Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.21489 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915268900421632 |
|---|---|
| author | Anlen, Shirin Wojciak, Zuzanna |
| author_facet | Anlen, Shirin Wojciak, Zuzanna |
| contents | The proliferation of generative AI and deceptive synthetic media threatens the global information ecosystem, especially across the Global Majority. This report from WITNESS highlights the limitations of current AI detection tools, which often underperform in real-world scenarios due to challenges related to explainability, fairness, accessibility, and contextual relevance. In response, WITNESS introduces the Truly Innovative and Effective AI Detection (TRIED) Benchmark, a new framework for evaluating detection tools based on their real-world impact and capacity for innovation. Drawing on frontline experiences, deceptive AI cases, and global consultations, the report outlines how detection tools must evolve to become truly innovative and relevant by meeting diverse linguistic, cultural, and technological contexts. It offers practical guidance for developers, policy actors, and standards bodies to design accountable, transparent, and user-centered detection solutions, and incorporate sociotechnical considerations into future AI standards, procedures and evaluation frameworks. By adopting the TRIED Benchmark, stakeholders can drive innovation, safeguard public trust, strengthen AI literacy, and contribute to a more resilient global information credibility. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_21489 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TRIED: Truly Innovative and Effective AI Detection Benchmark, developed by WITNESS Anlen, Shirin Wojciak, Zuzanna Computers and Society Artificial Intelligence The proliferation of generative AI and deceptive synthetic media threatens the global information ecosystem, especially across the Global Majority. This report from WITNESS highlights the limitations of current AI detection tools, which often underperform in real-world scenarios due to challenges related to explainability, fairness, accessibility, and contextual relevance. In response, WITNESS introduces the Truly Innovative and Effective AI Detection (TRIED) Benchmark, a new framework for evaluating detection tools based on their real-world impact and capacity for innovation. Drawing on frontline experiences, deceptive AI cases, and global consultations, the report outlines how detection tools must evolve to become truly innovative and relevant by meeting diverse linguistic, cultural, and technological contexts. It offers practical guidance for developers, policy actors, and standards bodies to design accountable, transparent, and user-centered detection solutions, and incorporate sociotechnical considerations into future AI standards, procedures and evaluation frameworks. By adopting the TRIED Benchmark, stakeholders can drive innovation, safeguard public trust, strengthen AI literacy, and contribute to a more resilient global information credibility. |
| title | TRIED: Truly Innovative and Effective AI Detection Benchmark, developed by WITNESS |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2504.21489 |