Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Evaluating ChatGPT’s responses to vaccine-related questions: the impact of question framing on content and quality
0
Zitationen
2
Autoren
2025
Jahr
Abstract
ChatGPT maintained comparable quality in Japanese responses to both supportive and critical vaccine questions, suggesting resilience to negative framing. However, expert reviewers identified thematic biases, occasional inadequacy of detail, and linguistic issues that could mislead lay readers. These findings underscore the need for continued human oversight, refinement of Japanese-language outputs, and algorithmic adjustments to reduce topical bias.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.239 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.095 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.463 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.428 Zit.