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I don't think that's quite correct, many (most?) kinds of AI achieve things which are difficult or impossible for humans to do, but that doesn't mean you can't

I don't think that's quite correct, many (most?) kinds of AI achieve things which are difficult or impossible for humans to do, but that doesn't mean you can't figure out why a decision was made afterwards. There are some scenarios where that isn't possible, but... if nobody knows why decisions impacting people's lives are made and it isn't possible to determine what they were done for, is that something we really want?

bobcostas55 9y ago
>if nobody knows why decisions impacting people's lives are made and it isn't possible to determine what they were done for, is that something we really want? We do this every day with human cognition and nobody complains.
- montrose 9y ago
  It's too bad your comment is buried so far down in the conversation, because this is probably the most insightful point I've seen on the internet today. And not only do we do this, we have to.
  - ethbro 9y ago
    I don't think that's an accurate analogy, at least at the enterprise level. Generally speaking, individuals do not make decisions. They may influence decisions or find novel ways to apply rules, but anything organizationally important is written down somewhere. Typically for legal purposes.
- danieltillett 9y ago
  Yes we do this everyday, but there is lots of complaining.
- smsm42 9y ago
  It is not exactly true that nobody complains. There a lot of discrimination complaints to go around. But since we do not have means to open the brain and check what was the reason for this or that decision, deducing motivations is hard (unless you are commenting on internet, where everybody knows everybody else's motivations and is not afraid to explain it voluminously to each other). It would also be hard with algorithms, so basically the approach seems to be "reducing the problem to one we already know" - i.e. switching algorithmic unscrutability for human unscrutability and hoping that humans would do better or at least in won't be worse than what we have already been dealing with for millenia.
- ThePhysicist 9y ago
  I think one of the reasons that we have a higher standard for algorithmic decision making is the fact that algorithms are used at scale: For example, for a classification task we usually train an algorithm on labeled data (i.e. good debtor vs. bad debtor). When trained, we apply the algorithms to ALL future decisions on whom to give a credit. This makes algorithms so dangerous as compared to humans, because if 10 out of 1000 bankers are racist and discriminate against certain groups of people we still have 990 that don't. If our algorithm is trained on data that contains racism it will discriminate in every single case if it has the data to do so.

bobcostas55 9y ago

>if nobody knows why decisions impacting people's lives are made and it isn't possible to determine what they were done for, is that something we really want? We do this every day with human cognition and nobody complains.

montrose 9y ago
It's too bad your comment is buried so far down in the conversation, because this is probably the most insightful point I've seen on the internet today. And not only do we do this, we have to.
- ethbro 9y ago
  I don't think that's an accurate analogy, at least at the enterprise level. Generally speaking, individuals do not make decisions. They may influence decisions or find novel ways to apply rules, but anything organizationally important is written down somewhere. Typically for legal purposes.
danieltillett 9y ago
Yes we do this everyday, but there is lots of complaining.
smsm42 9y ago
It is not exactly true that nobody complains. There a lot of discrimination complaints to go around. But since we do not have means to open the brain and check what was the reason for this or that decision, deducing motivations is hard (unless you are commenting on internet, where everybody knows everybody else's motivations and is not afraid to explain it voluminously to each other). It would also be hard with algorithms, so basically the approach seems to be "reducing the problem to one we already know" - i.e. switching algorithmic unscrutability for human unscrutability and hoping that humans would do better or at least in won't be worse than what we have already been dealing with for millenia.
ThePhysicist 9y ago
I think one of the reasons that we have a higher standard for algorithmic decision making is the fact that algorithms are used at scale: For example, for a classification task we usually train an algorithm on labeled data (i.e. good debtor vs. bad debtor). When trained, we apply the algorithms to ALL future decisions on whom to give a credit. This makes algorithms so dangerous as compared to humans, because if 10 out of 1000 bankers are racist and discriminate against certain groups of people we still have 990 that don't. If our algorithm is trained on data that contains racism it will discriminate in every single case if it has the data to do so.