Latest effort by NIST toward a standard identifying AI biases is worthy of a close look, and can be clearly useful including in the case of AI-based self-driving cars.
As you might directly guess, trying to pin down the specifics underlying these principles can be extremely hard to do. Even more so, the effort to turn those broad principles into something entirely tangible and detailed enough to be used when crafting AI systems is also a tough nut to crack.
For now, we can take a closer look at the proposed three categories and see what kind of a hand we’ve been dealt with so far .Here’s what the NIST document says: “Systemic biases result from procedures and practices of particular institutions that operate in ways which result in certain social groups being advantaged or favored and others being disadvantaged or devalued.
The type of AI that I am focusing on consists of the non-sentient AI that we have today. If we wanted to wildly speculate aboutAI, this discussion could go in a radically different direction. A sentient AI would supposedly be of human quality. You would need to consider that the sentient AI is the cognitive equivalent of a human. More so, since some speculate we might have super-intelligent AI, it is conceivable that such AI could end up being smarter than humans .
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