{"type":"ScholarlyArticle","title":"Explainable Automatic Fact-Checking for Journalists Augmentation in the Wild","authors":[{"name":"Filipe Altoe","slug":"filipe-altoe","given":"Filipe","family":"Altoe","affiliation":""},{"name":"Sérgio Miguel Gonçalves Pinto","slug":"sergio-miguel-goncalves-pinto","given":"Sérgio Miguel Gonçalves","family":"Pinto","affiliation":""},{"name":"H Sofia Pinto","slug":"h-sofia-pinto","given":"H Sofia","family":"Pinto","affiliation":""}],"abstract":"Journalistic manual fact-checking is the usual way to address fake news; however, this labor-intensive task regularly is not a match for the scale of the problem. The literature introduced automated fact-checking (AFC) as a potential solution; however, there is still missing functionality in the AFC pipeline, a lack of research benchmarking data, and a disconnect between their design and human factors crucial for adoption. We present a fully explainable AFC framework designed to augment professional journalists in the wild. A novel human annotation-free approach surpasses state-of-the-art multi-label classification by 12%. It is the first to demonstrate strong generalization across different claim subjects without retraining and to generate complete verdict explanation articles and their summaries. A focused user study of 103 professional journalists, with 93% having dedicated experience with fact-checking, validates the framework's level of explainability, transparency, and quality of generated fact-checking artifacts. The importance of establishing clear source selection and bias evaluation criteria reinforced the need for human augmentation, not replacement, by AFC systems.","doi":"10.24963/ijcai.2025/1140","url":"https://ijcai.org/proceedings/2025/1140","pdf":"https://ijcai.org/proceedings/2025/1140.pdf","markdown":"https://ijcai.org/proceedings/2025/1140.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/1140","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Human-Centred AI","track":"Human-Centred AI","number":1140,"pages":{"first":10262,"last":10270},"keywords":["IJCAI25: Human-Centred AI"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}