6 ms·

> Corporations can use them to be unaccountable. Insider trading? No, that was our "algorithm". Racist policies? Oops, sorry that was just our bot. I would say

• johnchristopher 7y ago
  "Our" algorithm ? I was under the impression that AI were generating their own algorithms.
  • azdacha 7y ago
    In a sense you are building an algorithm but with different means from the usual ones. It is built trough compilation of a large amount of data using the well known machine learning algorithms. Tbh and especially in this case these are vocabulary terminations we should not but stuck on.
  • nradov 7y ago
    It's an algorithm, just at a higher level of abstraction. Turtles all the way down.
• pjc50 7y ago
  "The input to our algorithm is the entire content of the Alexa top 1,000 websites over the last year". Good luck finding the secret signal in that one. Similarly, there's plenty of evidence that algorithms can reconstruct discrimination from inputs other than skin color - names are the obvious example, but address seems a likely risk too. Algorithms need anti-racism quality control on their output.
• windsurfer 7y ago
  And tell me, how can you verify that these were the inputs used? How can you check to see how those inputs were used within the algorithm? How can you audit such a system?
  • xwdv 7y ago
    You rebuild the system using the same inputs and initial conditions and observe the outcome. Thank you, next.
    • naasking 7y ago
      Talk about underplaying the difficulties. Computer science needed a whole new package system (Nix) just to guarantee reproducible builds. Compilation is pretty much the definition of a pure input/output function, and most builds are simply not reproducible. If even builds aren't reproducible, good luck reproducing anything more complex like machine learning.
      • xwdv 7y ago
        Auditing is a complicated process, if you don’t want to do the work you’ll just have to take their word for it.
        • naasking 7y ago
          The problem is the feasibility of auditing, not whether the motivation exists. And no, taking their word for it is not adequate.
          • xwdv 7y ago
            Then what do you propose be done? If you accuse someone of having an extremely racist AI you need a way to prove they set out to make it that way. You don’t just get to say “It’s racist” and shut it down.
            • pjc50 7y ago
              You look at the outcome distribution.
              • naasking 7y ago
• bart_spoon 7y ago
  How would that solve anything? Most machine learning algorithms being used today are black boxes and the people implementing them often have little understanding of exactly what transformations the model ends up making between the inputs and the outputs. Its entirely possible for seemingly-innocuous inputs to pick up outright problematic features (i.e. skin color from a photo id) or indirectly problematic features (i.e. income level and address located in an area predominantly populated by minorities) that its outputs hinge on. If anything, the issues with machine learning are even more problematic that what the OP posted, as simply identifying that something like systemic racism in a machine learning model can be very hard to identify.
• twirlip 7y ago
  Biased algorithms is a thing. We are often blind to that realization because we are often blind to our own biases.