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Ok, so I guess Hacker News has decided that data can only be 100% biased or 0% unbiased, but nothing in-between. Yes, almost all data is biased... of course.

Ok, so I guess Hacker News has decided that data can only be 100% biased or 0% unbiased, but nothing in-between. Yes, almost all data is biased... of course. Some data is 100% biased. Some data is 1% biased. How about we try to collect data and then weigh it such that what we feed to the AI during training is as unbiased as possible, given a certain amount of effort? You know that you can actually influence what data you feed to the AI, right? Or how much the training takes some data into account vs some other data, I guess. You know that you can create a metric for measuring bias, right? You know that even if you are not capable of being 100% unbiased, you can work towards that goal, right? You know that there are plenty of smart people who can come up with ideas for eliminating (or mitigating) sources of errors when measuring bias, right? I hope you begin to see the solution at hand.

pixl97 4y ago
>You know that you can create a metric for measuring bias, right? Yes, and no. So, lets go back in the past and do data collection in 1840 from citizens with the right to vote. We'll take one sample from New York City and the other from Mobile Alabama. Now what do you think happens when you query that dataset on views about slavery? Your data is inherently biased. In fact one could say there is no middle ground here.
- wizeman 4y ago
  I'm sorry, I'm lacking the historical knowledge to answer your question. My view is that a measure of "bias" should reflect what a representative sample of the entire population [1] would answer if you asked them how biased the AI is. Of course, if you live in a historical context where slavery is socially acceptable, then the answers the AI gives you will reflect that environment. It's no different from raising a human person in that same environment. The problem is, you can't necessarily know whether something is good or bad without the benefit of hindsight. Thinking you know better than everyone else and then imposing your view may just serve to magnify your mistakes. However, one would think that, once we have that technology, a sufficiently intelligent AI would start to have opinions of their own about what is moral/ethical vs what isn't, that isn't strictly a representation of the training data. [1] of the world even, if that's the target market for the AI.

pixl97 4y ago

>You know that you can create a metric for measuring bias, right? Yes, and no. So, lets go back in the past and do data collection in 1840 from citizens with the right to vote. We'll take one sample from New York City and the other from Mobile Alabama. Now what do you think happens when you query that dataset on views about slavery? Your data is inherently biased. In fact one could say there is no middle ground here.

wizeman 4y ago
I'm sorry, I'm lacking the historical knowledge to answer your question. My view is that a measure of "bias" should reflect what a representative sample of the entire population [1] would answer if you asked them how biased the AI is. Of course, if you live in a historical context where slavery is socially acceptable, then the answers the AI gives you will reflect that environment. It's no different from raising a human person in that same environment. The problem is, you can't necessarily know whether something is good or bad without the benefit of hindsight. Thinking you know better than everyone else and then imposing your view may just serve to magnify your mistakes. However, one would think that, once we have that technology, a sufficiently intelligent AI would start to have opinions of their own about what is moral/ethical vs what isn't, that isn't strictly a representation of the training data. [1] of the world even, if that's the target market for the AI.