How is ʻUnexplainable’ and Non-transparent AI Affecting Healthcare Delivery?

The healthcare industry is undergoing a profound transformation with the integration of artificial intelligence (AI) into various healthcare settings. However, the successful implementation of AI in healthcare is challenged by several factors, particularly the lack of transparency and explainability in current AI systems. These limitations hamper their effectiveness and reduce their adoption in the field. The key issues that require attention encompass accountability, biases, erroneous results, lack of justification of medical decisions, and the erosion of trust. This paper addresses the challenges raised by non-transparent and non-explainable AI and analyses whether these features jeopardise the responsible integration of AI into healthcare.

Authors

Publication Details

Journal
Oslo Law Review
Published
2024-10-31
DOI
https://doi.org/10.18261/olr.11.1.6
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.24
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article

How is ʻUnexplainable’ and Non-transparent AI Affecting Healthcare Delivery?

Vera Lúcia Raposo
2 citations
Oslo Law Review
Artificial Intelligence in Healthcare and Education
0.24
article

How is ʻUnexplainable’ and Non-transparent AI Affecting Healthcare Delivery?

Vera Lúcia Raposo
article en
2 citations

Abstract

The healthcare industry is undergoing a profound transformation with the integration of artificial intelligence (AI) into various healthcare settings. However, the successful implementation of AI in healthcare is challenged by several factors, particularly the lack of transparency and explainability in current AI systems. These limitations hamper their effectiveness and reduce their adoption in the field. The key issues that require attention encompass accountability, biases, erroneous results, lack of justification of medical decisions, and the erosion of trust. This paper addresses the challenges raised by non-transparent and non-explainable AI and analyses whether these features jeopardise the responsible integration of AI into healthcare.

Oslo Law ReviewVol. 11(1)
Openalex Percentile: Top 40%
Artificial Intelligence in Healthcare and Education
0.24
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