Sex and Gender Bias in Technology and Artificial Intelligence

Biomedicine and Healthcare Applications

1st Edition - May 21, 2022

Editors: Davide Cirillo, Silvina Catuara Solarz, Emre Guney

Hardback ISBN:

9 7 8 - 0 - 1 2 - 8 2 1 3 9 2 - 6

eBook ISBN:

9 7 8 - 0 - 1 2 - 8 2 1 3 9 3 - 3

Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications details the integration of sex and gender as critical factors in innovative… Read more

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Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications details the integration of sex and gender as critical factors in innovative technologies (artificial intelligence, digital medicine, natural language processing, robotics) for biomedicine and healthcare applications. By systematically reviewing existing scientific literature, a multidisciplinary group of international experts analyze diverse aspects of the complex relationship between sex and gender, health and technology, providing a perspective overview of the pressing need of an ethically-informed science. The reader is guided through the latest implementations and insights in technological areas of accelerated growth, putting forward the neglected and overlooked aspects of sex and gender in biomedical research and healthcare solutions that leverage artificial intelligence, biosensors, and personalized medicine approaches to predict and prevent disease outcomes. The reader comes away with a critical understanding of this fundamental issue for the sake of better future technologies and more effective clinical approaches.

Cover image
Title page
Table of Contents
Copyright
Dedication
Endorsements
Contributors
Editor Biographies
Acknowledgments
The Women’s Brain Project
1: The birth of the Women’s Brain Project
2: The Women’s Brain Project way—A holistic approach to a complex topic
3: Becoming an international opinion leader
4: The future: Women’s Brain Project call to action
References
Chapter 0: Introduction: The relevance of sex and gender in precision medicine and the role of technologies and artificial intelligence
1: Sex and gender in biomedical research and medicine
2: The role of technologies and AI to understand sex and gender differences in health
3: Organization and scope of this book
Acknowledgments
References
Section 1: Sex and gender differences and precision medicine
Chapter 1: Implications of sex-specific differences on clinical studies of human health
Abstract
Acknowledgments
Chapter points
1: Introduction
2: Genetic and physiological differences and differential manifestation of diseases between sexes
3: Preclinical and clinical study design: A historical perspective
4: Socioeconomic and socioethical considerations
5: Discussion and conclusions
References
Chapter 2: Sex and gender inequality in precision medicine: Socioeconomic determinants of health
Abstract
Chapter points
1: Introduction
2: Precision medicine and inequalities
3: Future directions
References
Section 2: Biases in innovative technologies for biomedicine and health
Chapter 3: Bias and fairness in machine learning and artificial intelligence
Abstract
Acknowledgments
1: Introduction
2: A complex landscape of intersecting biases
3: Taxonomies of bias
4: From ideation to deployment: The life cycle of AI development
5: Bias metrics
6: Conclusions
References
Chapter 4: Big Data in healthcare from a sex and gender perspective
Abstract
Acknowledgments
Chapter points
1: Introduction
2: Big Data in healthcare and wellbeing: A sex and gender perspective
3: Challenges and opportunities
4: Conclusions
5: Brief summary
References
Chapter 5: Biases in digital health measures
Abstract
Acknowledgments
Chapter points
1: Introduction
2: History and development of digital measures
3: Biases and their consequences for digital measures
4: Outlook and recommendations
References
Chapter 6: Sex and gender bias in natural language processing
Abstract
Acknowledgments
Chapter points
1: Introduction
2: NLP today: Breakthroughs and new challenges
3: NLP for biomedicine and health
4: A case in study: Chatbots for mental health
5: Sex and gender bias in the training corpora
6: Debiasing methods
7: Discussion
References
Chapter 7: Sex differences in invasive and noninvasive neurotechnologies
Abstract
Acknowledgments
Chapter points
1: Introduction
2: Sex differences in noninvasive neurotechnologies
3: Sex differences in invasive neurotechnologies
4: Ethical considerations
5: Conclusions
References
Chapter 8: How gender is intertwined with robots and affective technologies: A short review
Abstract
Chapter points
1: Introduction
2: Robots
3: Robots for healthcare and wellbeing
4: Sex and gender aspects
5: Affective technologies
6: Discussion/conclusion
References
Section 3: Toward precision technology
Chapter 9: A unified framework for managing sex and gender bias in AI models for healthcare
Abstract
Acknowledgments
Chapter points
1: Introduction
2: A framework to manage sex and gender biases in biomedical research and healthcare
3: Bias identification
4: Bias explanation
5: Distinction between desirable and undesirable bias
6: Bias mitigation
7: Bias exploitation: Use of desirable bias for precision medicine
8: Summary and conclusions
References
Chapter 10: Privacy issues in healthcare and their mitigation through privacy preserving technologies
Abstract
Acknowledgments
Chapter points
1: Introduction
2: Responsible use of data and AI in healthcare
3: Embedding privacy in AI
4: Epilogue
5: Conclusion
References
Chapter 11: Societal and ethical impact of technologies for health and biomedicine
Abstract
Chapter points
1: Introduction
2: An ethical framework for AI in healthcare and biomedicine
3: Conclusions
References
Conclusion: Toward sex- and gender-stratified precision medicine
Index

Davide Cirillo

Davide Cirillo, Ph.D. is a postdoctoral researcher at Barcelona Supercomputing Center (BSC) Computational Biology group, Life Sciences Department. Davide Cirillo received the MSc degree in Pharmaceutical Biotechnology from University of Roma ‘La Sapienza’, Italy, and the PhD degree in Biomedicine from Universitat Pompeu Fabra (UPF) and Center for Genomic Regulation (CRG) of Barcelona, Spain. His research is devoted to the development and application of computational methods in Precision Medicine with a special emphasis on Machine Learning and Artificial Intelligence.

Affiliations and expertise

Postdoctoral Researcher, Barcelona Supercomputing Center (BSC) Computational Biology Group, Life Sciences Department, Spain

Silvina Catuara Solarz

Silvina Catuara-Solarz, Ph.D. is a translational neuroscientist with expertise in neurodevelopmental, neurodegenerative and psychiatric disorders. After earning a Ph.D. in Biomedicine by the Pompeu Fabra University that she developed at the Centre for Genomic Regulation (CRG), the Hospital del Mar Research Institute (IMIM) (Barcelona, Spain) and the University of California Irvine (Irvine, United States), she worked on target identification for drug development at Janssen Pharmaceutica (Beerse, Belgium). Driven by her interests in merging Technology and Health, she then joined the Health Moonshot at Telefonica Innovation Alpha (Barcelona, Spain) as Strategy Manager where she was involved with the development of evidence-based digital mental health solutions and their efficacy assessment. Given her conviction in the importance of sex and gender for the progress of medicine, Dr. Catuara-Solarz is an active member of the Women’s Brain Project. She has a track record of high impact scientific publications as well as books for the lay audience. Currently Dr. Catuara-Solarz is a selected member of the World Health Organisation Digital Health Roster of Experts and she serves in the European Institute of Innovation and Technology Health (EIT Health) as a project evaluator and a mentor of start-ups in the digital health and medtech sector.

Affiliations and expertise

Women’s Brain Project (WBP), World Health Organisation (WHO), European Institute of Innovation and Technology Health (EIT Health)

Emre Guney

Emre Guney, Ph.D. is a Senior Research Fellow at the Research Programme on Biomedical Informatics (GRIB), at the Pompeu Fabra University (UPF) and Hospital del Mar Research Institute (IMIM) in Barcelona, Spain and works on developing computational systems biology models for network medicine. He holds a secondary appointment at the Pharmacology & Personalised Medicine department at Maastricht University in the Netherlands. He obtained a B.S. in Computer Engineering from Middle East Technical University (METU), Ph.D. in Biomedicine from Pompeu Fabra University (UPF) and spent several years as a postdoctoral scholar at the Center for Complex Network Research (CCNR) and the Center for Cancer Systems Biology (CCSB), Boston, MA, USA.

Affiliations and expertise

Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Research; Institute (IMIM) and Pompeu Fabra University (UPF), Barcelona, Spain; Pharmacology and Personalised Medicine department, Maastricht University, Maastricht, The Netherlands