Literature DB >> 30995161

Coverage of ethics within the artificial intelligence and machine learning academic literature: The case of disabled people.

Aspen Lillywhite1, Gregor Wolbring1.   

Abstract

Disabled people are often the anticipated users of scientific and technological products and processes advanced and enabled by artificial intelligence (AI) and machine learning (ML). Disabled people are also impacted by societal impacts of AI/ML. Many ethical issues are identified within AI/ML as fields and within individual applications of AI/ML. At the same time, problems have been identified in how ethics discourses engage with disabled people. The aim of our scoping review was to better understand to what extent and how the AI/ML focused academic literature engaged with the ethics of AI/ML in relation to disabled people.Of the n = 1659 abstracts engaging with AI/ML and ethics downloaded from Scopus (which includes all Medline articles) and the 70 databases of EBSCO ALL, we found 54 relevant abstracts using the term "patient" and 11 relevant abstracts mentioning terms linked to "impair*", "disab*" and "deaf". Our study suggests a gap in the literature that should be filled given the many AI/ML related ethical issues identified in the literature and their impact on disabled people.

Entities:  

Keywords:  artificial intelligence; disabled people; ethics; machine learning; people with disabilities

Mesh:

Year:  2019        PMID: 30995161     DOI: 10.1080/10400435.2019.1593259

Source DB:  PubMed          Journal:  Assist Technol        ISSN: 1040-0435


  4 in total

1.  Legal concerns in health-related artificial intelligence: a scoping review protocol.

Authors:  Michael Da Silva; Tanya Horsley; Devin Singh; Emily Da Silva; Valentina Ly; Bryan Thomas; Ryan C Daniel; Karni A Chagal-Feferkorn; Samantha Iantomasi; Kelli White; Arianne Kent; Colleen M Flood
Journal:  Syst Rev       Date:  2022-06-17

2.  Improving Inclusivity in Robotics Design: An Exploration of Methods for Upstream Co-Creation.

Authors:  Stevienna de Saille; Eva Kipnis; Stephen Potter; David Cameron; Calum J R Webb; Peter Winter; Peter O'Neill; Richard Gold; Kate Halliwell; Lyuba Alboul; Andy J Bell; Andrew Stratton; Jon McNamara
Journal:  Front Robot AI       Date:  2022-06-21

3.  Analyzing the Treatment of Patients with Acute Exacerbation of COPD with the Aid of Intelligent Diagnosis Method.

Authors:  Qina Jiang; Guangxiang Zhao; Shiyan Song; Yujuan Chen
Journal:  J Healthc Eng       Date:  2022-03-12       Impact factor: 2.682

Review 4.  Artificial Intelligence and Machine Learning in Chronic Airway Diseases: Focus on Asthma and Chronic Obstructive Pulmonary Disease.

Authors:  Yinhe Feng; Yubin Wang; Chunfang Zeng; Hui Mao
Journal:  Int J Med Sci       Date:  2021-06-01       Impact factor: 3.738

  4 in total

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