The Role of Explainability in Collaborative Human-AI Disinformation Detection
Author:
Affiliation:
1. TU Berlin, DFKI, Germany
2. Telekom, TU Berlin, Germany
3. DFKI, Germany
4. Tel Aviv University, Israel
5. TU Berlin, Germany
Funder
BMBF Germany
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3630106.3659031
Reference74 articles.
1. Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
2. Evaluating the fake news problem at the scale of the information ecosystem
3. Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in Twitter’s Birdwatch crowdsourced fact-checking program
4. State of the Art Models for Fake News Detection Tasks
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1. Evaluating Human-Centered AI Explanations: Introduction of an XAI Evaluation Framework for Fact-Checking;3rd ACM International Workshop on Multimedia AI against Disinformation;2024-06-10
2. NewsPolyML: Multi-lingual European News Fake Assessment Dataset;3rd ACM International Workshop on Multimedia AI against Disinformation;2024-06-10
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