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Challenges in automating fact-checking
webSAGE Journals(peer-reviewed)·journals.sagepub.com/doi/10.1177/27523543241280195
Credibility Rating
4/5
High(4)High quality. Established institution or organization with editorial oversight and accountability.
Rating inherited from publication venue: SAGE Journals
Relevant to AI safety discussions around AI reliability and truthfulness verification; highlights fundamental limitations in AI epistemic authority and the gap between AI capability hype and real-world performance in high-stakes information verification contexts.
Metadata
Importance: 35/100journal articleanalysis
Summary
A technographic case study of an AI fact-checking startup examining why fully automated fact-checking tools have not materialized despite enthusiasm. The study identifies key obstacles including the elusive nature of truth claims, binary epistemology limitations, data scarcity, algorithmic deficiencies, and industry adoption challenges. It frames automated fact-checking as a technological innovation requiring both technical competence and epistemic authority.
Key Points
- •Fully automated fact-checking tools remain unrealized despite years of research and industry interest in combating disinformation at scale.
- •Binary true/false classification of information claims is epistemically problematic and a core technical obstacle for automation.
- •Data scarcity and algorithmic deficiencies limit AI accuracy in verifying information claims reliably.
- •Transparency of AI fact-checking results and compatibility with existing industry workflows are significant adoption barriers.
- •Effective automated fact-checking requires interdisciplinary approaches spanning technology, journalism, and epistemology.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| AI-Era Epistemic Infrastructure | Approach | 59.0 |
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Contents
- [Abstract](https://journals.sagepub.com/doi/10.1177/27523543241280195#abstract)
- [Introduction](https://journals.sagepub.com/doi/10.1177/27523543241280195#sec-1)
- [Presenting the case: “Grammarly for fact-checking”](https://journals.sagepub.com/doi/10.1177/27523543241280195#sec-2)
- [The emergence of automated fact-checking](https://journals.sagepub.com/doi/10.1177/27523543241280195#sec-3)
- [The quest for an interdisciplinary exploration of automated fact-checking and its challenges](https://journals.sagepub.com/doi/10.1177/27523543241280195#sec-4)
- [Qualitative technographic case study: Methodological clarifications](https://journals.sagepub.com/doi/10.1177/27523543241280195#sec-5)
- [Findings](https://journals.sagepub.com/doi/10.1177/27523543241280195#sec-6)
- [Discussion and conclusion](https://journals.sagepub.com/doi/10.1177/27523543241280195#sec-7)
- [Declaration of conflicting interests](https://journals.sagepub.com/doi/10.1177/27523543241280195#conflict)
- [Funding](https://journals.sagepub.com/doi/10.1177/27523543241280195#funding)
- [ORCID iD](https://journals.sagepub.com/doi/10.1177/27523543241280195#orcid)
- [References](https://journals.sagepub.com/doi/10.1177/27523543241280195#bibliography)
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## Abstract
The prevalence of disinformation in media ecosystems has spurred efforts by researchers from various disciplines and media professionals to find effective methods for verifying information at scale. Automated fact-checking has emerged as a promising solution to combat disinformation. However, fully automated tools have not yet materialized. This technographic case study of a start-up company, “X,” investigated the challenges associated with this process. By conceptualizing automated fact-checking as a technological innovation within journalistic knowledge production, the article uncovered the reasons behind the gap between “X's” initial enthusiasm about AI's capabilities in verifying information and the actual performance of such tools. These reasons cross the disciplinary boundaries relating to the technological aspects of automated fact-checking and a requirement for such tools to be epistemically authoritative. The study revealed significant hurdles faced b
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