Artificial Intelligence and Media Fact-Checking in Jordan: Digital Practices, Challenges, and Information Credibility
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Abstract
The study aimed to explore the use of artificial intelligence tools in verifying published information by fact-checking media observatories and visual media in Jordan (current situation and challenges). The research adopted a descriptive-analytical approach and was conducted on a purposive sample of 150 journalists and specialists in Jordanian media institutions, including those working in visual media, social media platforms, and blogs. The study utilized a questionnaire as the primary data collection tool, and its validity and reliability were verified. The results showed that image and video analysis tools were the most commonly used (35%), followed by natural language processing tools (25%). Social media platforms emerged as the most relied-upon source for verification (40%). The main challenges identified were the lack of technical infrastructure (35%) and insufficient trained competencies (30%). The most common verification methods included comparing images with reliable data (30%). Based on the findings, the study recommended enhancing technical infrastructure, providing comprehensive training programs for journalists, supporting scientific research to develop artificial intelligence algorithms compatible with the Arabic language, enacting legislation to ensure ethical use of artificial intelligence, and promoting international cooperation to improve local skills.
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