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I read it more as Google's blind faith in algorithms finally being loudly and publicly discredited. Baked deeply into Google's corporate DNA is the unquestioned

I read it more as Google's blind faith in algorithms finally being loudly and publicly discredited. Baked deeply into Google's corporate DNA is the unquestioned assumption that all you have to do to solve a problem -- any problem -- is throw clever algorithms and compute power at it. Which I suppose might still turn out to be true, but Google has picked off all the low-hanging fruit and is now hitting problems that seem to be well beyond their capabilities to solve algorithmically. But since the whole company is built on the assumption that this would never happen, the are incapable of confronting and dealing with it.

mtgx 9y ago
Algorithms can have bias, too. Like for instance, in the last election, Google removed the more negative expressions that would be suggested alongside politicians' names. That wasn't just the Algorithm™ -- it was Google deciding that. There are likely hundreds of such "manual" decisions within its search algorithms.
- zaarn 9y ago
  Algorithms are generally incapable of bias. What an algorithm does is a perfect reproduction of it's instructions plus it's parameters. The actual bias is either by the designer by making an algorithm that does not fit the intended use properly or by using flawed parameters. Also known as; garbage in, garbage out. The pipe in between doesn't care if it's garbage. In your example, this was a decision by a Google engineer or c-level, not the algorithm. The algorithm did as it was told to in exactly the way it was designed without bias or error.
  - ForHackernews 9y ago
    > Algorithms are generally incapable of bias. This is nonsense unless you define-down "bias" in such a way as to mean "performing contrary to the deterministic result of its implementation" (which seems to be what you're doing, and I agree is impossible). A more sensible definition of bias might be something like "preferentially favouring one outcome over another for reasons unrelated (or even contrary) to the core purpose of the software". Imagine a vending machine that when prompted generically by a user saying "I'm thirsty" always provided sugary soda instead of bottled water. Modern machine learning algorithms are extremely complex and opaque, and depending on the dataset they're trained on, and the features they're trained to focus on, they can very easily wind up just encoding human biases. https://www.theregreview.org/2017/10/10/cramer-bias-computer-algorithms/ https://www.theregreview.org/2017/10/10/cramer-bias-computer...
2sk21 9y ago
Yes - the fundamental limits to learning by induction
ConceptJunkie 9y ago
I don't think it's blind faith in algorithms, but that Google is using algorithms, because the only other alternative is to hire 100,000 people to do unrewarding grunt work classifying this stuff. They are trying to provide more services using the tools they've develop. Maybe they've exceeded their reach, but I wouldn't blame that on a "blind faith" in algorithms. And no, I am not a fan of Google. I think they are evil.

mtgx 9y ago

Algorithms can have bias, too. Like for instance, in the last election, Google removed the more negative expressions that would be suggested alongside politicians' names. That wasn't just the Algorithm™ -- it was Google deciding that. There are likely hundreds of such "manual" decisions within its search algorithms.

zaarn 9y ago
Algorithms are generally incapable of bias. What an algorithm does is a perfect reproduction of it's instructions plus it's parameters. The actual bias is either by the designer by making an algorithm that does not fit the intended use properly or by using flawed parameters. Also known as; garbage in, garbage out. The pipe in between doesn't care if it's garbage. In your example, this was a decision by a Google engineer or c-level, not the algorithm. The algorithm did as it was told to in exactly the way it was designed without bias or error.
- ForHackernews 9y ago
  > Algorithms are generally incapable of bias. This is nonsense unless you define-down "bias" in such a way as to mean "performing contrary to the deterministic result of its implementation" (which seems to be what you're doing, and I agree is impossible). A more sensible definition of bias might be something like "preferentially favouring one outcome over another for reasons unrelated (or even contrary) to the core purpose of the software". Imagine a vending machine that when prompted generically by a user saying "I'm thirsty" always provided sugary soda instead of bottled water. Modern machine learning algorithms are extremely complex and opaque, and depending on the dataset they're trained on, and the features they're trained to focus on, they can very easily wind up just encoding human biases. https://www.theregreview.org/2017/10/10/cramer-bias-computer-algorithms/ https://www.theregreview.org/2017/10/10/cramer-bias-computer...

2sk21 9y ago

Yes - the fundamental limits to learning by induction

ConceptJunkie 9y ago

I don't think it's blind faith in algorithms, but that Google is using algorithms, because the only other alternative is to hire 100,000 people to do unrewarding grunt work classifying this stuff. They are trying to provide more services using the tools they've develop. Maybe they've exceeded their reach, but I wouldn't blame that on a "blind faith" in algorithms. And no, I am not a fan of Google. I think they are evil.