Ethics in Artificial Intelligence: Bias, Fairness and Beyond PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Ethics in Artificial Intelligence: Bias, Fairness and Beyond PDF full book. Access full book title Ethics in Artificial Intelligence: Bias, Fairness and Beyond by Animesh Mukherjee. Download full books in PDF and EPUB format.
Author: Animesh Mukherjee
Publisher: Springer Nature
ISBN: 9819971845
Category : Technology & Engineering
Languages : en
Pages : 150
Get Book
Book Description
This book is a collection of chapters in the newly developing area of ethics in artificial intelligence. The book comprises chapters written by leading experts in this area which makes it a one of its kind collections. Some key features of the book are its unique combination of chapters on both theoretical and practical aspects of integrating ethics into artificial intelligence. The book touches upon all the important concepts in this area including bias, discrimination, fairness, and interpretability. Integral components can be broadly divided into two segments – the first segment includes empirical identification of biases, discrimination, and the ethical concerns thereof in impact assessment, advertising and personalization, computational social science, and information retrieval. The second segment includes operationalizing the notions of fairness, identifying the importance of fairness in allocation, clustering and time series problems, and applications of fairness in software testing/debugging and in multi stakeholder platforms. This segment ends with a chapter on interpretability of machine learning models which is another very important and emerging topic in this area.
Author: Animesh Mukherjee
Publisher: Springer Nature
ISBN: 9819971845
Category : Technology & Engineering
Languages : en
Pages : 150
Get Book
Book Description
This book is a collection of chapters in the newly developing area of ethics in artificial intelligence. The book comprises chapters written by leading experts in this area which makes it a one of its kind collections. Some key features of the book are its unique combination of chapters on both theoretical and practical aspects of integrating ethics into artificial intelligence. The book touches upon all the important concepts in this area including bias, discrimination, fairness, and interpretability. Integral components can be broadly divided into two segments – the first segment includes empirical identification of biases, discrimination, and the ethical concerns thereof in impact assessment, advertising and personalization, computational social science, and information retrieval. The second segment includes operationalizing the notions of fairness, identifying the importance of fairness in allocation, clustering and time series problems, and applications of fairness in software testing/debugging and in multi stakeholder platforms. This segment ends with a chapter on interpretability of machine learning models which is another very important and emerging topic in this area.
Author: Chris Reed
Publisher: Bloomsbury Publishing
ISBN: 1509976825
Category : Law
Languages : en
Pages : 416
Get Book
Book Description
This book proposes a regulatory system for ensuring that AI makes fair decisions. No one wants to be the subject of an unfair decision made by an AI, and fairness is so important to society that we are likely to want to regulate to demand it. But how? This book attempts to answer that question. The aim of regulation must be for an AI's decisions to match the human conception of fairness. To understand what that is, the book proposes a holistic understanding of fairness, which tells us what regulation must try to achieve. However, regulation is not an abstract activity – it regulates how humans behave, and the humans in question are those who develop and use AI for decision- making. Thus the book investigates how those humans are attempting to achieve AI fairness. It finds that there is a serious mismatch between how technologists conceptualise fairness, compared to other humans. How can AI regulation bridge this gap? Traditional models of regulation cannot solve this problem. Fairness is too nuanced, too contextual, and is ultimately a human emotional response. Instead the book proposes to place the responsibility on the AI community to explain and justify their eff orts to achieve fairness, basing regulatory and legal responses on how well that explanation deals with the risks that particular AI presents, and whether the AI operates in accordance with the explanation in use. The book concludes by examining how far this regulatory model might be useful for some of the other social problems which AI generates. An original and significant contribution to the literature on AI regulation, this book is a must-read for those working in the areas of law, regulation, and technology.
Author: Vasiliu-Feltes, Ingrid
Publisher: IGI Global
ISBN: 1799884694
Category : Technology & Engineering
Languages : en
Pages : 316
Get Book
Book Description
As advances in disruptive technologies transform politics and increase the velocity of information and policy flows worldwide, the public is being confronted with changes that move faster than they can comprehend. There is an urgent need to analyze and communicate the ethical issues of these advancements. In a perpetually updating digital world, data is becoming the dominant basis for reality. This new world demands a new approach because traditional methods are not fit for a non-physical space like the internet. Applied Ethics in a Digital World provides an analysis of the ethical questions raised by modern science, technological advancements, and the fourth industrial revolution and explores how to harness the speed, accuracy, and power of emerging technologies in policy research and public engagement to help leaders, policymakers, and the public understand the impact that these technologies will have on economies, legal and political systems, and the way of life. Covering topics such as artificial intelligence (AI) ethics, digital equity, and translational ethics, this book is a dynamic resource for policymakers, civil society, CEOs, ethicists, technologists, security advisors, sociologists, cyber behavior specialists, criminologists, data scientists, global governments, students, researchers, professors, academicians, and professionals.
Author: J. Storrs Hall, Ph.D
Publisher: Prometheus Books
ISBN: 1615920382
Category : Computers
Languages : en
Pages : 408
Get Book
Book Description
With a 30-year career in artificial intelligence (AI) and computer science, Hall reviews the history of AI, predicting the probable achievements in the near future and provides an intriguing glimpse into the astonishing possibilities and dilemmas on the horizon.
Author: Andreas Holzinger
Publisher: Springer Nature
ISBN: 303104083X
Category : Artificial intelligence
Languages : en
Pages : 397
Get Book
Book Description
This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science.
Author: Markus D. Dubber
Publisher: Oxford University Press
ISBN: 0190067411
Category : Law
Languages : en
Pages : 1000
Get Book
Book Description
This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."
Author: Ken Huang
Publisher: Springer Nature
ISBN: 3031452828
Category : Business & Economics
Languages : en
Pages : 412
Get Book
Book Description
This book explores the transformative potential of ChatGPT, Web3, and their impact on productivity and various industries. It delves into Generative AI (GenAI) and its representative platform ChatGPT, their synergy with Web3, and how they can revolutionize business operations. It covers the potential impact surpassing prior industrial revolutions. After providing an overview of GenAI, ChatGPT, and Web3, it investigates business applications in various industries and areas, such as product management, finance, real estate, gaming, and government, highlighting value creation and operational revolution through their integration. It also explores their impact on content generation, customer service, personalization, and data analysis and examines how the technologies can enhance content quality, customer experiences, sales, revenue, and resource efficiency. Moreover, it addresses security, privacy, and ethics concerns, emphasizing the responsible implementation of ChatGPT and Web3. Written by experts in this field, this book is aimed at business leaders, entrepreneurs, students, investors, and professionals who are seeking insights into ChatGPT, ChatGPT Plug-in, GPT-based autonomous agents, and the integration of Gen AI and Web3 in business applications.
Author: Omar Santos
Publisher: Addison-Wesley Professional
ISBN: 0138268398
Category : Computers
Languages : en
Pages : 536
Get Book
Book Description
As artificial intelligence (AI) becomes more and more woven into our everyday lives—and underpins so much of the infrastructure we rely on—the ethical, security, and privacy implications require a critical approach that draws not simply on the programming and algorithmic foundations of the technology. Bringing together legal studies, philosophy, cybersecurity, and academic literature, Beyond the Algorithm examines these complex issues with a comprehensive, easy-to-understand analysis and overview. The book explores the ethical challenges that professionals—and, increasingly, users—are encountering as AI becomes not just a promise of the future, but a powerful tool of the present. An overview of the history and development of AI, from the earliest pioneers in machine learning to current applications and how it might shape the future Introduction to AI models and implementations, as well as examples of emerging AI trends Examination of vulnerabilities, including insight into potential real-world threats, and best practices for ensuring a safe AI deployment Discussion of how to balance accountability, privacy, and ethics with regulatory and legislative concerns with advancing AI technology A critical perspective on regulatory obligations, and repercussions, of AI with copyright protection, patent rights, and other intellectual property dilemmas An academic resource and guide for the evolving technical and intellectual challenges of AI Leading figures in the field bring to life the ethical issues associated with AI through in-depth analysis and case studies in this comprehensive examination.
Author: Maneesha Dhir, Sonal Verma
Publisher: Notion Press
ISBN:
Category : Law
Languages : en
Pages : 192
Get Book
Book Description
"AI FOR GOOD-INDIA AND BEYOND" is a seminal work offering a comprehensive navigation into the evolution and current state of AI regulation in India, marking significant judicial decisions and emerging policies with a keen eye on their alignment with international laws/standards. The book advocates for a Human Rights-Centric Policy Approach promoting fairness, accountability, and transparency in the development of ethical AI systems. Analysing global trends and legal approaches towards AI governance, the authors provide a comparative panorama spanning the latest EU AI Act (2024) to enactments in Brazil, China, Japan, and the USA. Key features • Comprehensive Analysis: Detailed analysis of AI & laws, and policies in India and their global interplay. • Legal Frameworks: Exploration of the statutes and case laws that govern AI, highlighting the evolving legal landscape with real-life examples. • Ethical Considerations: Discussion on the ethical frameworks that must be considered for responsible AI management, including safety, inclusivity, equality, privacy, transparency, accountability, and protection of human values. • Policy Recommendations: Tailored recommendations for India, considering its unique position in the global market and potential for AI leadership. • International Perspectives: Examination of international frameworks and guidelines from major entities like the EU, OECD, and the UNESCO, offering a global context for comparison. • IPR and AI Interplay: A dedicated section on the relationship between AI and intellectual property rights, addressing concerns around AI-generated content, and ownership. • Civil and Criminal Liabilities: Insights into the complex issues of AI and legal liability, highlighting discussions of potential civil and criminal implications. • Legal Personhood of AI: An in-depth look at the concept of granting legal personhood to AI entities and the related legal and ethical implications. • Data Governance: The draft National Data Governance Framework Policy and its importance for managing government data and fostering an ecosystem for AI are covered. • Deeper Insights : 500 plus references for deeper understanding of the topics illustrated in the book
Author: Aileen Nielsen
Publisher: O'Reilly Media
ISBN: 1492075701
Category : Computers
Languages : en
Pages : 346
Get Book
Book Description
Fairness is an increasingly important topic as machine learning and AI more generally take over the world. While this is an active area of research, many realistic best practices are emerging at all steps along the data pipeline, from data selection and preprocessing to blackbox model audits. This book will guide you through the technical, legal, and ethical aspects of making your code fair and secure while highlighting cutting edge academic research and ongoing legal developments related to fairness and algorithms. There is mounting evidence that the widespread deployment of machine learning and artificial intelligence in business and government is reproducing the same biases we are trying to fight in the real world. For this reason, fairness is an increasingly important consideration for the data scientist. Yet discussions of what fairness means in terms of actual code are few and far between. This code will show you how to code fairly as well as cover basic concerns related to data security and privacy from a fairness perspective.
