Building Ethical AI from News Articles

Wonchul Kim, Keeheon Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Improving performance of artificial intelligence (AI) has been the most important focus of AI studies. As a result, AI is expected to replace what considered to be done by human intelligence. Additionally, human societies are willing to accept AI agents as members to collaborate with. For AI agents to be successfully integrated into human societies, the agents must understand important values in the societies. Ethics is a system of values that sustain the societies and it is considered as the most important. Therefore, there should be a way for AI agents to understand ethical values of human societies. In this paper, we show how to extract ethical values and moral values of the age from news articles using natural language processing. Our result shows that from newspaper articles ethical and moral values could be extracted and modeled for AI agents to refer. In conclusion AI can calculated ethicality of text by itself. In the future, we can develop more ethical autonomous AI agents.

Original languageEnglish
Title of host publication2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages210-217
Number of pages8
ISBN (Electronic)9781728170312
DOIs
Publication statusPublished - 2020 Sep 21
Event2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020 - Geneva, Switzerland
Duration: 2020 Sep 212020 Sep 25

Publication series

Name2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020

Conference

Conference2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020
Country/TerritorySwitzerland
CityGeneva
Period20/9/2120/9/25

Bibliographical note

Funding Information:
VIII.ACKNOWLEDGEMENT This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) [NRF-2017R1C1B1010094]; by the Ministry of Education, Sejong City, Korea. This work was supported (in part) by the Yonsei University Future-leading Research Initiative of 2017(2017-22-0067).

Publisher Copyright:
© 2020 IEEE.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications

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