Building Responsible Ai Algorithms

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Building Responsible AI Algorithms

Author : Toju Duke
Publisher :
ISBN 13 : 9781484293072
Total Pages : 0 pages
Book Rating : 4.2/5 (93 download)

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Book Synopsis Building Responsible AI Algorithms by : Toju Duke

Download or read book Building Responsible AI Algorithms written by Toju Duke and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a Responsible AI framework and guides you through processes to apply at each stage of the machine learning (ML) life cycle, from problem definition to deployment, to reduce and mitigate the risks and harms found in artificial intelligence (AI) technologies. AI offers the ability to solve many problems today if implemented correctly and responsibly. This book helps you avoid negative impacts - that in some cases have caused loss of life - and develop models that are fair, transparent, safe, secure, and robust. The approach in this book raises your awareness of the missteps that can lead to negative outcomes in AI technologies and provides a Responsible AI framework to deliver responsible and ethical results in ML. It begins with an examination of the foundational elements of responsibility, principles, and data. Next comes guidance on implementation addressing issues such as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers. What You Will Learn Build AI/ML models using Responsible AI frameworks and processes Document information on your datasets and improve data quality Measure fairness metrics in ML models Identify harms and risks per task and run safety evaluations on ML models Create transparent AI/ML models Develop Responsible AI principles and organizational guidelines.

Responsible AI

Author : Sray Agarwal
Publisher : Springer Nature
ISBN 13 : 3030768600
Total Pages : 189 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Responsible AI by : Sray Agarwal

Download or read book Responsible AI written by Sray Agarwal and published by Springer Nature. This book was released on 2021-09-13 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is written for software product teams that use AI to add intelligent models to their products or are planning to use it. As AI adoption grows, it is becoming important that all AI driven products can demonstrate they are not introducing any bias to the AI-based decisions they are making, as well as reducing any pre-existing bias or discrimination. The responsibility to ensure that the AI models are ethical and make responsible decisions does not lie with the data scientists alone. The product owners and the business analysts are as important in ensuring bias-free AI as the data scientists on the team. This book addresses the part that these roles play in building a fair, explainable and accountable model, along with ensuring model and data privacy. Each chapter covers the fundamentals for the topic and then goes deep into the subject matter – providing the details that enable the business analysts and the data scientists to implement these fundamentals. AI research is one of the most active and growing areas of computer science and statistics. This book includes an overview of the many techniques that draw from the research or are created by combining different research outputs. Some of the techniques from relevant and popular libraries are covered, but deliberately not drawn very heavily from as they are already well documented, and new research is likely to replace some of it.

Responsible Artificial Intelligence

Author : Virginia Dignum
Publisher : Springer Nature
ISBN 13 : 3030303713
Total Pages : 127 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Responsible Artificial Intelligence by : Virginia Dignum

Download or read book Responsible Artificial Intelligence written by Virginia Dignum and published by Springer Nature. This book was released on 2019-11-04 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens.

Introducing MLOps

Author : Mark Treveil
Publisher : O'Reilly Media
ISBN 13 : 1098116445
Total Pages : 186 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Introducing MLOps by : Mark Treveil

Download or read book Introducing MLOps written by Mark Treveil and published by O'Reilly Media. This book was released on 2020-11-30 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized

Responsible AI

Author : Sray Agarwal
Publisher :
ISBN 13 : 9783030768614
Total Pages : 0 pages
Book Rating : 4.7/5 (686 download)

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Book Synopsis Responsible AI by : Sray Agarwal

Download or read book Responsible AI written by Sray Agarwal and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is written for software product teams that use AI to add intelligent models to their products or are planning to use it. As AI adoption grows, it is becoming important that all AI driven products can demonstrate they are not introducing any bias to the AI-based decisions they are making, as well as reducing any pre-existing bias or discrimination. The responsibility to ensure that the AI models are ethical and make responsible decisions does not lie with the data scientists alone. The product owners and the business analysts are as important in ensuring bias-free AI as the data scientists on the team. This book addresses the part that these roles play in building a fair, explainable and accountable model, along with ensuring model and data privacy. Each chapter covers the fundamentals for the topic and then goes deep into the subject matter - providing the details that enable the business analysts and the data scientists to implement these fundamentals. AI research is one of the most active and growing areas of computer science and statistics. This book includes an overview of the many techniques that draw from the research or are created by combining different research outputs. Some of the techniques from relevant and popular libraries are covered, but deliberately not drawn very heavily from as they are already well documented, and new research is likely to replace some of it. Hands-on approach to ensure easy practical implementation of the concepts discussed Most of the techniques covered are new, with only a few that refer to existing packages. For the techniques covered, the book goes deep into the subject matter and includes code to help the product teams implement these techniques for their products Also addresses the contribution that product owners and the business analysts make to the product being fair and explainable, explaining every topic in detail, including the math involved Covers the end-to-end view of what any software product team needs to do to be able to create a robust, successful and fair AI-driven product Most of the chapters include notes sections throughout to cover the topic in progress for all audiences. Non-technical readers will also benefit by the introductions and conclusions for the book and in each of the chapters.

Responsible AI

Author : CSIRO
Publisher : Addison-Wesley Professional
ISBN 13 : 0138073880
Total Pages : 424 pages
Book Rating : 4.1/5 (38 download)

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Book Synopsis Responsible AI by : CSIRO

Download or read book Responsible AI written by CSIRO and published by Addison-Wesley Professional. This book was released on 2023-12-08 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE FIRST PRACTICAL GUIDE FOR OPERATIONALIZING RESPONSIBLE AI ̃FROM MUL TI°LEVEL GOVERNANCE MECHANISMS TO CONCRETE DESIGN PATTERNS AND SOFTWARE ENGINEERING TECHNIQUES. AI is solving real-world challenges and transforming industries. Yet, there are serious concerns about its ability to behave and make decisions in a responsible way. Operationalizing responsible AI is about providing concrete guidelines to a wide range of decisionmakers and technologists on how to govern, design, and build responsible AI systems. These include governance mechanisms at the industry, organizational, and team level; software engineering best practices; architecture styles and design patterns; system-level techniques connecting code with data and models; and trade-offs in design decisions. Responsible AI includes a set of practices that technologists (for example, technology-conversant decision-makers, software developers, and AI practitioners) can undertake to ensure the AI systems they develop or adopt are trustworthy throughout the entire lifecycle and can be trusted by those who use them. The book offers guidelines and best practices not just for the AI part of a system, but also for the much larger software infrastructure that typically wraps around the AI. First book of its kind to cover the topic of operationalizing responsible AI from the perspective of the entire software development life cycle. Concrete and actionable guidelines throughout the lifecycle of AI systems, including governance mechanisms, process best practices, design patterns, and system engineering techniques. Authors are leading experts in the areas of responsible technology, AI engineering, and software engineering. Reduce the risks of AI adoption, accelerate AI adoption in responsible ways, and translate ethical principles into products, consultancy, and policy impact to support the AI industry. Online repository of patterns, techniques, examples, and playbooks kept up-to-date by the authors. Real world case studies to demonstrate responsible AI in practice. Chart the course to responsible AI excellence, from governance to design, with actionable insights and engineering prowess found in this defi nitive guide.

Platform and Model Design for Responsible AI

Author : Amita Kapoor
Publisher : Packt Publishing Ltd
ISBN 13 : 1803249773
Total Pages : 516 pages
Book Rating : 4.8/5 (32 download)

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Book Synopsis Platform and Model Design for Responsible AI by : Amita Kapoor

Download or read book Platform and Model Design for Responsible AI written by Amita Kapoor and published by Packt Publishing Ltd. This book was released on 2023-04-28 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Craft ethical AI projects with privacy, fairness, and risk assessment features for scalable and distributed systems while maintaining explainability and sustainability Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn risk assessment for machine learning frameworks in a global landscape Discover patterns for next-generation AI ecosystems for successful product design Make explainable predictions for privacy and fairness-enabled ML training Book Description AI algorithms are ubiquitous and used for tasks, from recruiting to deciding who will get a loan. With such widespread use of AI in the decision-making process, it's necessary to build an explainable, responsible, transparent, and trustworthy AI-enabled system. With Platform and Model Design for Responsible AI, you'll be able to make existing black box models transparent. You'll be able to identify and eliminate bias in your models, deal with uncertainty arising from both data and model limitations, and provide a responsible AI solution. You'll start by designing ethical models for traditional and deep learning ML models, as well as deploying them in a sustainable production setup. After that, you'll learn how to set up data pipelines, validate datasets, and set up component microservices in a secure and private way in any cloud-agnostic framework. You'll then build a fair and private ML model with proper constraints, tune the hyperparameters, and evaluate the model metrics. By the end of this book, you'll know the best practices to comply with data privacy and ethics laws, in addition to the techniques needed for data anonymization. You'll be able to develop models with explainability, store them in feature stores, and handle uncertainty in model predictions. What you will learn Understand the threats and risks involved in ML models Discover varying levels of risk mitigation strategies and risk tiering tools Apply traditional and deep learning optimization techniques efficiently Build auditable and interpretable ML models and feature stores Understand the concept of uncertainty and explore model explainability tools Develop models for different clouds including AWS, Azure, and GCP Explore ML orchestration tools such as Kubeflow and Vertex AI Incorporate privacy and fairness in ML models from design to deployment Who this book is for This book is for experienced machine learning professionals looking to understand the risks and leakages of ML models and frameworks, and learn to develop and use reusable components to reduce effort and cost in setting up and maintaining the AI ecosystem.

Human-Centered AI

Author : Ben Shneiderman
Publisher : Oxford University Press
ISBN 13 : 0192845292
Total Pages : 390 pages
Book Rating : 4.1/5 (928 download)

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Book Synopsis Human-Centered AI by : Ben Shneiderman

Download or read book Human-Centered AI written by Ben Shneiderman and published by Oxford University Press. This book was released on 2022 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.

Creator's Economy in Metaverse Platforms: Empowering Stakeholders Through Omnichannel Approach

Author : Singla, Babita
Publisher : IGI Global
ISBN 13 :
Total Pages : 306 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Creator's Economy in Metaverse Platforms: Empowering Stakeholders Through Omnichannel Approach by : Singla, Babita

Download or read book Creator's Economy in Metaverse Platforms: Empowering Stakeholders Through Omnichannel Approach written by Singla, Babita and published by IGI Global. This book was released on 2024-02-26 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the era of the metaverse, a big challenge permeates the digital landscapea challenge that resonates both with creators seeking to thrive in this dynamic space and policymakers attempting to navigate its uncharted territories. Creators, driven by innovation, grapple with a myriad of uncertainties in monetizing their virtual content effectively. Simultaneously, policymakers find themselves at a crossroads, caught between the rapid evolution of the virtual realm and the lack of clear regulatory guidelines. This struggle is exacerbated by the issue of cybersecurity threats that cast a shadow over the metaverse's transformative potential. It is within this context of challenges that Creator's Economy in Metaverse Platforms emerges, poised to tackle the pressing issues at the intersection of creativity, regulation, and the ever-expanding metaverse. Creator's Economy in Metaverse Platforms dissects, analyzes, and offers solutions to the multifaceted challenges prevailing in the metaverse. By addressing fundamental questions about the creator economy, the elusive concept of the metaverse economy, and the indispensable role policymakers play, the book provides a holistic understanding of the landscape. Delving into topics such as stakeholder engagement, digital asset management, and the intricacies of various monetization models, it equips readers with actionable insights. Not content with a reactive approach, the book takes a proactive stance, offering solutions to foster interoperability and create an ecosystem where creators and policymakers can mutually thrive. It envisions not just a book but a catalyst for transformative change in the metaverse.

Building Trust: Microsoft's Journey towards Responsible AI

Author : M.B. Chatfield
Publisher :
ISBN 13 :
Total Pages : 143 pages
Book Rating : 4./5 ( download)

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Book Synopsis Building Trust: Microsoft's Journey towards Responsible AI by : M.B. Chatfield

Download or read book Building Trust: Microsoft's Journey towards Responsible AI written by M.B. Chatfield and published by . This book was released on with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) has the potential to revolutionize the way we live, work, and learn. However, it is also important to ensure that AI is developed and used in a responsible way. Microsoft is committed to building trust in AI by developing and deploying AI systems that are fair, equitable, and accountable. This book explores Microsoft's journey towards responsible AI. It looks at the company's AI ethics principles, and the steps it is taking to ensure that AI is developed and used in an ethical and responsible way. Microsoft's AI Ethics Principles Microsoft's AI ethics principles are a set of guiding principles that the company uses to develop and deploy AI systems. The principles are designed to ensure that AI is developed and used in a way that is fair, equitable, and accountable. Building Trust in AI Microsoft is committed to building trust in AI by developing and deploying AI systems that are fair, equitable, and accountable. The company's AI ethics principles and responsible AI commitments are an important step towards achieving this goal. A Must-Read for AI Professionals Whether you're an AI professional, a business leader, or a concerned citizen, this book is an essential guide to understanding how Microsoft is working to build trust in AI. Join Microsoft on its journey towards responsible AI, and help shape a future where AI is used for good.

The Ethical Algorithm

Author : Michael Kearns
Publisher : Oxford University Press
ISBN 13 : 0190948213
Total Pages : 288 pages
Book Rating : 4.1/5 (99 download)

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Book Synopsis The Ethical Algorithm by : Michael Kearns

Download or read book The Ethical Algorithm written by Michael Kearns and published by Oxford University Press. This book was released on 2019-10-04 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions reflect racial and gender bias. Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services, and navigation apps. Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while continuing to inspire wondrous advances in technology.

AI Doctor

Author : Ronald M. Razmi, MD
Publisher : John Wiley & Sons
ISBN 13 : 1394240163
Total Pages : 373 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis AI Doctor by : Ronald M. Razmi, MD

Download or read book AI Doctor written by Ronald M. Razmi, MD and published by John Wiley & Sons. This book was released on 2024-01-31 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores the transformative impact of artificial intelligence (AI) on the healthcare industry AI Doctor: The Rise of Artificial Intelligence in Healthcare provides a timely and authoritative overview of the current impact and future potential of AI technology in healthcare. With a reader-friendly narrative style, this comprehensive guide traces the evolution of AI in healthcare, describes methodological breakthroughs, drivers and barriers of its adoption, discusses use cases across clinical medicine, administration and operations, and life sciences, and examines the business models for the entrepreneurs, investors, and customers. Detailed yet accessible chapters help those in the business and practice of healthcare recognize the remarkable potential of AI in areas such as drug discovery and development, diagnostics, therapeutics, clinical workflows, personalized medicine, early disease prediction, population health management, and healthcare administration and operations. Throughout the text, author Ronald M. Razmi, MD offers valuable insights on harnessing AI to improve health of the world population, develop more efficient business models, accelerate long-term economic growth, and optimize healthcare budgets. Addressing the potential impact of AI on the clinical practice of medicine, the business of healthcare, and opportunities for investors, AI Doctor: The Rise of Artificial Intelligence in Healthcare: Discusses what AI is currently doing in healthcare and its direction in the next decade Examines the development and challenges for medical algorithms Identifies the applications of AI in diagnostics, therapeutics, population health, clinical workflows, administration and operations, discovery and development of new clinical paradigms and more Presents timely and relevant information on rapidly expanding generative AI technologies, such as Chat GPT Describes the analysis that needs to be made by entrepreneurs and investors as they evaluate building or investing in health AI solutions Features a wealth of relatable real-world examples that bring technical concepts to life Explains the role of AI in the development of vaccines, diagnostics, and therapeutics during the COVID-19 pandemic AI Doctor: The Rise of Artificial Intelligence in Healthcare. A Guide for Users, Buyers, Builders, and Investors is a must-read for healthcare professionals, researchers, investors, entrepreneurs, medical and nursing students, and those building or designing systems for the commercial marketplace. The book's non-technical and reader-friendly narrative style also makes it an ideal read for everyone interested in learning about how AI will improve health and healthcare in the coming decades.

Grokking Artificial Intelligence Algorithms

Author : Rishal Hurbans
Publisher : Simon and Schuster
ISBN 13 : 1638355681
Total Pages : 392 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Grokking Artificial Intelligence Algorithms by : Rishal Hurbans

Download or read book Grokking Artificial Intelligence Algorithms written by Rishal Hurbans and published by Simon and Schuster. This book was released on 2020-07-20 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: "From start to finish, the best book to help you learn AI algorithms and recall why and how you use them." - Linda Ristevski, York Region District School Board ”This book takes an impossibly broad area of computer science and communicates what working developers need to understand in a clear and thorough way.” - David Jacobs, Product Advance Local Key Features Master the core algorithms of deep learning and AI Build an intuitive understanding of AI problems and solutions Written in simple language, with lots of illustrations and hands-on examples Creative coding exercises, including building a maze puzzle game and exploring drone optimization About The Book “Artificial intelligence” requires teaching a computer how to approach different types of problems in a systematic way. The core of AI is the algorithms that the system uses to do things like identifying objects in an image, interpreting the meaning of text, or looking for patterns in data to spot fraud and other anomalies. Mastering the core algorithms for search, image recognition, and other common tasks is essential to building good AI applications Grokking Artificial Intelligence Algorithms uses illustrations, exercises, and jargon-free explanations to teach fundamental AI concepts.You’ll explore coding challenges like detecting bank fraud, creating artistic masterpieces, and setting a self-driving car in motion. All you need is the algebra you remember from high school math class and beginning programming skills. What You Will Learn Use cases for different AI algorithms Intelligent search for decision making Biologically inspired algorithms Machine learning and neural networks Reinforcement learning to build a better robot This Book Is Written For For software developers with high school–level math skills. About the Author Rishal Hurbans is a technologist, startup and AI group founder, and international speaker. Table of Contents 1 Intuition of artificial intelligence 2 Search fundamentals 3 Intelligent search 4 Evolutionary algorithms 5 Advanced evolutionary approaches 6 Swarm intelligence: Ants 7 Swarm intelligence: Particles 8 Machine learning 9 Artificial neural networks 10 Reinforcement learning with Q-learning

Responsible Data Science

Author : Peter C. Bruce
Publisher : John Wiley & Sons
ISBN 13 : 1119741777
Total Pages : 304 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Responsible Data Science by : Peter C. Bruce

Download or read book Responsible Data Science written by Peter C. Bruce and published by John Wiley & Sons. This book was released on 2021-04-13 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of “Black box” algorithms that are difficult or impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box models Diagnose bias and unfairness within models using multiple metrics Audit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.

Responsible AI in the Age of Generative Models

Author : I. Almeida
Publisher : Now Next Later AI
ISBN 13 : 0975642219
Total Pages : 302 pages
Book Rating : 4.9/5 (756 download)

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Book Synopsis Responsible AI in the Age of Generative Models by : I. Almeida

Download or read book Responsible AI in the Age of Generative Models written by I. Almeida and published by Now Next Later AI. This book was released on 2024-03-11 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: In "Responsible AI in the Age of Generative Models: Governance, Ethics and Risk Management" we present a comprehensive guide to navigating the complex landscape of ethical AI development and deployment. As generative AI systems become increasingly powerful and ubiquitous, it is crucial to develop governance frameworks that mitigate potential risks while harnessing the technology's transformative potential. This book presents a rights-based approach, grounded in established human rights frameworks, to align AI systems with societal values and expectations. Divided into ten parts, the book covers a wide range of topics essential for responsible AI governance: Part I maps generative AI risks to specific human rights, while Part II presents a framework for institutionalizing rights-respecting AI practices throughout the development lifecycle. Part III delves into responsible data governance practices, and Part IV examines participatory approaches to data stewardship. Part V explores the roles and responsibilities of different organizational functions in operationalizing responsible AI, emphasizing the need for cross-functional collaboration. Transparency and algorithmic auditing are the focus of Part VI, followed by Part VII, which provides guidance on implementing effective multi-layered governance across the AI system lifecycle. Part VIII introduces maturity models for assessing an organization's responsible AI capabilities, and Part IX features an in-depth case study of Anthropic's innovative Constitutional AI approach. Finally, Part X analyzes emerging regulatory frameworks such as the EU AI Act and discusses the implications for businesses operating in multiple jurisdictions. "Responsible AI in the Age of Generative Models" equips readers with the knowledge, tools, and strategies needed to unlock the transformative potential of generative models while safeguarding human rights and promoting social justice. It is an essential resource for business leaders, policymakers, researchers, and anyone concerned about the future of AI governance. By embracing responsible AI as an imperative, we can work together to build a world where AI empowers and uplifts us all. This book is an invitation to engage in that critical conversation and take action towards a more equitable future.

After the Digital Tornado

Author : Kevin Werbach
Publisher : Cambridge University Press
ISBN 13 : 1108645259
Total Pages : 251 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis After the Digital Tornado by : Kevin Werbach

Download or read book After the Digital Tornado written by Kevin Werbach and published by Cambridge University Press. This book was released on 2020-07-23 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks powered by algorithms are pervasive. Major contemporary technology trends - Internet of Things, Big Data, Digital Platform Power, Blockchain, and the Algorithmic Society - are manifestations of this phenomenon. The internet, which once seemed an unambiguous benefit to society, is now the basis for invasions of privacy, massive concentrations of power, and wide-scale manipulation. The algorithmic networked world poses deep questions about power, freedom, fairness, and human agency. The influential 1997 Federal Communications Commission whitepaper “Digital Tornado” hailed the “endless spiral of connectivity” that would transform society, and today, little remains untouched by digital connectivity. Yet fundamental questions remain unresolved, and even more serious challenges have emerged. This important collection, which offers a reckoning and a foretelling, features leading technology scholars who explain the legal, business, ethical, technical, and public policy challenges of building pervasive networks and algorithms for the benefit of humanity. This title is also available as Open Access on Cambridge Core.

Intelligent Optimization Techniques for Business Analytics

Author : Bansal, Sanjeev
Publisher : IGI Global
ISBN 13 :
Total Pages : 377 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Intelligent Optimization Techniques for Business Analytics by : Bansal, Sanjeev

Download or read book Intelligent Optimization Techniques for Business Analytics written by Bansal, Sanjeev and published by IGI Global. This book was released on 2024-04-15 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, the convergence of cutting-edge algorithms and actionable insights in business is paramount for success. Scholars and practitioners grapple with the dilemma of optimizing data to drive efficiency, innovation, and competitiveness. The formidable challenge of effectively harnessing the immense power of intelligent optimization techniques and business analytics only increases as the volume of data grows exponentially, and the complexities of navigating the intricate landscape of business analytics becomes more daunting. This pressing issue underscores the critical need for a comprehensive solution, and Intelligent Optimization Techniques for Business Analytics is poised to provide much-needed answers. This groundbreaking book offers an all-encompassing solution to the challenges that academic scholars encounter in the pursuit of mastering the interplay between learning algorithms and intelligent optimization techniques for business analytics. Through a wealth of diverse perspectives and expert case studies, it illuminates the path to effectively implementing these advanced systems in real-world business scenarios. It caters not only to the scholarly community but also to industry professionals and policymakers, equipping them with the necessary tools and insights to excel in the realm of data-driven decision-making.