Scholarly use of AI tools

Written in accessible language without mathematical formulas, this short book provides an overview of the wide and varied applications of artificial intelligence (AI) across the spectrum of physical sciences. Focusing in particular on AI's ability to extract patterns from data, known as machine learning (ML), the book includes a chapter on important machine learning algorithms and their respective applications in physics. It then explores the use of ML across a number of important sub-fields in more detail, ranging from particle, molecular and condensed matter physics, to astrophysics, cosmology and the theory of everything. The book covers such applications as the search for new particles and the detection of gravitational waves from the merging of black holes, and concludes by discussing what the future may hold.

This book marries social work and artificial intelligence to provide an introductory guide for using AI for social good. Following an introductory chapter laying out approaches and ethical principles of using AI for social work interventions, the book describes in detail an intervention to increase the spread of HIV information by using algorithms to determine the key individuals in a social network of homeless youth. Other chapters present interdisciplinary collaborations between AI and social work students, including a chatbot for sexual health information and algorithms to determine who is at higher stress among persons with Type 2 Diabetes. For students, academic researchers, industry leaders, and practitioners, these real-life examples from the USC Center for Artificial Intelligence in Society demonstrate how social work and artificial intelligence can be used in tandem for the greater good.

Abstract: As AI technologies are increasingly deployed in work, welfare, healthcare, and other domains, there is a growing realization not only of their power but of their problems. AI has the capacity to reinforce historical injustice, to amplify labor precarity, and to cement forms of racial and gendered inequality. An alternate set of values, paradigms, and priorities are urgently needed. How might we design and evaluate AI from an indigenous perspective? This article draws upon the five Tests developed by Māori scholar Sir Hirini Moko Mead. This framework, informed by Māori knowledge and concepts, provides a method for assessing contentious issues and developing a Māori position. This paper takes up these tests, considers how each test might be applied to data-driven systems, and provides a number of concrete examples. This intervention challenges the priorities that currently underpin contemporary AI technologies but also offers a rubric for designing and evaluating AI according to an indigenous knowledge system.

Abstract: Data governance remains an ongoing concern in Native communities. Almost all aspects of data about Indigenous people - from what is shared and where it is shared - are externally (ie, non-Native) controlled, which often renders Indigenous peoples invisible from mainstream narratives. This erasure has long resulted in inaccurate and usually stereotypic portrayals of Native Peoples that mischaracterize them, justify their oppression, and ultimately deny them justice. This article explores whether artificial intelligence ("AI") will serve as a "revolution" or a "new colonizer" for Indigenous peoples - an answer that ultimately hangs on which narratives AI developers embed into their technologies. Without purposefully centering Indigenous Peoples and accurate data from and about them, this emerging technology will only perpetuate colonial narratives and exacerbate existing disparities. Thus, Indigenous data - whether stories, instruments, values, or customs - must guide and serve as the foundation for 21st century data governance and AI development to promote equity and advance justice for Indigenous Peoples.

This book introduces readers to critical ethical concerns in the development and use of artificial intelligence. Offering clear and accessible information on central concepts and debates in AI ethics, it explores how related problems are now forcing us to address fundamental, age-old questions about human life, value, and meaning. In addition, the book shows how foundational and theoretical issues relate to concrete controversies, with an emphasis on understanding how ethical questions play out in practice. All topics are explored in depth, with clear explanations of relevant debates in ethics and philosophy, drawing on both historical and current sources. Questions in AI ethics are explored in the context of related issues in technology, regulation, society, religion, and culture, to help readers gain a nuanced understanding of the scope of AI ethics within broader debates and concerns. Written with both students and educators in mind, the book is easy to use, with key terms clearly explained, and numerous exercises designed to stretch and challenge. It offers readers essential insights into the evolving field of AI ethics. Moreover, it presents a range of methods and strategies that can be used to analyse and understand ethical questions, which are illustrated throughout with case studies.

The early 2020s have been marked by a surge of interest in artificial intelligence (AI), and it has grown to be one of the hottest topics in computer science, business technology research, and educational technologies. Despite AI winters in the 1970s and 1990s, where interest and subsequently adequate funding for AI research ceased, and as the technology and its usefulness become more perceptible, often with brilliant results, society is once again ready to investigate this powerful technology and its potential. However, a challenge arises when AI is called into question in an ethical context. It is important that we explore how it can contribute to the resolution of ethical, social, and environmental issues and also to address growing concerns around AI developing emergent bias as well as the human application of AI for malicious purposes. With recent AI-based writing technologies, concerns around academic integrity abound and challenge our perceptions of authenticity in writing. A careful assessment of these technologies, their usefulness and potential harm, and strategic solutions to maintaining ethical standards and regulation of the technology is a necessity for the maintenance of civilized life amidst these tools. Philosophy of Artificial Intelligence and Its Place in Society evaluates various aspects of artificial intelligence including the range of technologies, their advantages and disadvantages, and how AI systems operate. Spanning from machine learning to deep learning, philosophical insights, societal concerns, and the newest approaches to AI, it helps to develop an appreciation for and breadth of knowledge across the full range of AI sub-disciplines including neural networks, evolutionary computation, computer vision, robotics, expert systems, speech processing, and natural language processing. Led Dr. Luiz Moutinho of the University of Suffolk in the United Kingdom, who has won several awards for his academic literature, this book provides academic market-scholars; researchers and students of philosophy, sociology, economics, and education; as well as corporate scientists with a comprehensive collection of core research elements, concepts, advances, applications, evidence, and outcomes related to artificial intelligence.

Rapidly developing Artificial Intelligence (AI) systems hold tremendous potential to change various domains and exert considerable influence on societies and organizations alike. More than merely a technical discipline, AI requires interaction between various professions. Based on the results of fundamental literature and empirical research, this book addresses the management's awareness of the ethical and moral aspects of AI. It seeks to fill a literature gap and offer the management guidance on tackling Trustworthy AI Implementation (TAII) while also considering ethical dependencies within the company. The TAII Framework introduced here pursues a holistic approach to identifying systemic ethical relationships within the company ecosystem and considers corporate values, business models, and common goods aspects like the Sustainable Development Goals and the Universal Declaration of Human Rights. Further, it provides guidance on the implementation of AI ethics in organisations without requiring a deeper background in philosophy and considers the social impacts outside of the software and data engineering setting. Depending on the respective legal context or area of application, the TAII Framework can be adapted and used with a range of regulations and ethical principles. This book can serve as a case study or self-review for c-level managers and students who are interested in this field. It also offers valuable guidelines and perspectives for policymakers looking to pursue an ethical approach to AI.  

As Artificial Intelligence (AI) technologies rapidly progress, questions about the ethics of AI, in both the near-future and the long-term, become more pressing than ever. This volume features seventeen original essays by prominent AI scientists and philosophers and represents thestate-of-the-art thinking in this fast-growing field.Organized into four sections, this volume explores the issues surrounding how to build ethics into machines; ethical issues in specific technologies, including self-driving cars, autonomous weapon systems, surveillance algorithms, and sex robots; the long term risks of superintelligence; and whetherAI systems can be conscious or have rights.Though the use and practical applications of AI are growing exponentially, discussion of its ethical implications is still in its infancy. This volume provides an invaluable resource for thinking through the ethical issues surrounding AI today and for shaping the study and development of AI in thecoming years.