In this episode, Byron talks about biases. For more on Artificial Intelligence: https://voicesinai.com https://gigaom.com https://byronreese.com https://ift.tt/31WftGA... Transcript: One thing to be aware of is that when we build artificial intelligence it's pretty easy for us to accidentally encode our own biases. Because in the end, we are the ones who are training the system and telling it right and wrong as it tries to sort through the universe. To illustrate this imagine someone who has green blue color blindness and they can’t see the difference between blue and green. So they feed examples of colors of objects and say this is green, and this is green, and this is green, and this one's green, and they would say that for blue things and green things. What they will end up doing of course is make a color blind artificial intelligence. One that has the exact same limitation that the human who trained it has. In short, we create systems in essence better able to do things than we are, but creating systems, as it were, in our own image.
2019年8月23日星期五
Beware of Biased AI
In this episode, Byron talks about biases. For more on Artificial Intelligence: https://voicesinai.com https://gigaom.com https://byronreese.com https://ift.tt/31WftGA... Transcript: One thing to be aware of is that when we build artificial intelligence it's pretty easy for us to accidentally encode our own biases. Because in the end, we are the ones who are training the system and telling it right and wrong as it tries to sort through the universe. To illustrate this imagine someone who has green blue color blindness and they can’t see the difference between blue and green. So they feed examples of colors of objects and say this is green, and this is green, and this is green, and this one's green, and they would say that for blue things and green things. What they will end up doing of course is make a color blind artificial intelligence. One that has the exact same limitation that the human who trained it has. In short, we create systems in essence better able to do things than we are, but creating systems, as it were, in our own image.
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