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S. Scott Graham - The Doctor and the Algorithm: Promise, Peril, and the Future of Health AI

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S. Scott Graham The Doctor and the Algorithm: Promise, Peril, and the Future of Health AI
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For years, technologists and computer scientists have promised an AI revolution that would transform the very basis of how we imagine and administer modern medicine. AI-driven advancements in medical error rates, diagnostic accuracy, or disease outbreak detection could potentially save thousands of lives. But health AI also carries the potential for exacerbating deep systemic biases if left unchecked.
The Doctor and the Algorithm combines insights from science and technology studies, critical algorithm studies, and public interest informatics to better understand the promise and peril of health AI. The book draws on case studies in automated diagnostics, algorithmic pain measurement, AI-driven drug discovery, and death prediction to investigate how health AI is made, promoted, and justified. It explores the enthusiastic promises of health AI marketing communication and medical futurism while also analyzing the inequitable outcomes new AI technology often creates for already marginalized communities. Finally, the book closes with specific recommendations for regulatory frameworks that might support more ethical and equitable approaches to health AI in the future.
Interweaving textual analysis and original informatics, The Doctor and the Algorithm offers a sobering analysis of the promise of medical AI against the real and unintended consequences that deep medicine can bring for patients, providers, and public health alike.

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Oxford University Press is a department of the University of Oxford. It furthers the Universitys objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and certain other countries.

Published in the United States of America by Oxford University Press

198 Madison Avenue, New York, NY 10016, United States of America.

Oxford University Press 2022

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by license, or under terms agreed with the appropriate reproduction rights organization. Inquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above.

You must not circulate this work in any other form and you must impose this same condition on any acquirer.

Library of Congress Control Number: 2022908882

ISBN 9780197644461

ISBN 9780197644485

DOI: 10.1093/oso/9780197644461.001.0001

Contents

One of my main goals for The Doctor and the Algorithmwas to bring together scholarship in critical algorithm studies and AI-focused bioethics research. This simply would not have been feasible without the work of many excellent scholars who have already done so much in these areas. Therefore, many of the most important acknowledgments for this book can be found in my works cited. Additionally, I would like to take this opportunity to thank my friends and colleagues who were generous enough to discuss emerging ideas with me and/or read early drafts of selected chapters: Joshua Barbour, Zoltan Majdik, Justin Rousseau, Casey Boyle, Christa Teston, Caroline Gottschalk-Druschke, and Jodi Nicotra. I also offer sincere thanks to Sarah Humphreville of Oxford University Press and my two reviewers for their generous support of this book. Last but not least, special thanks to Roxi Copland for her continued willingness to put up with me on a daily basis.

AIartificial intelligence
ALG-PAlgorithmic Pain Prediction
AUCarea under the curve
AUROCarea under the receiver operating curve
CCCLins concordance correlation coefficient
CONSORTConsolidated Standards for Reporting of Trials
CRTCritical Race Theory
DCNNdeep convoluted neural network
DNNdeep neural network
DTCdirect-to-consumer
EHRelectronic health records
EISenvironmental impact statement
ERBethics review board
FNfalse negative
FNACfine needle aspiration cytology
FONSIfinding of no significant impact
FPfalse positive
ICCintra-class correlation coefficient
IRBInstitutional Review Board
JITAIjust-in-time adaptive interventions
KLGKellgrenLawrence Grade
KNNk-nearest neighbor algorithm
MCImild cognitive impairment
MeSHmedical subject headings
MI-CLAIMminimum information about clinical artificial intelligence modeling
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