Abstract
Human fake information detection ability is a critical and debated skill. Practitioners have developed various AI detection tools to aid and alert online consumers about fake content. This study aims to investigate how the types of clues provided by AI detection tools influence human fake information detection ability, measured through decision-making competence (including resistance to fake information and cognitive biases). Online vigilance is proposed as a potential underlying mechanism. Additionally, this research introduces two critical boundaries: the expectation gap and the stages of detection tool usage. Theoretical and practical contributions are discussed.
| Original language | English |
|---|---|
| Title of host publication | The 17th China Summer Workshop on Information Management, CSWIM 2024 - PROCEEDINGS |
| Pages | 143-148 |
| Publication status | Published - Jun 2024 |
| Event | 17th China Summer Workshop on Information Management (CSWIM 2024) - Xiamen, China Duration: 29 Jun 2024 → 30 Jun 2024 https://2024.cswimworkshop.org/ https://2024.cswimworkshop.org/wp-content/uploads/2024/06/CSWIM2024-Proceddings.pdf |
Conference
| Conference | 17th China Summer Workshop on Information Management (CSWIM 2024) |
|---|---|
| Abbreviated title | CSWIM2024 |
| Country/Territory | China |
| City | Xiamen |
| Period | 29/06/24 → 30/06/24 |
| Internet address |
Research Keywords
- Fake information detection ability
- AI detection tool
- Clue types
- Decision-making competence
- Online vigilance