Abstract
Humans and other animals are often touted as examples of systems that possess general intelligence. However, rarely if ever do they achieve high levels of intelligence and autonomy on their own: they are raised by parents and caregivers in a society with peers and seniors, who serve as teachers and examples. Current methods for developing artificial learning systems typically do not account for this. This paper gives a taxonomy of the main methods for raising / educating naturally intelligent systems and provides examples for how these might be applied to artificial systems. The methods are heuristic rewarding, decomposition, simplification, situation selection, teleoperation, demonstration, coaching, explanation, and cooperation. We argue that such tutoring methods that provide assistance in the learning process can be expected to have great benefits when properly applied to certain kinds of artificial systems.
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Bieger, J., Thórisson, K.R., Garrett, D. (2014). Raising AI: Tutoring Matters. In: Goertzel, B., Orseau, L., Snaider, J. (eds) Artificial General Intelligence. AGI 2014. Lecture Notes in Computer Science(), vol 8598. Springer, Cham. https://doi.org/10.1007/978-3-319-09274-4_1
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DOI: https://doi.org/10.1007/978-3-319-09274-4_1
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