On the usability of generative AI: Human generative AI
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866929730019655680 |
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| author | Ravera, Anna Gena, Cristina |
| author_facet | Ravera, Anna Gena, Cristina |
| contents | Generative AI systems are transforming content creation, but their usability remains a key challenge. This paper examines usability factors such as user experience, transparency, control, and cognitive load. Common challenges include unpredictability and difficulties in fine-tuning outputs. We review evaluation metrics like efficiency, learnability, and satisfaction, highlighting best practices from various domains. Improving interpretability, intuitive interfaces, and user feedback can enhance usability, making generative AI more accessible and effective. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_17714 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On the usability of generative AI: Human generative AI Ravera, Anna Gena, Cristina Human-Computer Interaction Artificial Intelligence Generative AI systems are transforming content creation, but their usability remains a key challenge. This paper examines usability factors such as user experience, transparency, control, and cognitive load. Common challenges include unpredictability and difficulties in fine-tuning outputs. We review evaluation metrics like efficiency, learnability, and satisfaction, highlighting best practices from various domains. Improving interpretability, intuitive interfaces, and user feedback can enhance usability, making generative AI more accessible and effective. |
| title | On the usability of generative AI: Human generative AI |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2502.17714 |