Abstract
The accelerated life and flourishing short-form videos have squeezed the viability of long-form videos, which play important roles in the diffusion of knowledge. Video summary has been proposed to facilitate video views and knowledge acquisition as a solution to this dilemma. And the emergence of AI has made the solution possible. We propose that AI-generated video summaries may reduce the effort to acquire information, but logical confusion and information loss may reduce the acquired information quality. Based on the effort-accuracy framework, users with different information quality requirements will react differently towards videos with/without AI summary. Therefore, we plan to conduct laboratory experiments to explore whether and how AI summary increases users’ video-watching intention. Moreover, we will also examine whether AI summary usage affects knowledge acquisition quality. We expect to improve the understanding of AI video summary usage and provide insights into how to make it work efficiently. Copyright © 2024 [Ouyang & Xu].
| Original language | English |
|---|---|
| Title of host publication | ACIS 2024 Proceedings |
| Publication status | Published - 10 Dec 2024 |
| Event | Australasian Conference on Information Systems (ACIS 2024) - University of Canberra, Canberra, Australia Duration: 4 Dec 2024 → 6 Dec 2024 |
Conference
| Conference | Australasian Conference on Information Systems (ACIS 2024) |
|---|---|
| Place | Australia |
| City | Canberra |
| Period | 4/12/24 → 6/12/24 |
Funding
The work described in this paper was fully supported by the National Natural Science Foundation of China (NSFC Grant No. 72271210).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 4 Quality Education
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SDG 10 Reduced Inequalities
Research Keywords
- AI Video Summary
- Effort-accuracy Framework
- Loss Aversion
- Video-watching Intention, recognition accuracy
- Recognition Speed
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