There are two traditional systems of automating intelligence, one is machine learning, where you feed data into a program until it learns to distinguish patterns and "think" for itself (of course "correct" thinking is based on correct data, so if the data is biased like most humans then...)
The other form of automation is the more symbolic systems approach where each step leads to different automated outcomes. This version is more like a maze – there are a lot of options, but in the end only a finite amount of directions you can take (you cannot, for instance, fly up on the z-axis out of the maze, that would be cheating).
This paper examines one example of the earlier non-machine-learning approaches to to automation in the field of automated phone calls. What's good? What's bad? And, what's next?
The other form of automation is the more symbolic systems approach where each step leads to different automated outcomes. This version is more like a maze – there are a lot of options, but in the end only a finite amount of directions you can take (you cannot, for instance, fly up on the z-axis out of the maze, that would be cheating).
This paper examines one example of the earlier non-machine-learning approaches to to automation in the field of automated phone calls. What's good? What's bad? And, what's next?
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