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Main Authors: Wei, Mengyi, Zhang, Puzhen, Chen, Chuan, Chen, Dongsheng, Zuo, Chenyu, Meng, Liqiu
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2406.14123
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author Wei, Mengyi
Zhang, Puzhen
Chen, Chuan
Chen, Dongsheng
Zuo, Chenyu
Meng, Liqiu
author_facet Wei, Mengyi
Zhang, Puzhen
Chen, Chuan
Chen, Dongsheng
Zuo, Chenyu
Meng, Liqiu
contents Public participation is indispensable for an insightful understanding of the ethics issues raised by AI technologies. Twitter is selected in this paper to serve as an online public sphere for exploring discourse on AI ethics, facilitating broad and equitable public engagement in the development of AI technology. A research framework is proposed to demonstrate how to transform AI ethics-related discourse on Twitter into coherent and readable narratives. It consists of two parts: 1) combining neural networks with large language models to construct a topic hierarchy that contains popular topics of public concern without ignoring small but important voices, thus allowing a fine-grained exploration of meaningful information. 2) transforming fragmented and difficult-to-understand social media information into coherent and easy-to-read stories through narrative visualization, providing a new perspective for understanding the information in Twitter data. This paper aims to advocate for policy makers to enhance public oversight of AI technologies so as to promote their fair and sustainable development.
format Preprint
id arxiv_https___arxiv_org_abs_2406_14123
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Mapping AI Ethics Narratives: Evidence from Twitter Discourse Between 2015 and 2022
Wei, Mengyi
Zhang, Puzhen
Chen, Chuan
Chen, Dongsheng
Zuo, Chenyu
Meng, Liqiu
Computers and Society
Public participation is indispensable for an insightful understanding of the ethics issues raised by AI technologies. Twitter is selected in this paper to serve as an online public sphere for exploring discourse on AI ethics, facilitating broad and equitable public engagement in the development of AI technology. A research framework is proposed to demonstrate how to transform AI ethics-related discourse on Twitter into coherent and readable narratives. It consists of two parts: 1) combining neural networks with large language models to construct a topic hierarchy that contains popular topics of public concern without ignoring small but important voices, thus allowing a fine-grained exploration of meaningful information. 2) transforming fragmented and difficult-to-understand social media information into coherent and easy-to-read stories through narrative visualization, providing a new perspective for understanding the information in Twitter data. This paper aims to advocate for policy makers to enhance public oversight of AI technologies so as to promote their fair and sustainable development.
title Mapping AI Ethics Narratives: Evidence from Twitter Discourse Between 2015 and 2022
topic Computers and Society
url https://arxiv.org/abs/2406.14123