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AI has a lot more potential for bias than humans. It depends on the input data which is likely heavily biased based on other data set results like face detectio

by gibolt 7y ago

AI has a lot more potential for bias than humans. It depends on the input data which is likely heavily biased based on other data set results like face detection. It will only amplify any small bias present in the data.

solveit 7y ago
So will humans. With AI, the model and training data are auditable and, if necessary, modifiable. You can't audit a person's life history and you can only really modify a grader by replacing them, and it's much less socially damaging to retrain a model than to fire an employee. AI certainly has a lot of potential for bias, but claims that AI bias is somehow worse than good old human bias always seem shoddily supported (Note I'm not claiming it's untrue. Just that it's never been shown to my satisfaction, which is not surprising given how quickly AI is changing. It may well be true.)
- kazinator 7y ago
  > but claims that AI bias is somehow worse than good old human bias always seem shoddily supported Well, AI bias can combine sampling bias with human bias. Like say we train the AI with the output of only 10 human paper graders, all chosen from the same school district. Due to the sampling bias, that data could create markedly more (or less!) bias than the entire population of human paper-graders. The resulting AI will ideally mimic those 10 humans, though; it shouldn't show more bias than that group. If those 10 are flaring racists, and grade accordingly, the AI will be the same. (In fact, we hope that it will be the same, if the algorithm actually works in mimicking human grading.)
Spivak 7y ago
It's amazing to see how the general opinion of CS people has completely shifted in the last few years from "algorithmic scoring is important in removing the bias from human graders" to the exact opposite.
- Larrikin 7y ago
  That was the hope, but all the most effective methods suffer from data collection bias and the studies show that makes them worst than implicitly biased humans.
- kazinator 7y ago
  If we can quantify the bias in the machine, that gives us an opportunity to close the feedback loop and control the bias. The bias comes from the human-generated training data in the first place; the machine isn't introducing its own. For instance, the machine has no inherent concept of disparaging someone's language because it's from an identifiable inner city dialect. If it picks up that bias, at least it will apply it consistently. When we investigate the machine, the machine will not know that it's being investigated and will not try to conceal its bias from us. On the other hand, eliminating bias from humans basically means this: producing a new litter of small humans and teaching them better than their predecessors.
  - gibolt 7y ago
    If...
- peteradio 7y ago
  It is important but its not ready.
- deleted 7y ago
  [deleted]

by gibolt 7y ago

solveit 7y ago

So will humans. With AI, the model and training data are auditable and, if necessary, modifiable. You can't audit a person's life history and you can only really modify a grader by replacing them, and it's much less socially damaging to retrain a model than to fire an employee. AI certainly has a lot of potential for bias, but claims that AI bias is somehow worse than good old human bias always seem shoddily supported (Note I'm not claiming it's untrue. Just that it's never been shown to my satisfaction, which is not surprising given how quickly AI is changing. It may well be true.)

kazinator 7y ago
> but claims that AI bias is somehow worse than good old human bias always seem shoddily supported Well, AI bias can combine sampling bias with human bias. Like say we train the AI with the output of only 10 human paper graders, all chosen from the same school district. Due to the sampling bias, that data could create markedly more (or less!) bias than the entire population of human paper-graders. The resulting AI will ideally mimic those 10 humans, though; it shouldn't show more bias than that group. If those 10 are flaring racists, and grade accordingly, the AI will be the same. (In fact, we hope that it will be the same, if the algorithm actually works in mimicking human grading.)

Spivak 7y ago

It's amazing to see how the general opinion of CS people has completely shifted in the last few years from "algorithmic scoring is important in removing the bias from human graders" to the exact opposite.

Larrikin 7y ago
That was the hope, but all the most effective methods suffer from data collection bias and the studies show that makes them worst than implicitly biased humans.
kazinator 7y ago
If we can quantify the bias in the machine, that gives us an opportunity to close the feedback loop and control the bias. The bias comes from the human-generated training data in the first place; the machine isn't introducing its own. For instance, the machine has no inherent concept of disparaging someone's language because it's from an identifiable inner city dialect. If it picks up that bias, at least it will apply it consistently. When we investigate the machine, the machine will not know that it's being investigated and will not try to conceal its bias from us. On the other hand, eliminating bias from humans basically means this: producing a new litter of small humans and teaching them better than their predecessors.
- gibolt 7y ago
  If...
peteradio 7y ago
It is important but its not ready.
deleted 7y ago
[deleted]