LibGuides: Artificial Intelligence: Library Resources

eBooks/Artificial Intelligence

Artificial intelligence. [ebook] by Healey, Justin Artificial intelligence (AI) has been quietly evolving from futuristic sci-fi movie plots and into the factual present day. Put simply, AI is a computer system that can do tasks that humans need intelligence to do.
ISBN: 9781922274014

Publication Date: 2020
Advances in Artificial Intelligence Systems by K. Kamalanand (Editor) This book will help in fast decision making and solving complex real-world problems. In recent years, the fields of artificial intelligence along with nanotechnology, robotics and 3D printing have been referred to as the technologies of the future which will help mankind move towards a time of self-sustainability and development even in resource limited environments.
ISBN: 9781536154856

Publication Date: 2019-04-24
Machine Learning by Steven W. Knox AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONS PROSE Award Finalist 2019 Association of American Publishers Award for Professional and Scholarly Excellence Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author--an expert in the field--presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. The design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods. Understanding these principles leads to more flexible and successful applications. Machine Learning: a Concise Introduction also includes methods for optimization, risk estimation, and model selection-- essential elements of most applied projects. This important resource: Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods Presents R source code which shows how to apply and interpret many of the techniques covered Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions Contains useful information for effectively communicating with clients A volume in the popular Wiley Series in Probability and Statistics, Machine Learning: a Concise Introduction offers the practical information needed for an understanding of the methods and application of machine learning. STEVEN W. KNOX holds a Ph.D. in Mathematics from the University of Illinois and an M.S. in Statistics from Carnegie Mellon University. He has over twenty years' experience in using Machine Learning, Statistics, and Mathematics to solve real-world problems. He currently serves as Technical Director of Mathematics Research and Senior Advocate for Data Science at the National Security Agency.
ISBN: 9781119438984

Publication Date: 2018-03-15

Artificial Intelligence: Application

Artificial Intelligence in Medicine by Peter Szolovits (Editor) This book introduces the field of artificial intelligence in medicine, a new research area that combines sophisticated representational and computing techniques with the insights of expert physicians to produce tools for improving health care. An introductory chapter describes the historical and technical foundations of the work and provides an overview of the current state of the art and research directions. The authors then describe four prototype computer programs that tackle difficult clinical problems in a manner similar to that of an expert physician. The programs presented are internist, a diagnostic aid that combines a large database of disease/manifestation associations with techniques for problem formulation; expert and the Glaucoma Program which use physiological models for the diagnosis and treatment of eye disease; mycin, a rule-based program for diagnosis and therapy selection for infectious diseases; and the Digitalis Therapy Advisor, which aids the physician in prescribing the right dose of the drug digitalis and also explains its actions.
Call Number: HF5718 S557

ISBN: 9780429708459

Publication Date: 2019-03-13
Artificial Intelligence for Learning by Donald Clark Artificial intelligence is creating huge opportunities for workplace learning and employee development. However, it can be difficult for L&D professionals to assess what difference AI can make in their organization and where it is best implemented. Artificial Intelligence for Learning is the practical guide L&D practitioners need to understand what AI is and how to use it to improve all aspects of learning in the workplace. It includes specific guidance on how AI can provide content curation and personalization to improve learner engagement, how it can be implemented to improve the efficiency of evaluation, assessment and reporting and how chatbots can provide learner support to a global workforce. Artificial Intelligence for Learning debunks the myths and cuts through the hype around AI allowing L&D practitioners to feel confident in their ability to critically assess where artificial intelligence can make a measurable difference and where it is worth investing in. There is also critical discussion of how AI is an aid to learning and development, not a replacement as well as how it can be used to boost the effectiveness of workplace learning, reduce drop off rates in online learning and improve ROI. With real-world examples from companies who have effectively implemented AI and seen the benefits as well as case studies from organizations including Netflix, British Airways and the NHS, this book is essential reading for all L&D practitioners needing to understand AI and what it means in practice.
ISBN: 9781789660814

Publication Date: 2020-08-25

Artificial Intelligence: change management

Almost human: Anthropomorphism increases trust resilience in cognitive agents. We interact daily with computers that appear and behave like humans. Some researchers propose that people apply the same social norms to computers as they do to humans, suggesting that social psychological knowledge can be applied to our interactions with computers. In contrast, theories of human–automation interaction postulate that humans respond to machines in unique and specific ways. We believe that anthropomorphism—the degree to which an agent exhibits human characteristics—is the critical variable that may resolve this apparent contradiction across the formation, violation, and repair stages of trust. Three experiments were designed to examine these opposing viewpoints by varying the appearance and behavior of automated agents. Participants received advice that deteriorated gradually in reliability from a computer, avatar, or human agent. Our results showed (a) that anthropomorphic agents were associated with greater trust resilience, a higher resistance to breakdowns in trust; (b) that these effects were magnified by greater uncertainty; and c) that incorporating human-like trust repair behavior largely erased differences between the agents. Automation anthropomorphism is therefore a critical variable that should be carefully incorporated into any general theory of human–agent trust as well as novel automation design.

Artificial Intelligence: ethics and regulation

Artificial Intelligence: evolution, ethics and public policy by Saswat Sarangi; Pankaj Sharma What will the future be? A dystopian landscape controlled by machines or a brave new world full of possibilities? Perhaps the answer lies with Artificial Intelligence (AI)--a phenomenon much beyond technology that has, continues to, and will shape lives in ways we do not understand yet. This book traces the evolution of AI in contemporary history. It analyses how AI is primarily being driven by "capital" as the only "factor of production" and its consequences for the global political economy. It further explores the dystopian prospect of mass unemployment by AI and takes up the ethical aspects of AI and its possible use in undermining natural and fundamental rights. A tract for the times, this volume will be a major intervention in an area that is heavily debated but rarely understood. It will be essential reading for researchers and students of digital humanities, politics, economics, science and technology studies, physics, and computer science. It will also be key reading for policy makers, cyber experts and bureaucrats.
ISBN: 9780429865411

Publication Date: 2018-10-10

Artificial intelligence for decision-makers We propose an exercise with the purpose of providing a basic understanding of key concepts within AI and extending the understanding of AI beyond mathematics. The exercise allows participants to carry out analysis based on accounting data using visualization tools as well as to develop their own machine learning algorithms that can mimic their decisions. Finally, we also problematize the use of AI in decision-making, with such aspects as biases in data and/or ethical concerns.
How is the patent world responding to the AI revolution? There is no doubt that artificial intelligence (AI) is creeping into our lives slowly, but surely. From an outlier in the practical world for the past 60 years, AI is now driving developments in technology and business globally. In 2016, AI was identified as one of the technological breakthroughs that will drive the Fourth Industrial Revolution which is slated to significantly improve quality of life on a global scale while raising income levels. Recent numbers support this proposition as it is believed that, by 2020, AI will drive up to US$33 trillion of annual global economic growth. The speed at which AI will transform businesses will not only have an impact on customers/users but it will have a profound impact on how technology associated with the acceleration of innovation and disruption of businesses is created, protected and monetised.
Can AI be an inventor? The article examines whether inventions solely made by artificial intelligence (AI) inventors caT be protected through filing a patent application and be granted, just like those made by human beings. Topics discussed include advantages of AI, issues that arise from a global push towards incorporating technical solutions created by AI into patent law scope, and information on DABUS, an AI system developed by American AI expert, Stephen Thaler.
The Future of Inventing? ARTIFICIAL INTELLIGENCE MAY CHANGE OUR ROLE TO BEING DEFINERS OF NEEDS. The article offers the author's view regarding the impact of artificial intelligence in the future of inventions. Other topics discussed include the emergence of robot prototype, importance of writing and civilization. It also outlines the book "21 Lessons for the 21st Century" by Yuval Harari which shows that AI is more than linear improvement in programming.

Artificial Intelligence: biases

Revolutionary but a big business risk The article presents the Allianz Risk Barometer 2018 on the impact of artificial intelligence (AI) in business. According to Allianz, the effect of AI and other technologies ranks as the seventh-top risk in business, ahead of climate change and political risk. Allianz observes that autonomous chatbots that are being trained on language texts are prone to perpetuate human unfairness and prejudices.
Can We Keep Our Biases from Creeping into AI? Eminent industry leaders worry that the biggest risk tied to artificial intelligence is the militaristic downfall of humanity. But there’s a smaller community of people committed to addressing two more tangible risks: AI created with harmful biases built into its core, and AI that does not reflect the diversity of the users it serves. I am proud to be part of the second group of concerned practitioners. And I would argue that not addressing the issues of bias and diversity could lead to a different kind of weaponized AI. The good news is that AI is an opportunity to build technology with less human bias and built-in inequality than has been the case in previous innovations. But that will only happen if we expand AI talent pools and explicitly test AI-driven technologies for bias.
Google's DeepMind Has An Idea For Stopping Biased AI. The article offers information on the idea of artificial intelligence (AI) firm DeepMind on prevention of biased decision making in AI by teaching machine how to decide. Topics discussed include ethic division which promotes the importance of unbiased-decision making into AI and programming diversity, "Path-Specific Counterfactual Fairness," paper by chief executive officer (CEO) Demis Hassabis, and academic research on AI accountability and fairness.

Gartner research

Digital Ethics: From Compliance Duty to Competitive Differentiator Data and analytics leaders must move digital ethics beyond reactive checklist exercises toward proactive ethics by design. Protecting privacy, deploying responsible AI and ethically using other emerging technologies are key success factors for business and societal value creation.
Predicts 2021: Artificial Intelligence Core Technologies The development process for AI is clear to enterprises today, but the pressing need for AI operationalization will shift the focus to continuous delivery of AI-based systems. Data and analytics leaders must focus on technologies that bridge the gap between development and continuous value delivery.
Top 5 Priorities for Managing AI Risk Within Gartner’s MOST Framework AI operates as a “black box” in most organizations, so gaining clarity about AI models is the first step application leaders must take to gain the context needed for risk management. We outline the top five priorities for managing AI risk in your organization.
4 Stages of Ethical AI: Algorithmic Bias is Not the Problem but Part of the Solution Recently I have participated in a few long Gartner research threaded discussions on “explainable AI,” AI ethics and how to manage bias in particular. I’ve also recently attended a few discussions with machine learning luminaries such as Harry Shum, former EVP of AI and Research at Microsoft. In those discussions there was a lot of talk about bias in algorithms and how to recognize it and manage it. However, my position is that if you are primarily looking for bias in the algorithm you are looking in the wrong place. From these interactions, among other things, I believe there are 4 stages relevant to AI bias; real world bias, data bias, algorithm bias and business bias.

Database statistics and articles

Statista: AI dossier Artificial intelligence (AI), once the subject of people’s imaginations and main plot of science fiction movies for decades, is no longer a piece of fiction, but rather commonplace among people’s daily lives whether they realize it or not. AI refers to the ability of a computer or machine to mimic the competencies of the human mind, which often learns from previous experiences to understand and respond to language, decisions, and problems. These AI capabilities, such as computer vision and conversational interfaces, have become embedded throughout various industries’ standard business processes. The industries that have become prominent for AI adoption in organizations include high tech and telecommunications, financial services, and healthcare and pharmaceutical.
WARC: Succeeding in trying times: Behind PayPal’s and Scania’s DMA Awards-winning work Through a deep dive into two 2020 DMA Awards winners, WARC’s Chiara Manco looks at how challenging times can be the breeding ground for creative and effective work.
WARC: The importance of artificial intelligence, analytics and automation in the customer experience journey Artificial intelligence, analytics and automation are among the fundamental technologies that can give organisations the edge when it comes to enhancing customer experience.
WARC: Understanding AI advertising from the consumer perspective: What factors determine consumer appreciation of AI-created advertisements? In recent years, artificial intelligence (AI) technology has been used to create advertising messages. This study examined the factors that influence consumers’ overall appreciation of AI-created advertisements. The findings indicate that, in addition to its direct effect on consumer reactions to AI-created advertisements, consumers’ perceived objectivity of the general advertisement creation process positively influences machine heuristic—a rule of thumb that machines are more secure and trustworthy than humans. This effect boosted consumer appreciation of AI-created advertisements. Consumers’ perceived objectivity of advertisement creation negatively influenced perceived eeriness of AI advertising, which jeopardized consumer appreciation of AI-created advertisements. Consumers’ feelings of uneasiness with robots were found to have a positive influence on both machine heuristic and perceived eeriness of AI advertising.