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Ethical Reflections on Integrating Artificial Intelligence in Care Practices.

Giulia Ricchezze1, Luca Tomassini2, Mauro Bacci3

  • 1Institute of Legal Medicine, Department of Law, University of Macerata, Macerata, Italy.

Community Health Equity Research & Policy
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Summary
This summary is machine-generated.

Artificial intelligence (AI) and robotics in disability care offer benefits but raise ethical concerns regarding autonomy and dignity. Ensuring equitable access and human-centered design is crucial for responsible integration of these technologies.

Keywords:
artificial intelligencedisabilityequityhealth carerehabilitation

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Area of Science:

  • Bioethics
  • Artificial Intelligence
  • Disability Studies
  • Healthcare Technology

Background:

  • Integration of AI and robotics in disability care presents significant ethical challenges.
  • Key concerns include autonomy, human dignity, equitable access, and the changing nature of care delivery.
  • These technologies impact clinical relationships and the lived experiences of individuals with disabilities.

Purpose of the Study:

  • To examine the ethical landscape of AI-supported rehabilitation and assistance.
  • To analyze risks such as algorithmic bias, over-reliance on automation, and the erosion of human connection in care.
  • To apply a biopsychosocial model to understand the intersection of technology and disability.

Main Methods:

  • Interdisciplinary approach synthesizing bioethical literature.
  • Analysis of illustrative case studies.
  • Incorporation of expert perspectives from healthcare, law, and technology.

Main Results:

  • Ethical tensions identified in personalized care, decision-making transparency, and inclusivity of data/design.
  • Risks include algorithmic bias and potential diminishment of the human element in care.
  • A biopsychosocial framework highlights the impact on individuals with disabilities.

Conclusions:

  • Need for governance models with ethical safeguards and fairness promotion.
  • Emphasis on participatory design involving patients, caregivers, and professionals.
  • Pathways toward equitable, human-centered AI integration require inclusive datasets, fairness-aware algorithms, and aligned regulatory mechanisms.