Machine Learning and Human Intelligence

2018

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Author: Rosemary Luckin
Publisher: UCL Institute of Education Press (University College London Institute of Education Press)
ISBN: 9781782772514
Category : Artificial intelligence
Languages : en
Pages : 0

Intelligence is at the heart of what makes us human, but the methods we use for identifying, talking about and valuing human intelligence are impoverished. We invest artificial intelligence (AI) with qualities it does not have and, in so doing, risk losing the capacity for education to pass on the emotional, collaborative, sensory and self-effective aspects of human intelligence that define us. To address this, Rosemary Luckin--leading expert in the application of AI in education - proposes a framework for understanding the complexity of human intelligence. She identifies the comparative limitation of AI when analyzed using the same framework, and offers clear-sighted recommendations for how educators can draw on what AI does best to nurture and expand our human capabilities.

Artificial Intelligence

2019-10-15

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Author: Melanie Mitchell
Publisher: Farrar, Straus and Giroux
ISBN: 0374715238
Category : Computers
Languages : en
Pages : 336

Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

Human and Machine Learning

2018-06-07

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Author: Jianlong Zhou
Publisher: Springer
ISBN: 3319904035
Category : Computers
Languages : en
Pages : 482

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications. This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making. This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.

The Myth of Artificial Intelligence

2021-04-06

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Author: Erik J. Larson
Publisher: Harvard University Press
ISBN: 0674983513
Category : Computers
Languages : en
Pages : 321

“Artificial intelligence has always inspired outlandish visions—that AI is going to destroy us, save us, or at the very least radically transform us. Erik Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. This is a timely, important, and even essential book.” —John Horgan, author of The End of Science Many futurists insist that AI will soon achieve human levels of intelligence. From there, it will quickly eclipse the most gifted human mind. The Myth of Artificial Intelligence argues that such claims are just that: myths. We are not on the path to developing truly intelligent machines. We don’t even know where that path might be. Erik Larson charts a journey through the landscape of AI, from Alan Turing’s early work to today’s dominant models of machine learning. Since the beginning, AI researchers and enthusiasts have equated the reasoning approaches of AI with those of human intelligence. But this is a profound mistake. Even cutting-edge AI looks nothing like human intelligence. Modern AI is based on inductive reasoning: computers make statistical correlations to determine which answer is likely to be right, allowing software to, say, detect a particular face in an image. But human reasoning is entirely different. Humans do not correlate data sets; we make conjectures sensitive to context—the best guess, given our observations and what we already know about the world. We haven’t a clue how to program this kind of reasoning, known as abduction. Yet it is the heart of common sense. Larson argues that all this AI hype is bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we are to make real progress, we must abandon futuristic talk and learn to better appreciate the only true intelligence we know—our own.

Artificial Intelligence/ Human Intelligence: An Indissoluble Nexus

2021-03-02

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Author: Richard J Wallace
Publisher: World Scientific
ISBN: 981123289X
Category : Computers
Languages : en
Pages : 368

This book presents a novel view of intelligence, and of the relationship between machine intelligence and human beings. From this perspective, machine intelligence is viewed as an artificial aid to human intelligence, and the two are seen to form a 'seamless web'.Having established this new perspective on intelligence, the book highlights some basic deficiencies of unaided human intelligence through case studies to show how human beings are capable of destroying existing intelligence networks as well as how they fail to recognize that such intelligence networks are needed. In many such cases, along with the other aspects of the problem, there is also a failure of discourse: bad arguments and the like dominate the discourse, and crucial aspects of the situation are overlooked or glossed over.The book then lays out a proposal on how to deal with this kind of problem — one that relies heavily on techniques developed in AI. This is done in the form of a new kind of grand challenge for AI, involving software monitors that are applied to discourse on major issues. All this is in keeping with the perspective on intelligence and AI presented in this book.

A Human's Guide to Machine Intelligence

2020-03-10

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Author: Kartik Hosanagar
Publisher: Penguin
ISBN: 0525560904
Category : Business & Economics
Languages : en
Pages : 274

A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. 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. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

Algorithms Are Not Enough

2020-10-13

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Author: Herbert L. Roitblat
Publisher: MIT Press
ISBN: 0262044129
Category : Computers
Languages : en
Pages : 340

Why a new approach is needed in the quest for general artificial intelligence. Since the inception of artificial intelligence, we have been warned about the imminent arrival of computational systems that can replicate human thought processes. Before we know it, computers will become so intelligent that humans will be lucky to kept as pets. And yet, although artificial intelligence has become increasingly sophisticated—with such achievements as driverless cars and humanless chess-playing—computer science has not yet created general artificial intelligence. In Algorithms Are Not Enough, Herbert Roitblat explains how artificial general intelligence may be possible and why a robopocalypse is neither imminent, nor likely. Existing artificial intelligence, Roitblat shows, has been limited to solving path problems, in which the entire problem consists of navigating a path of choices—finding specific solutions to well-structured problems. Human problem-solving, on the other hand, includes problems that consist of ill-structured situations, including the design of problem-solving paths themselves. These are insight problems, and insight is an essential part of intelligence that has not been addressed by computer science. Roitblat draws on cognitive science, including psychology, philosophy, and history, to identify the essential features of intelligence needed to achieve general artificial intelligence. Roitblat describes current computational approaches to intelligence, including the Turing Test, machine learning, and neural networks. He identifies building blocks of natural intelligence, including perception, analogy, ambiguity, common sense, and creativity. General intelligence can create new representations to solve new problems, but current computational intelligence cannot. The human brain, like the computer, uses algorithms; but general intelligence, he argues, is more than algorithmic processes.

Human + Machine

2018-03-20

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Author: Paul R. Daugherty
Publisher: Harvard Business Press
ISBN: 1633693872
Category : Computers
Languages : en
Pages : 264

AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.

AI and Developing Human Intelligence

2021-09-16

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Author: John Senior
Publisher: Routledge
ISBN: 1000449653
Category : Education
Languages : en
Pages : 223

As the relationship between AI machines and humans develops, we ask what it will mean to be an intelligent learner in an emerging, socio-dynamic learningscape. The need for a new global view of intelligence and education is the core discussion of this future-focussed collection of ideas, questions, and activities for learners to explore. This fascinating guide offers activities to understand what needs to be changed in our educations systems and our view of intelligence. As well as exploring AI, HI, the future of learning and caring for all learners, this book addresses fundamental questions such as: How do we educate ourselves for an increasingly uncertain future? What is the purpose of intelligence? How can a curriculum focussing on human curiosity and creativity be created? Who are we and what are we becoming? What will we invent now that AI exists? AI and Developing Human Intelligence will interest you, inform you, and empower your understanding of "intelligence" and where we are going on the next part of our journey in understanding what it is to be human now and tomorrow.

Human Compatible

2019

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Author: Stuart Jonathan Russell
Publisher: Penguin Books
ISBN: 0525558616
Category : Business & Economics
Languages : en
Pages : 354

A leading artificial intelligence researcher lays out a new approach to AI that will enable people to coexist successfully with increasingly intelligent machines.