Human + Machine

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

Get Book

Book Description
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.

Human + Machine

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

Get Book

Book Description
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.

Humans, Machines, and Data

Humans, Machines, and Data PDF Author: Brent M Eastwood
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 290

Get Book

Book Description
Are you ready for the warzones of tomorrow? Have you always been fascinated about the future of warfare? Do you want to discover the cutting-edge technology and strategies that will shape the way we solve conflicts? Offering an engaging and illuminating glimpse into the future of warfare across the world's land, sky, and sea, Humans, Machines, and Data delves into the latest military and scientific technology to explore how these advancements will impact the way nations conduct war. Covering human biotech, robotics, and even big data, you will also discover how broader social and environmental changes will impact every facet of warfare. From super soldiers and cyborgs to artificial intelligence and the emerging threats in cyberspace, warfare is changing by the second - and Humans, Machines, and Data provides you with a profound look at the evolution of combat. Here is just a little of what you will discover inside: The Sociology of Warfare How the Modern Age Has Created New Kinds of Warfare Why Artificial Intelligence and Robots Will Dominate the Warzones of Tomorrow How Social Shifts, Demographics, and Climate Change Will Define Our Future Cyborgs and Biotechnology - Why Super Soldiers Will Soon Become Reality A Breakdown of War in The Information Age Exploring Cyber Threats and Quantum Computing Deep Analysis of China, Russia, Iran, and North Korea And So Much More... Perfect for military enthusiasts, futurists, war buffs, and anyone interested in the technology of tomorrow, Humans, Machines, and Data offers you a unique and unparalleled look at how the world's militaries are evolving. Brent M. Eastwood, PhD is a Political Scientist and Emerging Threats expert. He was Founder and CEO of a tech firm that predicted world events using machine learning and artificial intelligence. He served in the U.S. Senate as a legislative fellow and advised a senator on defense and foreign policy issues. Brent has taught at George Washington University and George Mason University. He is a former U.S. Army Infantry officer. Go to brenteastwood.com for more about Brent.

How Humans Judge Machines

How Humans Judge Machines PDF Author: Cesar A. Hidalgo
Publisher: MIT Press
ISBN: 026236252X
Category : Computers
Languages : en
Pages : 257

Get Book

Book Description
How people judge humans and machines differently, in scenarios involving natural disasters, labor displacement, policing, privacy, algorithmic bias, and more. How would you feel about losing your job to a machine? How about a tsunami alert system that fails? Would you react differently to acts of discrimination depending on whether they were carried out by a machine or by a human? What about public surveillance? How Humans Judge Machines compares people's reactions to actions performed by humans and machines. Using data collected in dozens of experiments, this book reveals the biases that permeate human-machine interactions. Are there conditions in which we judge machines unfairly? Is our judgment of machines affected by the moral dimensions of a scenario? Is our judgment of machine correlated with demographic factors such as education or gender? César Hidalgo and colleagues use hard science to take on these pressing technological questions. Using randomized experiments, they create revealing counterfactuals and build statistical models to explain how people judge artificial intelligence and whether they do it fairly. Through original research, How Humans Judge Machines bring us one step closer tounderstanding the ethical consequences of AI.

Radically Human

Radically Human PDF Author: Paul Daugherty
Publisher: Harvard Business Press
ISBN: 1647821096
Category : Business & Economics
Languages : en
Pages : 152

Get Book

Book Description
Technology advances are making tech more . . . human. This changes everything you thought you knew about innovation and strategy. In their groundbreaking book, Human + Machine, Accenture technology leaders Paul R. Daugherty and H. James Wilson showed how leading organizations use the power of human-machine collaboration to transform their processes and their bottom lines. Now, as new AI powered technologies like the metaverse, natural language processing, and digital twins begin to rapidly impact both life and work, those companies and other pioneers across industries are tipping the balance even more strikingly toward the human side with technology-led strategy that is reshaping the very nature of innovation. In Radically Human, Daugherty and Wilson show this profound shift, fast-forwarded by the pandemic, toward more human—and more humane—technology. Artificial intelligence is becoming less artificial and more intelligent. Instead of data-hungry approaches to AI, innovators are pursuing data-efficient approaches that enable machines to learn as humans do. Instead of replacing workers with machines, they're unleashing human expertise to create human-centered AI. In place of lumbering legacy IT systems, they're building cloud-first IT architectures able to continuously adapt to a world of billions of connected devices. And they're pursuing strategies that will take their place alongside classic, winning business formulas like disruptive innovation. These against-the-grain approaches to the basic building blocks of business—Intelligence, Data, Expertise, Architecture, and Strategy (IDEAS)—are transforming competition. Industrial giants and startups alike are drawing on this radically human IDEAS framework to create new business models, optimize post-pandemic approaches to work and talent, rebuild trust with their stakeholders, and show the way toward a sustainable future. With compelling insights and fresh examples from a variety of industries, Radically Human will forever change the way you think about, practice, and win with innovation.

A Human's Guide to Machine Intelligence

A Human's Guide to Machine Intelligence PDF Author: Kartik Hosanagar
Publisher: Penguin
ISBN: 0525560904
Category : Business & Economics
Languages : en
Pages : 274

Get Book

Book Description
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.

Human-in-the-Loop Machine Learning

Human-in-the-Loop Machine Learning PDF Author: Robert Munro
Publisher: Simon and Schuster
ISBN: 1617296740
Category : Computers
Languages : en
Pages : 422

Get Book

Book Description
Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.

Human/Machine

Human/Machine PDF Author: Daniel Newman
Publisher: Kogan Page Publishers
ISBN: 074948425X
Category : Business & Economics
Languages : en
Pages : 265

Get Book

Book Description
Will the workplace of the future be overrun by machines and robots? Are the new frontiers of artificial intelligence (AI) on the cusp of dethroning us in efficiency, intelligence and innovative potential? Automation and AI will augment our human world and potential. The winners of the future of work are those that harness the power of machines to their advantage. Human/Machine is the only guide you need to understand the fourth industrial revolution. It sets out a road map to the challenges ahead, but also unlocks the wondrous opportunities that it offers. Human/Machine explores how we will work symbiotically with machines, detailing how institutions, companies, individuals and education providers will evolve to integrate seamlessly with new technologies. With exclusive case studies, this book offers a glimpse into the future and details how top companies are already thriving on this very special relationship. From gamification in job training to project management teams integrated with bots and predictive technologies that fix problems in the supply chain before they happen, the authors deliver a powerful manifesto for the adoption and celebration of automation and AI. In a much more fluid, skills-based economy, we will all need to prove our worth and future-proof our skills base. This book offers a blueprint to avoid being left behind and unearth the opportunities unique to human-machine partnership ecosystems.

Human and Machine Learning

Human and Machine Learning PDF Author: Jianlong Zhou
Publisher: Springer
ISBN: 3319904035
Category : Computers
Languages : en
Pages : 482

Get Book

Book Description
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.

Cyber-Humans

Cyber-Humans PDF Author: Woodrow Barfield
Publisher: Springer
ISBN: 3319250507
Category : Computers
Languages : en
Pages : 291

Get Book

Book Description
It is predicted that robots will surpass human intelligence within the next fifty years. The ever increasing speed of advances in technology and neuroscience, coupled with the creation of super computers and enhanced body parts and artificial limbs, is paving the way for a merger of both human and machine. Devices which were once worn on the body are now being implanted into the body, and as a result, a class of true cyborgs, who are displaying a range of skills beyond those of normal humans-beings, are being created. There are cyborgs which can see colour by hearing sound, others have the ability to detect magnetic fields, some are equipped with telephoto lenses to aid their vision or implanted computers to monitor their heart, and some use thought to communicate with a computer or to manipulate a robotic arm. This is not science-fiction, these are developments that are really happening now, and will continue to develop in the future. However, a range of legal and policy questions has arisen alongside this rise of artificial intelligence. Cyber-Humans provides a deep and unique perspective on the technological future of humanity, and describes how law and policy will be particularly relevant in creating a fair and equal society and protecting the liberties of different life forms which will emerge in the 21st century. Dr Woodrow (Woody) Barfield previously headed up the Sensory Engineering Laboratory, holding the position of Industrial and Systems Engineering Professor at the University of Washington. His research revolves around the design and use of wearable computers and augmented reality systems and holds both JD and LLM degrees in intellectual property law and policy. He has published over 350 articles and major presentations in the areas of computer science, engineering and law. He currently lives in Chapel Hill, NC, USA.

Human-Machine Shared Contexts

Human-Machine Shared Contexts PDF Author: William Lawless
Publisher: Academic Press
ISBN: 0128223790
Category : Computers
Languages : en
Pages : 448

Get Book

Book Description
Human-Machine Shared Contexts considers the foundations, metrics, and applications of human-machine systems. Editors and authors debate whether machines, humans, and systems should speak only to each other, only to humans, or to both and how. The book establishes the meaning and operation of “shared contexts between humans and machines; it also explores how human-machine systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems composed of humans and machines. This book explores how user interventions may improve the context for autonomous machines operating in unfamiliar environments or when experiencing unanticipated events; how autonomous machines can be taught to explain contexts by reasoning, inferences, or causality, and decisions to humans relying on intuition; and for mutual context, how these machines may interdependently affect human awareness, teams and society, and how these "machines" may be affected in turn. In short, can context be mutually constructed and shared between machines and humans? The editors are interested in whether shared context follows when machines begin to think, or, like humans, develop subjective states that allow them to monitor and report on their interpretations of reality, forcing scientists to rethink the general model of human social behavior. If dependence on machine learning continues or grows, the public will also be interested in what happens to context shared by users, teams of humans and machines, or society when these machines malfunction. As scientists and engineers "think through this change in human terms," the ultimate goal is for AI to advance the performance of autonomous machines and teams of humans and machines for the betterment of society wherever these machines interact with humans or other machines. This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning (ML) and artificial intelligence (AI) scientists and engineers, especially those engaged in research on autonomy, computational context, and human-machine shared contexts; advanced robotics scientists and engineers; scientists working with or interested in data issues for autonomous systems such as with the use of scarce data for training and operations with and without user interventions; social psychologists, scientists and physical research scientists pursuing models of shared context; modelers of the internet of things (IOT); systems of systems scientists and engineers and economists; scientists and engineers working with agent-based models (ABMs); policy specialists concerned with the impact of AI and ML on society and civilization; network scientists and engineers; applied mathematicians (e.g., holon theory, information theory); computational linguists; and blockchain scientists and engineers. Discusses the foundations, metrics, and applications of human-machine systems Considers advances and challenges in the performance of autonomous machines and teams of humans Debates theoretical human-machine ecosystem models and what happens when machines malfunction