time. The decision on whether records should be maintained or deleted should be made based on the circumstances, not on the faultyness of the hardware. I mean if you really wanted to, you could always program a computer to delete data at random, but it's just a dumb idea. Human rules can be bad. A human black box can not spit out an error log showing the particular sequence of neurons that activated that led to its decision. It can generate a statement, but whether that statement correctly explains it's decision making process can not be determined reliably. For example a human can shoot someone because of the color of their skin, and then state that it was because they felt they were in danger despite not actually feeling that way. Detecting such a glitch is extremely difficult, and no one has a reliable method of fixing it. Falsely suspecting people because their name is foreign is a well known bug in humans. Racism and bigotry is likewise a common issue with human neural networks. When you consider the countless multitudes of erroneous decisions made by humans over the millenia, an AI falsely flagging mere thousands is an immense improvement.