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On Educating Machines (arxiv.org)
3 points by sel1 on Sep 17, 2019 | hide | past | pdf | discuss on HN

In plain words: Instead of machines learning from data, the question is how to teach them well. It gathers scattered studies on that idea and sorts them into a few research directions with enough work behind them to help the field stand on its own.

Abstract · On educating machines

Machine education is an emerging research field that focuses on the problem which is inverse to machine learning. To date, the literature on educating machines is still in its infancy. A fairly low number of methodology and method papers are scattered throughout various formal and informal publication avenues, mainly because the field is not yet well coalesced (with no well established discussion forums or investigation pathways), but also due to the breadth of its potential ramifications and research directions. In this study we bring together the existing literature and organise the discussion into a small number of research directions (out of many) which are to date sufficiently explored to form a minimal critical mass that can push the machine education concept further towards a standalone research field status.

George Leu, Jiangjun Tang
arXiv:1909.06017 · cs.AI · submitted Sep 13, 2019
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