Reflecting on Ethical use of AI

Following interactions with providers, researchers and users of AI related to our work in the AI4TB project on applying computer assisted diagnosis processes to achieve high-volume identification of silicosis and tuberculosis to facilitate timely attention to compensation claims of black gold miners in southern Africa, we have published an article to consider lessons for AI application more generally.

The full article is available here: DOI: https://doi.org/10.5334/aogh.3206

Spiegel JM, Ehrlich R, Yassi A, Riera F, Wilkinson J, Lockhart K, Barker S, Kistnasamy B. Using Artificial Intelligence for High-Volume Identification of Silicosis and Tuberculosis: A Bio-Ethics Approach. Annals of Global Health. 2021; 87(1): 58, 1–12.

Abstract

Although Artificial Intelligence (AI) is being increasingly applied, considerable distrust about introducing “disruptive” technologies persists. Intrinsic and contextual factors influencing where and how such innovations are introduced therefore require careful scrutiny to ensure that health equity is promoted. To illustrate one such critical approach, we describe and appraise an AI application — the development of computer assisted diagnosis (CAD) to support more efficient adjudication of compensation claims from former gold miners with occupational lung disease in Southern Africa. In doing so, we apply a bio-ethical lens that considers the principles of beneficence, non-maleficence, autonomy and justice and add explicability as a core principle. We draw on the AI literature, our research on CAD validation and process efficiency, as well as apprehensions of users and stakeholders. Issues of concern included AI accuracy, biased training of AI systems, data privacy, impact on human skill development, transparency and accountability in AI use, as well as intellectual property ownership. We discuss ways in which each of these potential obstacles to successful use of CAD could be mitigated. We conclude that efforts to overcoming technical challenges in applying AI must be accompanied from the onset by attention to ensuring its ethical use.

Figure 2 — Spiegel et al. Using Artificial Intelligence for High-Volume Identification of Silicosis and Tuberculosis: A Bio-Ethics Approach. Annals of Global Health. 2021; 87(1): 58, 4.

Previous AI4TB blogs:

AI4TB: Ground-truthing machine-learning innovations

  • Sept. 16, 2020

AI4TB: Ground-truthing from machine-learning innovations

  • April 9, 2020

AI4TB: Moving forward on technical and decision-making challenges

  • December 11, 2019

Can artificial intelligence systems be used to detect tuberculosis and silicosis among ex-miners in Southern Africa?

  • October 27, 2019

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I am a Professor in the School of Population and Public Health at the University of British Columbia where I co-direct the Global Health Research Program.

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Jspiegel

Jspiegel

I am a Professor in the School of Population and Public Health at the University of British Columbia where I co-direct the Global Health Research Program.

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