Can we trust AI not to further embed racial bias and prejudice?BMJ 2020; 368 doi: https://doi.org/10.1136/bmj.m363 (Published 12 February 2020) Cite this as: BMJ 2020;368:m363
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TRUE AI eliminates racial bias and prejudice – every life matters! Re: Can we trust AI not to further embed racial bias and prejudice?
Over the last few years’ considerable discussion around the topic of Artificial Intelligence (AI) and Machine Learning (ML) have continued to capture the imagination of physicians, journalists and the lay public. Unfortunately the erroneous use of terms – as is the case with the terms AI and ML - can and has lead to more bias and confusion than clarification [1-4].
Most individuals and companies using the term AI or ML are referring to algorithms coupling a series of tests together in an effort to improve the predictability of these algorithms. Each of these tests has their independent sensitivity and specificity errors corrupting the algorithm .
The inclusion of these errors, based upon qualitative interpretation of testing outcomes and associated limitations is nothing more than a collection of human bias – including the bias introduced by race, sex and religion. Such testing is not TRUE AI and does introduce bias and prejudice [5,6] – in addition to more tests, time, money and potential loss of life .
TRUE AI  does not and cannot introduce such bias because it is free of human interpretation, error and prejudice . Resistance to transitioning from biased medical tests or merely adding the term AI or ML to these tests by those seeking to profit from the use of AI/ML has appropriately lead to considerable confusion and concern  over the potential for AI bias and prejudice. To remove this bias, concern and prejudice, and to achieve TRUE AI we must remove the human element .
1. Fleming RM, Fleming MR, McKusick A, Chaudhuri TK. FMTVDM©℗ Nuclear Imaging Artificial (AI) Intelligence but first we need to clarify the use of (1) Stress, (2) Rest, (3) Redistribution and (4) Quantification. Biomed J Sci & Tech Res 2018;7(2):1-4, DOI:10.26717/BJSTR. 2018.07.001489.
2. Fleming RM, Fleming MR, Dooley WC, Chaudhuri TK. From Coronary Arteriography to Stenosis Flow Reserve to FMTVDM. The Sequential Evolution of Artificial Intelligence in Cardiology and Oncology – Removing the Human Error Element. Acta Scientific Medical Sciences 2020;4(1):114-118.
3. Fleming RM, Fleming MR, Chaudhuri TK, Dooley WC. Further Qualitative Anatomic Testing Interpretation – Even by a Machine – Is not True AI and is not the answer for Women with Dense Breasts – or for Women with any Type of Breast Tissue. Sci J Womens Health Care. 2020;4(1):1-2.
4. Fleming RM, Fleming MR, Chaudhuri TK, McKusick A. Machine Learning through FMTVDM Proprietary QCA Equations. J Angiol Vasc Surg 2019;4:026. DOI:10.24966/A VS-7397/100026.
5. Fleming RM, Fleming MR, Dooley WC, Chaudhuri TK. Invited Editorial. The Importance of Differentiating Between Qualitative, Semi-Quantitative and Quantitative Imaging – Close Only Counts in Horseshoes. Eur J Nucl Med Mol Imaging. DOI:10.1007/s00259-019-04668-y. Published online 17 January 2020 https://link.springer.com/article/10.1007/s00259-019-04668-y
6. Fleming RM, Fleming MR, Chaudhuri TK. Coronary Artery Calcium (CAC) Scoring and Treatment Decision Making. J Cardiovasc Med Cardiol 2019;6(4):92-93. DOI:10.17352/2455-2976.000200.
7. Fleming RM, Fleming MR, Chaudhuri TK. Replacing Cardiovascular Risk Factors with True AI and Absolute Quantifiable Measurement (FMTVDM) of Coronary Artery Disease. Inter J Res Studies Med & Health Sci. 2019;4(11):11- 13. ISSN:2456-6373.
8. Fleming RM, Fleming MR, Chaudhuri TK, McKusick A, Dooley WC. Nuclear Imaging: Physician Confusion Over True Quantification and Isotope Redistribution. J Clin Cases Rep 2019;3(2):32-42.
9. Fleming RM, Fleming MR, Chaudhuri TK. The Need to Actually Measure What We’re Talking about before we Put it All Together. Int J Nuclear Med Radioactive Subs 2019;2(1):000114.
10. Fleming RM, Fleming MR, Dooley WC, Chaudhuri TK. From Coronary Arteriography to Stenosis Flow Reserve to FMTVDM. The Sequential Evolution of Artificial Intelligence in Cardiology and Oncology – Removing the Human Error Element. Acta Scientific Medical Sciences 2020;4(1):114-118.
Competing interests: FMTVDM is issued to first author.