Understanding and Mitigating Unintended Demographic Bias in Machine Learning Systems

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Publisher :
ISBN 13 :
Total Pages : 84 pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Understanding and Mitigating Unintended Demographic Bias in Machine Learning Systems by : Christopher J. Sweeney (M. Eng.)

Download or read book Understanding and Mitigating Unintended Demographic Bias in Machine Learning Systems written by Christopher J. Sweeney (M. Eng.) and published by . This book was released on 2019 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning is becoming more and more influential in our society. Algorithms that learn from data are streamlining tasks in domains like employment, banking, education, heath care, social media, etc. Unfortunately, machine learning models are very susceptible to unintended bias, resulting in unfair and discriminatory algorithms with the power to adversely impact society. This unintended bias is usually subtle, emanating from many different sources and taking on many forms. This thesis will focus on understanding how unfair biases with respect to various demographic groups show up in machine learning systems. Furthermore, we develop multiple techniques to mitigate unintended demographic bias at various stages of typical machine learning pipelines. Using Natural Language Processing as a framework, we show substantial improvements in fairness for standard machine learning systems, when using our bias mitigation techniques.

Mitigating Bias in Machine Learning

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Publisher : McGraw Hill Professional
ISBN 13 : 126492271X
Total Pages : 249 pages
Book Rating : 4.2/5 (649 download)

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Book Synopsis Mitigating Bias in Machine Learning by : Carlotta A. Berry

Download or read book Mitigating Bias in Machine Learning written by Carlotta A. Berry and published by McGraw Hill Professional. This book was released on 2024-10-18 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical guide shows, step by step, how to use machine learning to carry out actionable decisions that do not discriminate based on numerous human factors, including ethnicity and gender. The authors examine the many kinds of bias that occur in the field today and provide mitigation strategies that are ready to deploy across a wide range of technologies, applications, and industries. Edited by engineering and computing experts, Mitigating Bias in Machine Learning includes contributions from recognized scholars and professionals working across different artificial intelligence sectors. Each chapter addresses a different topic and real-world case studies are featured throughout that highlight discriminatory machine learning practices and clearly show how they were reduced. Mitigating Bias in Machine Learning addresses: Ethical and Societal Implications of Machine Learning Social Media and Health Information Dissemination Comparative Case Study of Fairness Toolkits Bias Mitigation in Hate Speech Detection Unintended Systematic Biases in Natural Language Processing Combating Bias in Large Language Models Recognizing Bias in Medical Machine Learning and AI Models Machine Learning Bias in Healthcare Achieving Systemic Equity in Socioecological Systems Community Engagement for Machine Learning

Uncovering Bias in Machine Learning

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Publisher : Wiley
ISBN 13 : 9781119763147
Total Pages : 300 pages
Book Rating : 4.7/5 (631 download)

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Book Synopsis Uncovering Bias in Machine Learning by : Ayodele Odubela

Download or read book Uncovering Bias in Machine Learning written by Ayodele Odubela and published by Wiley. This book was released on 2021-10-05 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: With machine learning systems becoming more ubiquitous in automated decision making, it is crucial that we make these systems sensitive to the type of bias that results in discrimination, especially discrimination on illegal grounds. Machine learning is already being used to make or assist decisions in the following domains of Recruiting (Screening job applicants), Banking (Credit ratings/Loan approvals), Judiciary (Recidivism risk assessments), Welfare (Welfare Benefit Eligibility), Journalism (News Recommender Systems) etc. Given the scale and impact of these industries, it is crucial that we take measures to prevent unfair discrimination in them via legal as well as technical means. This book will give data scientists and Machine learning engineers insight on how building machine learning models and algorithms can negatively impact users. The book will also provide tools and code examples to help document, identify, and mitigate different types of machine bias. The audience are Data Scientists, Machine Learning Engineers, and Researchers who implement and productionalize machine learning models. This book has been needed for decades because it not only helps the reader understand how human bias slips into models but gives them code and techniques to analyze the models they’ve already built. This book will also give engineers the tools to push back on demands from management that result in harmful models. While this book will focus on machine learning that is used to predict data about users that can be impactful on their lives. Thousands of consumer products use machine learning and these algorithms can cause major damage if influenced by biased data. Google has already classified black people as “gorillas” in Google Photos. Some facial recognition doesn’t even pick up darker toned skin. In terms of trends, ML and AI are by far the hottest fields in computing. The problem with this high-paying, high-growth area is that few practitioners are actually skilled in reducing and mitigating harm caused to users. This book will allow Data Scientists, Machine Learning Engineers, Software Developers, and Researchers alike to apply these explainability steps to their system.

Human Compatible

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Publisher : Penguin Books
ISBN 13 : 0525558616
Total Pages : 354 pages
Book Rating : 4.5/5 (255 download)

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Book Synopsis Human Compatible by : Stuart Jonathan Russell

Download or read book Human Compatible written by Stuart Jonathan Russell and published by Penguin Books. This book was released on 2019 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A leading artificial intelligence researcher lays out a new approach to AI that will enable people to coexist successfully with increasingly intelligent machines.

An Intelligence in Our Image

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Publisher : Rand Corporation
ISBN 13 : 0833097636
Total Pages : 45 pages
Book Rating : 4.8/5 (33 download)

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Book Synopsis An Intelligence in Our Image by : Osonde A. Osoba

Download or read book An Intelligence in Our Image written by Osonde A. Osoba and published by Rand Corporation. This book was released on 2017-04-05 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning algorithms and artificial intelligence influence many aspects of life today. This report identifies some of their shortcomings and associated policy risks and examines some approaches for combating these problems.

The Oxford Handbook of Ethics of AI

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Publisher : Oxford Handbooks
ISBN 13 : 019006739X
Total Pages : 896 pages
Book Rating : 4.1/5 (9 download)

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Book Synopsis The Oxford Handbook of Ethics of AI by : Markus Dirk Dubber

Download or read book The Oxford Handbook of Ethics of AI written by Markus Dirk Dubber and published by Oxford Handbooks. This book was released on 2020 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: This interdisciplinary and international handbook captures and shapes much needed reflection on normative frameworks for the production, application, and use of artificial intelligence in all spheres of individual, commercial, social, and public life.

Data Feminism

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Publisher : MIT Press
ISBN 13 : 0262358530
Total Pages : 328 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Data Feminism by : Catherine D'Ignazio

Download or read book Data Feminism written by Catherine D'Ignazio and published by MIT Press. This book was released on 2020-03-31 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

Machine Learning and Knowledge Discovery in Databases: Research Track

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Publisher : Springer Nature
ISBN 13 : 3031434153
Total Pages : 758 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases: Research Track by : Danai Koutra

Download or read book Machine Learning and Knowledge Discovery in Databases: Research Track written by Danai Koutra and published by Springer Nature. This book was released on 2023-09-16 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: ​Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: ​Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: ​Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: ​Robustness; Time Series; Transfer and Multitask Learning. Part VI: ​Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. ​Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.

Advances in Knowledge Discovery and Data Mining

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Publisher : Springer Nature
ISBN 13 : 3031333837
Total Pages : 360 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Advances in Knowledge Discovery and Data Mining by : Hisashi Kashima

Download or read book Advances in Knowledge Discovery and Data Mining written by Hisashi Kashima and published by Springer Nature. This book was released on 2023-05-29 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023. The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.

Towards Ethical and Socially Responsible Explainable AI

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Publisher : Springer Nature
ISBN 13 : 3031664892
Total Pages : 381 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis Towards Ethical and Socially Responsible Explainable AI by : Mohammad Amir Khusru Akhtar

Download or read book Towards Ethical and Socially Responsible Explainable AI written by Mohammad Amir Khusru Akhtar and published by Springer Nature. This book was released on with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Improving Diagnosis in Health Care

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Publisher : National Academies Press
ISBN 13 : 0309377722
Total Pages : 473 pages
Book Rating : 4.3/5 (93 download)

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Book Synopsis Improving Diagnosis in Health Care by : National Academies of Sciences, Engineering, and Medicine

Download or read book Improving Diagnosis in Health Care written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2015-12-29 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.

Interpretable Machine Learning

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Publisher : Lulu.com
ISBN 13 : 0244768528
Total Pages : 320 pages
Book Rating : 4.2/5 (447 download)

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Book Synopsis Interpretable Machine Learning by : Christoph Molnar

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Global Environmental Change

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Publisher : National Academies Press
ISBN 13 : 0309044944
Total Pages : 321 pages
Book Rating : 4.3/5 (9 download)

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Book Synopsis Global Environmental Change by : National Research Council

Download or read book Global Environmental Change written by National Research Council and published by National Academies Press. This book was released on 1991-02-01 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global environmental change often seems to be the most carefully examined issue of our time. Yet understanding the human sideâ€"human causes of and responses to environmental changeâ€"has not yet received sustained attention. Global Environmental Change offers a strategy for combining the efforts of natural and social scientists to better understand how our actions influence global change and how global change influences us. The volume is accessible to the nonscientist and provides a wide range of examples and case studies. It explores how the attitudes and actions of individuals, governments, and organizations intertwine to leave their mark on the health of the planet. The book focuses on establishing a framework for this new field of study, identifying problems that must be overcome if we are to deepen our understanding of the human dimensions of global change, presenting conclusions and recommendations.

Web Information Systems Engineering – WISE 2022

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Publisher : Springer Nature
ISBN 13 : 3031208919
Total Pages : 658 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Web Information Systems Engineering – WISE 2022 by : Richard Chbeir

Download or read book Web Information Systems Engineering – WISE 2022 written by Richard Chbeir and published by Springer Nature. This book was released on 2022-11-07 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 23nd International Conference on Web Information Systems Engineering, WISE 2021, held in Biarritz, France, in November 2022. The 31 full, 13 short and 3 demo papers were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: Social Media, Spatial & Temporal Issues, Query Processing & Information Extraction, Architecture and Performance, Graph Data Management, Security & Privacy, Information Retrieval & Text Processing, Reinforcement Learning, Learning & Optimization, Spatial Data Processing, Recommendation, Neural Networks, and Demo Papers.

Pain Management and the Opioid Epidemic

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Publisher : National Academies Press
ISBN 13 : 0309459575
Total Pages : 483 pages
Book Rating : 4.3/5 (94 download)

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Book Synopsis Pain Management and the Opioid Epidemic by : National Academies of Sciences, Engineering, and Medicine

Download or read book Pain Management and the Opioid Epidemic written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-09-28 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drug overdose, driven largely by overdose related to the use of opioids, is now the leading cause of unintentional injury death in the United States. The ongoing opioid crisis lies at the intersection of two public health challenges: reducing the burden of suffering from pain and containing the rising toll of the harms that can arise from the use of opioid medications. Chronic pain and opioid use disorder both represent complex human conditions affecting millions of Americans and causing untold disability and loss of function. In the context of the growing opioid problem, the U.S. Food and Drug Administration (FDA) launched an Opioids Action Plan in early 2016. As part of this plan, the FDA asked the National Academies of Sciences, Engineering, and Medicine to convene a committee to update the state of the science on pain research, care, and education and to identify actions the FDA and others can take to respond to the opioid epidemic, with a particular focus on informing FDA's development of a formal method for incorporating individual and societal considerations into its risk-benefit framework for opioid approval and monitoring.

Statistical Analysis of Network Data

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Publisher : Springer Science & Business Media
ISBN 13 : 0387881468
Total Pages : 397 pages
Book Rating : 4.3/5 (878 download)

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Book Synopsis Statistical Analysis of Network Data by : Eric D. Kolaczyk

Download or read book Statistical Analysis of Network Data written by Eric D. Kolaczyk and published by Springer Science & Business Media. This book was released on 2009-04-20 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.

Processes of Prejudice

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Publisher :
ISBN 13 : 9781842062708
Total Pages : 111 pages
Book Rating : 4.0/5 (627 download)

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Book Synopsis Processes of Prejudice by : Dominic Abrams

Download or read book Processes of Prejudice written by Dominic Abrams and published by . This book was released on 2010 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: