| Presentation | 2021-09-18 [Keynote Address] Neural Network as an Explainable Human Yugo Murawaki, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this talk, I argue that techniques developed in the field of explainable AI (XAI) have potential applications in computational human sciences. In typical XAI scenarios, artificial intelligence is seen as a technological Other that is obliged to win human trust by explaining the black box. In computational human sciences, however, it is humans that are the black box, and artificial intelligence serves as an approximation of human functions. This observation motivates us to use explanation methods to explain humans. As a concrete example, I show that neural network-based classifiers can be applied to contrastive studies. We begin by training a classifier to discriminate texts written by two groups of humans and then apply an explanation method to analyze how it performs classification. A major advantage of this approach is that the high expressive power of modern neural networks allows us to investigate context-sensitive words and long expressions in an explorative manner. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | explainable AI / neural networks / classifiers / contrastive studies |
| Paper # | TL2021-16 |
| Date of Issue | 2021-09-11 (TL) |
| Conference Information | |
| Committee | TL |
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| Conference Date | 2021/9/18(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Language Processing and Language Learning |
| Chair | Yasushi Tsubota(Kyoto Inst. of Tech.) |
| Vice Chair | Tadahisa Kondo(Kogakuin Univ.) / Kazuhiro Takeuchi(Osaka Electro-Comm. Univ.) |
| Secretary | Tadahisa Kondo(Kobe Gakuin Univ.) / Kazuhiro Takeuchi(Ferris Univ.) |
| Assistant | Nobuyuki Jincho(Miidas) / Akio Shimogori(Hakodate-ct) |
| Paper Information | |
| Registration To | Technical Committee on Thought and Language |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Keynote Address] Neural Network as an Explainable Human |
| Sub Title (in English) | A New Approach to Contrastive Studies |
| Keyword(1) | explainable AI |
| Keyword(2) | neural networks |
| Keyword(3) | classifiers |
| Keyword(4) | contrastive studies |
| 1st Author's Name | Yugo Murawaki |
| 1st Author's Affiliation | Kyoto University(Kyoto Univ.) |
| Date | 2021-09-18 |
| Paper # | TL2021-16 |
| Volume (vol) | vol.121 |
| Number (no) | TL-180 |
| Page | pp.pp.23-27(TL), |
| #Pages | 5 |
| Date of Issue | 2021-09-11 (TL) |