Download or read book Bias and Social Aspects in Search and Recommendation written by Ludovico Boratto and published by Springer Nature. This book was released on 2020-07-11 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the First International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2020, held in April, 2020. Due to the COVID-19 pandemic BIAS 2020 was held virtually. The 10 full papers and 7 short papers were carefully reviewed and seleced from 44 submissions. The papers cover topics that go from search and recommendation in online dating, education, and social media, over the impact ofgender bias in word embeddings, to tools that allow to explore bias and fairnesson the Web.

Download or read book Algorithms of Oppression written by Safiya Umoja Noble and published by NYU Press. This book was released on 2018-02-20 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acknowledgments -- Introduction: the power of algorithms -- A society, searching -- Searching for Black girls -- Searching for people and communities -- Searching for protections from search engines -- The future of knowledge in the public -- The future of information culture -- Conclusion: algorithms of oppression -- Epilogue -- Notes -- Bibliography -- Index -- About the author

Download or read book Advances in Bias and Fairness in Information Retrieval written by Ludovico Boratto and published by Springer Nature. This book was released on 2022-06-18 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the Third International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2022, held in April, 2022. The 9 full papers and 4 short papers were carefully reviewed and selected from 34 submissions. The papers cover topics that go from search and recommendation in online dating, education, and social media, over the impact of gender bias in word embeddings, to tools that allow to explore bias and fairnesson the Web.

Download or read book Advances in Bias and Fairness in Information Retrieval written by Ludovico Boratto and published by Springer Nature. This book was released on 2021-06-24 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the Second International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2021, held in April, 2021. Due to the COVID-19 pandemic BIAS 2021 was held virtually. The 11 full papers and 3 short papers were carefully reviewed and selected from 37 submissions. The papers cover topics that go from search and recommendation in online dating, education, and social media, over the impact of gender bias in word embeddings, to tools that allow to explore bias and fairnesson the Web.

Download or read book Advances in Bias and Fairness in Information Retrieval written by Ludovico Boratto and published by Springer Nature. This book was released on 2023-08-22 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2023, held in Dublin, Ireland, in April 2023. The 10 full papers and 4 short papers included in this book were carefully reviewed and selected from 36 submissions. The present recent research in the following topics: biases exploration and assessment; mitigation strategies against biases; biases in newly emerging domains of application, including healthcare, Wikipedia, and news, novel perspectives; and conceptualizations of biases in the context of generative models and graph neural networks.

Download or read book Recommendation and Search in Social Networks written by Özgür Ulusoy and published by Springer. This book was released on 2015-02-12 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume offers a clear in-depth overview of research covering a variety of issues in social search and recommendation systems. Within the broader context of social network analysis it focuses on important and up-coming topics such as real-time event data collection, frequent-sharing pattern mining, improvement of computer-mediated communication, social tagging information, search system personalization, new detection mechanisms for the identification of online user groups, and many more. The twelve contributed chapters are extended versions of conference papers as well as completely new invited chapters in the field of social search and recommendation systems. This first-of-its kind survey of current methods will be of interest to researchers from both academia and industry working in the field of social networks.

Download or read book Recommender Systems Handbook written by Francesco Ricci and published by Springer. This book was released on 2015-11-17 with total page 1008 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.

Download or read book Anti Bias Education for Young Children and Ourselves written by Louise Derman-Sparks and published by . This book was released on 2020-04-07 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Anti-bias education begins with you! Become a skilled anti-bias teacher with this practical guidance to confronting and eliminating barriers.

Download or read book Understand Manage and Prevent Algorithmic Bias written by Tobias Baer and published by Apress. This book was released on 2019-06-07 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are algorithms friend or foe? The human mind is evolutionarily designed to take shortcuts in order to survive. We jump to conclusions because our brains want to keep us safe. A majority of our biases work in our favor, such as when we feel a car speeding in our direction is dangerous and we instantly move, or when we decide not take a bite of food that appears to have gone bad. However, inherent bias negatively affects work environments and the decision-making surrounding our communities. While the creation of algorithms and machine learning attempts to eliminate bias, they are, after all, created by human beings, and thus are susceptible to what we call algorithmic bias. In Understand, Manage, and Prevent Algorithmic Bias, author Tobias Baer helps you understand where algorithmic bias comes from, how to manage it as a business user or regulator, and how data science can prevent bias from entering statistical algorithms. Baer expertly addresses some of the 100+ varieties of natural bias such as confirmation bias, stability bias, pattern-recognition bias, and many others. Algorithmic bias mirrors—and originates in—these human tendencies. Baer dives into topics as diverse as anomaly detection, hybrid model structures, and self-improving machine learning. While most writings on algorithmic bias focus on the dangers, the core of this positive, fun book points toward a path where bias is kept at bay and even eliminated. You’ll come away with managerial techniques to develop unbiased algorithms, the ability to detect bias more quickly, and knowledge to create unbiased data. Understand, Manage, and Prevent Algorithmic Bias is an innovative, timely, and important book that belongs on your shelf. Whether you are a seasoned business executive, a data scientist, or simply an enthusiast, now is a crucial time to be educated about the impact of algorithmic bias on society and take an active role in fighting bias. What You'll Learn Study the many sources of algorithmic bias, including cognitive biases in the real world, biased data, and statistical artifact Understand the risks of algorithmic biases, how to detect them, and managerial techniques to prevent or manage them Appreciate how machine learning both introduces new sources of algorithmic bias and can be a part of a solutionBe familiar with specific statistical techniques a data scientist can use to detect and overcome algorithmic bias Who This Book is For Business executives of companies using algorithms in daily operations; data scientists (from students to seasoned practitioners) developing algorithms; compliance officials concerned about algorithmic bias; politicians, journalists, and philosophers thinking about algorithmic bias in terms of its impact on society and possible regulatory responses; and consumers concerned about how they might be affected by algorithmic bias

Download or read book Exploring Potentially Discriminatory Biases in Book Recommendation written by Mohammed Imran Rukmoddin Kazi and published by . This book was released on 2016 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent issues which occurred in the field of artificial intelligence present disproportionality based on protected attributes such as sex, race, and ethnicity in their output had raised concerns. The algorithms used in AI may amplify or propagate biases which exist in the historical data and may reflect this in the output data. Computer world now does not consider- this as an abstract fact and researchers are coming up with the new frameworks that modify the existing algorithms present in AI which aids these biases to be reduced to a reasonable level. Recommender System algorithms are well optimized with respect to accuracy and efficiency. But as recommender systems are built on top of Information Retrieval, Machine Learning, and Artificial Intelligence, these systems have high chances of producing a biased outcome. Our current research focus on building methodology for explores potentially discriminatory biases based on protected characteristics in Recommender System. Plus, the definition of discrimination in this work does not correlated with any particular definition which had been define in past. For this work we have taken Book Recommender as a basis for observation of the bias in both input and output of a recommender.

Download or read book Blindspot written by Mahzarin R. Banaji and published by Bantam. This book was released on 2016-08-16 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Accessible and authoritative . . . While we may not have much power to eradicate our own prejudices, we can counteract them. The first step is to turn a hidden bias into a visible one. . . . What if we’re not the magnanimous people we think we are?”—The Washington Post I know my own mind. I am able to assess others in a fair and accurate way. These self-perceptions are challenged by leading psychologists Mahzarin R. Banaji and Anthony G. Greenwald as they explore the hidden biases we all carry from a lifetime of exposure to cultural attitudes about age, gender, race, ethnicity, religion, social class, sexuality, disability status, and nationality. “Blindspot” is the authors’ metaphor for the portion of the mind that houses hidden biases. Writing with simplicity and verve, Banaji and Greenwald question the extent to which our perceptions of social groups—without our awareness or conscious control—shape our likes and dislikes and our judgments about people’s character, abilities, and potential. In Blindspot, the authors reveal hidden biases based on their experience with the Implicit Association Test, a method that has revolutionized the way scientists learn about the human mind and that gives us a glimpse into what lies within the metaphoric blindspot. The title’s “good people” are those of us who strive to align our behavior with our intentions. The aim of Blindspot is to explain the science in plain enough language to help well-intentioned people achieve that alignment. By gaining awareness, we can adapt beliefs and behavior and “outsmart the machine” in our heads so we can be fairer to those around us. Venturing into this book is an invitation to understand our own minds. Brilliant, authoritative, and utterly accessible, Blindspot is a book that will challenge and change readers for years to come. Praise for Blindspot “Conversational . . . easy to read, and best of all, it has the potential, at least, to change the way you think about yourself.”—Leonard Mlodinow, The New York Review of Books “Banaji and Greenwald deserve a major award for writing such a lively and engaging book that conveys an important message: Mental processes that we are not aware of can affect what we think and what we do. Blindspot is one of the most illuminating books ever written on this topic.”—Elizabeth F. Loftus, Ph.D., distinguished professor, University of California, Irvine; past president, Association for Psychological Science; author of Eyewitness Testimony

Download or read book Masked by Trust written by Matthew Reidsma and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Examines library discovery systems to show how the algorithms that power them are not the neutral and unbiased systems that they are claimed to be, but are affected by the human biases of programmers and the commercial influences of their production"--

Download or read book Complex Networks Their Applications X written by Rosa Maria Benito and published by Springer Nature. This book was released on 2022-01-01 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the X International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2021). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks, and technological networks.

Download or read book Advances in Bias and Fairness in Information Retrieval written by Alejandro Bellogin and published by Springer. This book was released on 2024-10-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2024, held in Washington, DC, USA, on July 18, 2024 in hybrid mode. The 7 full papers included in this book were carefully reviewed and selected from 20 submissions. They are grouped into three thematic sessions, each focusing on distinct aspects of bias and fairness in information retrieval.

Download or read book Social Cultural and Behavioral Modeling written by Robert Thomson and published by Springer Nature. This book was released on 2021-07-03 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 14th International Conference on Social, Cultural, and Behavioral Modeling, SBP-BRiMS 2021, which was held online during July 6–9, 2021. The 32 full papers presented in this volume were carefully reviewed and selected from 56 submissions. The papers were organized in topical sections as follows: COVID-related focus; methodologies; social cybersecurity and social networks; and human and agent modeling. They represent a wide number of disciplines including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science. Numerous types of computational methods are used including, but not limited to, machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics.

Download or read book Biased written by Jennifer L. Eberhardt, PhD and published by Penguin. This book was released on 2019-03-26 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Poignant....important and illuminating."—The New York Times Book Review "Groundbreaking."—Bryan Stevenson, New York Times bestselling author of Just Mercy From one of the world’s leading experts on unconscious racial bias come stories, science, and strategies to address one of the central controversies of our time How do we talk about bias? How do we address racial disparities and inequities? What role do our institutions play in creating, maintaining, and magnifying those inequities? What role do we play? With a perspective that is at once scientific, investigative, and informed by personal experience, Dr. Jennifer Eberhardt offers us the language and courage we need to face one of the biggest and most troubling issues of our time. She exposes racial bias at all levels of society—in our neighborhoods, schools, workplaces, and criminal justice system. Yet she also offers us tools to address it. Eberhardt shows us how we can be vulnerable to bias but not doomed to live under its grip. Racial bias is a problem that we all have a role to play in solving.

Download or read book Recommender Systems written by Charu C. Aggarwal and published by Springer. This book was released on 2016-03-28 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories: Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation. Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.