Publication Type
Journal Article
Version
publishedVersion
Publication Date
9-2023
Abstract
With its remarkable ability to generate content, generative artificial intelligence (GAI) has been recognized as a milestone in the development of artificial general intelligence. To understand the challenges, potential impact, and implications associated with GAI, we adopt a socio-technical perspective to analyze them. First, we identify the key characteristics of GAI, which include content generation, generalization ability, and reinforcement learning based on human feedback. Next, we address technological, ethical, societal, economic, regulatory, and governance challenges. Finally, we deploy activity theory to explore research directions in GAI. Research questions that warrant further investigation include how GAI may impact the future of work, how GAI can collaborate effectively with humans, and how we can improve the transparency of GAI models as well as mitigate biases and misinformation in GAI to achieve ethical and responsible GAI.
Keywords
Generative Artificial Intelligence, Activity System Analysis, Activity Theory, AI Challenges, Socio-technicalPerspective, Research Directions
Discipline
Artificial Intelligence and Robotics | Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
AIS Transactions on Human-Computer Interaction
Volume
15
Issue
3
First Page
247
Last Page
267
ISSN
1944-3900
Publisher
AIS
Citation
NAH, Fiona Fui-hoon; CAI, Jingyuan; ZHENG, Ruilin; and PANG, Natalie.
An activity system-based perspective of generative AI: Challenges and research directions. (2023). AIS Transactions on Human-Computer Interaction. 15, (3), 247-267.
Available at: https://ink.library.smu.edu.sg/sis_research/9524
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://aisel.aisnet.org/thci/vol15/iss3/1