This open access book contributes to the discourse of Responsible Artificial Intelligence (AI) from an African perspective. It is a unique collection that brings together prominent AI scholars to discuss AI ethics from theoretical and practical African perspectives and makes a case for African values, interests, expectations and principles to underpin the design, development and deployment (DDD) of AI in Africa. The book is a first in that it pays attention to the socio-cultural contexts of Responsible AI that is sensitive to African cultures and societies. It makes an important contribution to the global AI ethics discourse that often neglects AI narratives from Africa despite growing evidence of DDD in many domains. Nine original contributions provide useful insights to advance the understanding and implementation of Responsible AI in Africa, including discussions on epistemic injustice of global AI ethics, opportunities and challenges, an examination of AI co-bots and chatbots in an African work space, gender and AI, a consideration of African philosophies such as Ubuntu in the application of AI, African AI policy, and a look towards a future of Responsible AI in Africa. This is an open access book.

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

This open access book tackles the pressing problem of integrating concerns related to Artificial Intelligence (AI) ethics into higher education curriculums aimed at future AI developers in Africa and beyond. For doing so, it analyzes the present and future states of AI ethics education in local computer science and engineering programs. The authors share relevant best practices and use cases for teaching, develop answers to ongoing organizational challenges, and reflect on the practical implications of different theoretical approaches to AI ethics. The book is of great interest to faculty members, researchers, and students in the fields of artificial intelligence, computer science, mathematics, computer engineering, and related areas, as well as higher education administration.

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.

This book is an Open Access Publication. The Guidelines for Trustworthy AI developed by the European Commission High-Level Expert Group on AI is a framework that has been developed to promote and achieve the trustworthiness of AI systems. It provides seven ethical principles that can be operationalised in socio-technical systems to realise responsible AI design and deployment. The content of this book is shaped around these principles. In chapter one, the concept of Human Agency and oversight will be described from the lens of a social-cultural understanding of Agency, Autonomy, and oversight including a debate on the place of human rights and power dynamics. Beyond the Trustworthy AI discourse, this book will appeal to the wider AI developers community, civil society, policymakers, ICT and the RRI community. It will also appeal to other subject areas within the Social Sciences and Humanities including; Law and Technology and Digital Culture. Damian Okaibedi Eke is Assistant Professor at the School of Computer Science, University of Nottingham, UK. Kutoma Wakunuma is Associate Professor in Information Systems at De Montfort University where she works within the Centre for Computing and Social Responsibility (CCSR). Simisola Akintoye is an Associate Professor of Law at Northumbria University School of Law. She is interested in multidisciplinary research around legal and ethical regulation of Emerging Technologies and Corporate Sustainability. George Ogoh is a Senior Research Fellow in the School of Computer Science, University of Nottingham.

AI in and for Africa: A Humanistic Perspective explores the convoluted intersection of artificial intelligence (AI) with Africa’s unique socio-economic realities. This book is the first of its kind to provide a comprehensive overview of how AI is currently being deployed on the African continent. Given the existence of significant disparities in Africa related to gender, race, labour, and power, the book argues that the continent requires different AI solutions to its problems, ones that are not founded on technological determinism or exclusively on the adoption of Eurocentric or Western-centric worldviews. It embraces a decolonial approach to exploring and addressing issues such as AI’s diversity crisis, the absence of ethical policies around AI that are tailor-made for Africa, the ever-widening digital divide, and the ongoing practice of dismissing African knowledge systems in the contexts of AI research and education. Although the book suggests a number of humanistic strategies with the goal of ensuring that Africa does not appropriate AI in a manner that is skewed in favour of a privileged few, it does not support the notion that the continent should simply opt for a "one-size-fits-all" solution either. Rather, in light of Africa’s rich diversity, the book embraces the need for plurality within different regions’ AI ecosystems. The book advocates that Africa-inclusive AI policies incorporate a relational ethics of care which explicitly addresses how Africa’s unique landscape is entwined in an AI ecosystem. The book also works to provide actionable AI tenets that can be incorporated into policy documents that suit Africa’s needs. This book will be of great interest to researchers, students, and readers who wish to critically appraise the different facets of AI in the context of Africa, across many areas that run the gamut from education, gender studies, and linguistics to agriculture, data science, and economics. This book is of special appeal to scholars in disciplines including anthropology, computer science, philosophy, and sociology, to name a few.

Artificial intelligence (AI) is upending life, work, and play as we know it, and it's only just getting started. The rise of AI is a milestone on par with the discovery of fire, the invention of the wheel, and the creation of the internet. In short, AI is going to change everything. For some, that's an exciting prospect. For others, it's terrifying. However you feel about AI, there's no escaping it, whether you're in a global metropolis or a farmer in rural KwaZulu-Natal. Dr Mark Nasila has been watching AI's ascent for over a decade, studying its effects on everything from agriculture and aviation to healthcare, education, entertainment, crime prevention, energy management, policy creation, finance, and anything in between, and applying them to his role at one of South Africa's most successful financial institutions, First National Bank, a division of FirstRand Group. African Artificial Intelligence is a comprehensive and fascinating journey, tracing the rise of AI and its evolution into the emerging technology underpinning all others – from connected devices and smart chatbots to the metaverse. Mark combines unexpected use cases and tales of cutting-edge innovation with a unique and potent argument: harnessing AI to solve Africa's problems requires embracing it from an African perspective. African nations can't afford to simply import AI solutions from afar. Instead, Mark contends, they need to rework, remix, and refine AI so it's able to meet uniquely African challenges in uniquely African ways, and to take advantage of the once-in-a-generation opportunity AI represents for every industry, sector, and person, everywhere.

The hidden costs of artificial intelligence, from natural resources and labor to privacy and freedom What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? In this book Kate Crawford reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequality. Drawing on more than a decade of research, award-winning science, and technology, Crawford reveals how AI is a technology of extraction: from the energy and minerals needed to build and sustain its infrastructure, to the exploited workers behind "automated" services, to the data AI collects from us. Rather than taking a narrow focus on code and algorithms, Crawford offers us a political and a material perspective on what it takes to make artificial intelligence and where it goes wrong. While technical systems present a veneer of objectivity, they are always systems of power. This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world.

The author investigates how to produce realistic and workable ethical codes or regulations in this rapidly developing field to address the immediate and realistic longer-term issues facing us. She spells out the key ethical debates concisely, exposing all sides of the arguments, and addresses how codes of ethics or other regulations might feasibly be developed, looking for pitfalls and opportunities, drawing on lessons learned in other fields, and explaining key points of professional ethics. The book provides a useful resource for those aiming to address the ethical challenges of AI research in meaningful and practical ways.