Literature DB >> 30467198

Computer knows best? The need for value-flexibility in medical AI.

Rosalind J McDougall.   

Abstract

Artificial intelligence (AI) is increasingly being developed for use in medicine, including for diagnosis and in treatment decision making. The use of AI in medical treatment raises many ethical issues that are yet to be explored in depth by bioethicists. In this paper, I focus specifically on the relationship between the ethical ideal of shared decision making and AI systems that generate treatment recommendations, using the example of IBM's Watson for Oncology. I argue that use of this type of system creates both important risks and significant opportunities for promoting shared decision making. If value judgements are fixed and covert in AI systems, then we risk a shift back to more paternalistic medical care. However, if designed and used in an ethically informed way, AI could offer a potentially powerful way of supporting shared decision making. It could be used to incorporate explicit value reflection, promoting patient autonomy. In the context of medical treatment, we need value-flexible AI that can both respond to the values and treatment goals of individual patients and support clinicians to engage in shared decision making. © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  clinical ethics; decision-making; information technology

Mesh:

Year:  2018        PMID: 30467198     DOI: 10.1136/medethics-2018-105118

Source DB:  PubMed          Journal:  J Med Ethics        ISSN: 0306-6800            Impact factor:   2.903


  22 in total

1.  Ethical concerns around use of artificial intelligence in health care research from the perspective of patients with meningioma, caregivers and health care providers: a qualitative study.

Authors:  Melissa D McCradden; Ami Baba; Ashirbani Saha; Sidra Ahmad; Kanwar Boparai; Pantea Fadaiefard; Michael D Cusimano
Journal:  CMAJ Open       Date:  2020-02-18

Review 2.  Ethical Issues Raised by the Introduction of Artificial Companions to Older Adults with Cognitive Impairment: A Call for Interdisciplinary Collaborations.

Authors:  Elena Portacolone; Jodi Halpern; Jay Luxenberg; Krista L Harrison; Kenneth E Covinsky
Journal:  J Alzheimers Dis       Date:  2020       Impact factor: 4.472

Review 3.  Applications of machine learning to diagnosis and treatment of neurodegenerative diseases.

Authors:  Monika A Myszczynska; Poojitha N Ojamies; Alix M B Lacoste; Daniel Neil; Amir Saffari; Richard Mead; Guillaume M Hautbergue; Joanna D Holbrook; Laura Ferraiuolo
Journal:  Nat Rev Neurol       Date:  2020-07-15       Impact factor: 42.937

4.  Trust and medical AI: the challenges we face and the expertise needed to overcome them.

Authors:  Thomas P Quinn; Manisha Senadeera; Stephan Jacobs; Simon Coghlan; Vuong Le
Journal:  J Am Med Inform Assoc       Date:  2021-03-18       Impact factor: 4.497

5.  Perceptions of artificial intelligence in healthcare: findings from a qualitative survey study among actors in France.

Authors:  M-C Laï; M Brian; M-F Mamzer
Journal:  J Transl Med       Date:  2020-01-09       Impact factor: 5.531

6.  Shared decision-making and maternity care in the deep learning age: Acknowledging and overcoming inherited defeaters.

Authors:  Keith Begley; Cecily Begley; Valerie Smith
Journal:  J Eval Clin Pract       Date:  2020-11-13       Impact factor: 2.336

7.  Ethics parallel research: an approach for (early) ethical guidance of biomedical innovation.

Authors:  Karin R Jongsma; Annelien L Bredenoord
Journal:  BMC Med Ethics       Date:  2020-09-01       Impact factor: 2.652

8.  Artificial intelligence and the ongoing need for empathy, compassion and trust in healthcare.

Authors:  Angeliki Kerasidou
Journal:  Bull World Health Organ       Date:  2020-01-27       Impact factor: 9.408

9.  SERIES: eHealth in primary care. Part 2: Exploring the ethical implications of its application in primary care practice.

Authors:  Sarah N Boers; Karin R Jongsma; Federica Lucivero; Jiska Aardoom; Frederike L Büchner; Martine de Vries; Persijn Honkoop; Elisa J F Houwink; Marise J Kasteleyn; Eline Meijer; Hilary Pinnock; Martina Teichert; Paul van der Boog; Sanne van Luenen; Rianne M J J van der Kleij; Niels H Chavannes
Journal:  Eur J Gen Pract       Date:  2019-10-30       Impact factor: 1.904

10.  How to achieve trustworthy artificial intelligence for health.

Authors:  Kristine Bærøe; Ainar Miyata-Sturm; Edmund Henden
Journal:  Bull World Health Organ       Date:  2020-01-27       Impact factor: 9.408

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