A recent study from Salesforce AI Research reveals that popular AI search systems often produce unsupported claims, significantly undermining their trustworthiness. The evaluation of 303 queries showed unsupported claim rates ranging from 23% to 97.5%, depending on the system and search mode. The framework, DeepTRACE, assessed answers for various metrics, including citation accuracy and one-sidedness, revealing frequent instances of misattribution and overconfidence. While many sources were cited, the actual backing for specific claims was often lacking, leading to misleading information. Users are advised to treat AI-generated answers as preliminary rather than definitive, verifying claims against cited sources and considering counterarguments. The need for evolving search audits and greater accountability in AI output is emphasized, reflecting broader concerns about factual accuracy in AI-generated content. This study highlights the crucial role of critical evaluation and thorough research when interacting with AI systems.
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