Inclusivity of AI Speech in Healthcare: A Decade Look Back
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866918022051004416 |
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| author | Larasati, Retno |
| author_facet | Larasati, Retno |
| contents | The integration of AI speech recognition technologies into healthcare has the potential to revolutionize clinical workflows and patient-provider communication. However, this study reveals significant gaps in inclusivity, with datasets and research disproportionately favouring high-resource languages, standardized accents, and narrow demographic groups. These biases risk perpetuating healthcare disparities, as AI systems may misinterpret speech from marginalized groups. This paper highlights the urgent need for inclusive dataset design, bias mitigation research, and policy frameworks to ensure equitable access to AI speech technologies in healthcare. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2505_10596 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Inclusivity of AI Speech in Healthcare: A Decade Look Back Larasati, Retno Computers and Society Artificial Intelligence The integration of AI speech recognition technologies into healthcare has the potential to revolutionize clinical workflows and patient-provider communication. However, this study reveals significant gaps in inclusivity, with datasets and research disproportionately favouring high-resource languages, standardized accents, and narrow demographic groups. These biases risk perpetuating healthcare disparities, as AI systems may misinterpret speech from marginalized groups. This paper highlights the urgent need for inclusive dataset design, bias mitigation research, and policy frameworks to ensure equitable access to AI speech technologies in healthcare. |
| title | Inclusivity of AI Speech in Healthcare: A Decade Look Back |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2505.10596 |