Ethical Risk and Pathway of AIGC Cross-Modal Content Generation Technology

This study analyses the core technologies underlying AI-generated cross-modal content (AIGC), identifying data, algorithms, and computing power as the fundamental pillars supporting AIGC operation. And data are recognized as the underlying logic driving AI's continuous development and the source of ethical issues within AIGC. By integrating Gilbert Hottois' concept of technological accompaniment, this research incorporates multiple stakeholders to dissolve the binary opposition between humans and machines. This study explores pathways to scientifically and positively advance AIGC technologies at the micro, medium, and macro levels. It advocates for human‒machine symbiosis, enhances the frequency and potential of users' digital interactions, improves their understanding and autonomy in applications, and promotes digital literacy in the intelligent era. Additionally, it emphasizes the importance of government-led initiatives and global dialog to establish a multistakeholder regulatory framework and conventions, aiming to create a more harmonious human‒machine community with a shared future.

Authors

Institutions

Publication Details

Journal
International Journal of Social Sciences & Humanities
Published
2024-09-23
DOI
https://doi.org/10.58885/ijllis.v9i1.85.lj
Citations
4
Primary Topic
Educational Reforms and Innovations
Type
article
Field-Weighted Citation Impact
1.26
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ethical Risk and Pathway of AIGC Cross-Modal Content Generation Technology

Ling Jiang, Yiting Zhang
4 citations
International Journal of Social Sciences & Humanities
Educational Reforms and Innovations
1.26
article

Ethical Risk and Pathway of AIGC Cross-Modal Content Generation Technology

Ling Jiang, Yiting Zhang
article en
4 citations

Abstract

This study analyses the core technologies underlying AI-generated cross-modal content (AIGC), identifying data, algorithms, and computing power as the fundamental pillars supporting AIGC operation. And data are recognized as the underlying logic driving AI's continuous development and the source of ethical issues within AIGC. By integrating Gilbert Hottois' concept of technological accompaniment, this research incorporates multiple stakeholders to dissolve the binary opposition between humans and machines. This study explores pathways to scientifically and positively advance AIGC technologies at the micro, medium, and macro levels. It advocates for human‒machine symbiosis, enhances the frequency and potential of users' digital interactions, improves their understanding and autonomy in applications, and promotes digital literacy in the intelligent era. Additionally, it emphasizes the importance of government-led initiatives and global dialog to establish a multistakeholder regulatory framework and conventions, aiming to create a more harmonious human‒machine community with a shared future.

International Journal of Social Sciences & HumanitiesVol. 9(1)
University of Shanghai for Science and Technology (CN)
Quality Education
Openalex Percentile: Top 21%
Educational Reforms and Innovations
1.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Ethical Risk and Pathway of AIGC Cross-Modal Content Generation Technology — Ling Jiang, Yiting Zhang · International Journal of Social Sciences & Humanities (2024) | TGRS Research Map | TGRS