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AI and disability: A systematic scoping review.

Christo El MorrBushra KundiFariah MobeenSarah TaleghaniYahya El-LahibRachel Gorman
Published in: Health informatics journal (2024)
Background: Artificial intelligence (AI) can enhance life experiences and present challenges for people with disabilities. Objectives: This study aims to investigate the relationship between AI and disability, exploring the potential benefits and challenges of using AI for people with disabilities. Methods: A systematic scoping review was conducted using eight online databases; 45 scholarly articles from the last 5 years were identified and selected for thematic analysis. Results: The review's findings revealed AI's potential to enhance healthcare; however, it showed a high prevalence of a narrow medical model of disability and an ableist perspective in AI research. This raises concerns about the perpetuation of biases and discrimination against individuals with disabilities in the development and deployment of AI technologies. Conclusion: We recommend shifting towards a social model of disability, promoting interdisciplinary collaboration, addressing AI bias and discrimination, prioritizing privacy and security in AI development, focusing on accessibility and usability, investing in education and training, and advocating for robust policy and regulatory frameworks. The review emphasizes the urgent need for further research to ensure that AI benefits all members of society equitably and that future AI systems are designed with inclusivity and accessibility as core principles.
Keyphrases
  • artificial intelligence
  • big data
  • machine learning
  • healthcare
  • deep learning
  • multiple sclerosis
  • mental health
  • health information
  • transcription factor
  • electronic health record