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

An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI.

In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives.

An authoritative, up-to-date survey of the state of the art in artificial intelligence, written for non-specialists.

The variety, pace, and power of technological innovations that have emerged in the 21st Century have been breathtaking. These technological developments, which include advances in networked information and communications, biotechnology, neurotechnology, nanotechnology, robotics, and environmental engineering technology, have raised a number of vital and complex questions. Although these technologies have the potential to generate positive transformation and help address 'grand societal challenges', the novelty associated with technological innovation has also been accompanied by anxieties about their risks and destabilizing effects. Is there a potential harm to human health or the environment? What are the ethical implications? Do this innovations erode of antagonize values such as human dignity, privacy, democracy, or other norms underpinning existing bodies of law and regulation? These technological developments have therefore spawned a nascent but growing body of 'law and technology' scholarship, broadly concerned with exploring the legal, social and ethical dimensions of technological innovation. This handbook collates the many and varied strands of this scholarship, focusing broadly across a range of new and emerging technology and a vast array of social and policy sectors, through which leading scholars in the field interrogate the interfaces between law, emerging technology, and regulation. Structured in five parts, the handbook (I) establishes the collection of essays within existing scholarship concerned with law and technology as well as regulatory governance; (II) explores the relationship between technology development by focusing on core concepts and values which technological developments implicate; (III) studies the challenges for law in responding to the emergence of new technologies, examining how legal norms, doctrine and institutions have been shaped, challenged and destabilized by technology, and even how technologies have been shaped by legal regimes; (IV) provides a critical exploration of the implications of technological innovation, examining the ways in which technological innovation has generated challenges for regulators in the governance of technological development, and the implications of employing new technologies as an instrument of regulatory governance; (V) explores various interfaces between law, regulatory governance, and new technologies across a range of key social domains.

This new collection of essays follows in the footsteps of the successful volume Thinking Ahead - Essays on Big Data, Digital Revolution, and Participatory Market Society, published at a time when our societies were on a path to technological totalitarianism, as exemplified by mass surveillance reported by Edward Snowden and others. Meanwhile the threats have diversified and tech companies have gathered enough data to create detailed profiles about almost everyone living in the modern world - profiles that can predict our behavior better than our friends, families, or even partners. This is not only used to manipulate peoples’ opinions and voting behaviors, but more generally to influence consumer behavior at all levels. It is becoming increasingly clear that we are rapidly heading towards a cybernetic society, in which algorithms and social bots aim to control both the societal dynamics and individual behaviors. span lang="EN-US" style="font-family: However there are also silver linings: most of the threats that have accumulated over the past years have been identified and regulations are on the way to being introduced. Furthermore, entirely novel approaches based on blockchain technology and other developments derived from complexity science offer the possibility of entirely redefining collective trust and building platforms to support our core societal values. span lang="EN-US" style="font-family: This book conveys an encouraging vision of the future and provides a sketch of how it may look: The road to digital enlightenment is still open, but it needs to be taken now./pbrp

"Book abstract: The Oxford Handbook of AI Governance examines how artificial intelligence (AI) interacts with and influences governance systems. It also examines how governance systems influence and interact with AI. The handbook spans forty-nine chapters across nine major sections. These sections are (1) Introduction and Overview, (2) Value Foundations of AI Governance, (3) Developing an AI Governance Regulatory Ecosystem, (4) Frameworks and Approaches for AI Governance, (5) Assessment and Implementation of AI Governance, (6) AI Governance from the Ground Up, (7) Economic Dimensions of AI Governance, (8) Domestic Policy Applications of AI, and (9) International Politics and AI"--