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This book introduces the reader to Artificial Intelligence and its importance to our future. Campbell uses behavioural psychology, explores technology, economics, real-life and historical examples to predict five future scenarios with AI. Illustrating through speculative fiction, she describes possible futures after AI exceeds human capabilities. We are at a tipping point in history and must plan to ensure a successful co-existence with artificial intelligence. This book explains how to design for a future with AI so that, rather than herald our downfall, it helps us achieve a new renaissance.
Book Synopsis AI by Design by : Catriona Campbell
Download or read book AI by Design written by Catriona Campbell and published by CRC Press. This book was released on 2022-03-14 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the reader to Artificial Intelligence and its importance to our future. Campbell uses behavioural psychology, explores technology, economics, real-life and historical examples to predict five future scenarios with AI. Illustrating through speculative fiction, she describes possible futures after AI exceeds human capabilities. We are at a tipping point in history and must plan to ensure a successful co-existence with artificial intelligence. This book explains how to design for a future with AI so that, rather than herald our downfall, it helps us achieve a new renaissance.
This book introduces the reader to Artificial Intelligence and its importance to our future. Campbell uses behavioural psychology, explores technology, economics, real-life and historical examples to predict five future scenarios with AI. Illustrating through speculative fiction, she describes possible futures after AI exceeds human capabilities. We are at a tipping point in history and must plan to ensure a successful co-existence with artificial intelligence. This book explains how to design for a future with AI so that, rather than herald our downfall, it helps us achieve a new renaissance.
Book Synopsis AI by Design by : Catriona Campbell
Download or read book AI by Design written by Catriona Campbell and published by CRC Press. This book was released on 2022-03-13 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the reader to Artificial Intelligence and its importance to our future. Campbell uses behavioural psychology, explores technology, economics, real-life and historical examples to predict five future scenarios with AI. Illustrating through speculative fiction, she describes possible futures after AI exceeds human capabilities. We are at a tipping point in history and must plan to ensure a successful co-existence with artificial intelligence. This book explains how to design for a future with AI so that, rather than herald our downfall, it helps us achieve a new renaissance.
Advances in narrow artificial intelligence make possible agentive systems that do things directly for their users (like, say, an automatic pet feeder). They deliver on the promise of user-centered design, but present fresh challenges in understanding their unique promises and pitfalls. Designing Agentive Technology provides both a conceptual grounding and practical advice to unlock agentive technology’s massive potential.
Book Synopsis Designing Agentive Technology by : Christopher Noessel
Download or read book Designing Agentive Technology written by Christopher Noessel and published by Rosenfeld Media. This book was released on 2017-05-01 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in narrow artificial intelligence make possible agentive systems that do things directly for their users (like, say, an automatic pet feeder). They deliver on the promise of user-centered design, but present fresh challenges in understanding their unique promises and pitfalls. Designing Agentive Technology provides both a conceptual grounding and practical advice to unlock agentive technology’s massive potential.
Big Data, Big Design provides designers with the tools they need to harness the potential of machine learning and put it to use for good through thoughtful, human-centered, intentional design. Enter the world of Machine Learning (ML) and Artificial Intelligence (AI) through a design lens in this thoughtful handbook of practical skills, technical knowledge, interviews, essays, and theory, written specifically for designers. Gain an understanding of the design opportunities and design biases that arise when using predictive algorithms. Learn how to place design principles and cultural context at the heart of AI and ML through real-life case studies and examples. This portable, accessible guide will give beginners and more advanced AI and ML users the confidence to make reasoned, thoughtful decisions when implementing ML design solutions.
Book Synopsis Big Data, Big Design by : Helen Armstrong
Download or read book Big Data, Big Design written by Helen Armstrong and published by Chronicle Books. This book was released on 2021-11-04 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data, Big Design provides designers with the tools they need to harness the potential of machine learning and put it to use for good through thoughtful, human-centered, intentional design. Enter the world of Machine Learning (ML) and Artificial Intelligence (AI) through a design lens in this thoughtful handbook of practical skills, technical knowledge, interviews, essays, and theory, written specifically for designers. Gain an understanding of the design opportunities and design biases that arise when using predictive algorithms. Learn how to place design principles and cultural context at the heart of AI and ML through real-life case studies and examples. This portable, accessible guide will give beginners and more advanced AI and ML users the confidence to make reasoned, thoughtful decisions when implementing ML design solutions.
Architects who engaged with cybernetics, artificial intelligence, and other technologies poured the foundation for digital interactivity. In Architectural Intelligence, Molly Wright Steenson explores the work of four architects in the 1960s and 1970s who incorporated elements of interactivity into their work. Christopher Alexander, Richard Saul Wurman, Cedric Price, and Nicholas Negroponte and the MIT Architecture Machine Group all incorporated technologies—including cybernetics and artificial intelligence—into their work and influenced digital design practices from the late 1980s to the present day. Alexander, long before his famous 1977 book A Pattern Language, used computation and structure to visualize design problems; Wurman popularized the notion of “information architecture”; Price designed some of the first intelligent buildings; and Negroponte experimented with the ways people experience artificial intelligence, even at architectural scale. Steenson investigates how these architects pushed the boundaries of architecture—and how their technological experiments pushed the boundaries of technology. What did computational, cybernetic, and artificial intelligence researchers have to gain by engaging with architects and architectural problems? And what was this new space that emerged within these collaborations? At times, Steenson writes, the architects in this book characterized themselves as anti-architects and their work as anti-architecture. The projects Steenson examines mostly did not result in constructed buildings, but rather in design processes and tools, computer programs, interfaces, digital environments. Alexander, Wurman, Price, and Negroponte laid the foundation for many of our contemporary interactive practices, from information architecture to interaction design, from machine learning to smart cities.
Book Synopsis Architectural Intelligence by : Molly Wright Steenson
Download or read book Architectural Intelligence written by Molly Wright Steenson and published by MIT Press. This book was released on 2022-11-01 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Architects who engaged with cybernetics, artificial intelligence, and other technologies poured the foundation for digital interactivity. In Architectural Intelligence, Molly Wright Steenson explores the work of four architects in the 1960s and 1970s who incorporated elements of interactivity into their work. Christopher Alexander, Richard Saul Wurman, Cedric Price, and Nicholas Negroponte and the MIT Architecture Machine Group all incorporated technologies—including cybernetics and artificial intelligence—into their work and influenced digital design practices from the late 1980s to the present day. Alexander, long before his famous 1977 book A Pattern Language, used computation and structure to visualize design problems; Wurman popularized the notion of “information architecture”; Price designed some of the first intelligent buildings; and Negroponte experimented with the ways people experience artificial intelligence, even at architectural scale. Steenson investigates how these architects pushed the boundaries of architecture—and how their technological experiments pushed the boundaries of technology. What did computational, cybernetic, and artificial intelligence researchers have to gain by engaging with architects and architectural problems? And what was this new space that emerged within these collaborations? At times, Steenson writes, the architects in this book characterized themselves as anti-architects and their work as anti-architecture. The projects Steenson examines mostly did not result in constructed buildings, but rather in design processes and tools, computer programs, interfaces, digital environments. Alexander, Wurman, Price, and Negroponte laid the foundation for many of our contemporary interactive practices, from information architecture to interaction design, from machine learning to smart cities.
Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs
Book Synopsis Designing Autonomous AI by : Kence Anderson
Download or read book Designing Autonomous AI written by Kence Anderson and published by "O'Reilly Media, Inc.". This book was released on 2022-06-14 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs
The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.
Book Synopsis Human-Centered AI by : Ben Shneiderman
Download or read book Human-Centered AI written by Ben Shneiderman and published by Oxford University Press. This book was released on 2022 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.
Written for the novice AI programmer, this text introduces the reader to techniques such as finite state machines, fuzzy logic, neural networks and many others in an easy-to-understand language, supported with code samples throughout the text.
Book Synopsis AI for Game Developers by : David M Bourg
Download or read book AI for Game Developers written by David M Bourg and published by "O'Reilly Media, Inc.". This book was released on 2004-07-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written for the novice AI programmer, this text introduces the reader to techniques such as finite state machines, fuzzy logic, neural networks and many others in an easy-to-understand language, supported with code samples throughout the text.
Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples Key FeaturesAI-based examples to guide you in designing and implementing machine intelligenceBuild machine intelligence from scratch using artificial intelligence examplesDevelop machine intelligence from scratch using real artificial intelligenceBook Description AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions. What you will learnApply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google TranslateUnderstand chained algorithms combining unsupervised learning with decision treesSolve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graphLearn about meta learning models with hybrid neural networksCreate a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data loggingBuilding conversational user interfaces (CUI) for chatbotsWriting genetic algorithms that optimize deep learning neural networksBuild quantum computing circuitsWho this book is for Developers and those interested in AI, who want to understand the fundamentals of Artificial Intelligence and implement them practically. Prior experience with Python programming and statistical knowledge is essential to make the most out of this book.
Book Synopsis Artificial Intelligence By Example by : Denis Rothman
Download or read book Artificial Intelligence By Example written by Denis Rothman and published by Packt Publishing Ltd. This book was released on 2020-02-28 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples Key FeaturesAI-based examples to guide you in designing and implementing machine intelligenceBuild machine intelligence from scratch using artificial intelligence examplesDevelop machine intelligence from scratch using real artificial intelligenceBook Description AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions. What you will learnApply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google TranslateUnderstand chained algorithms combining unsupervised learning with decision treesSolve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graphLearn about meta learning models with hybrid neural networksCreate a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data loggingBuilding conversational user interfaces (CUI) for chatbotsWriting genetic algorithms that optimize deep learning neural networksBuild quantum computing circuitsWho this book is for Developers and those interested in AI, who want to understand the fundamentals of Artificial Intelligence and implement them practically. Prior experience with Python programming and statistical knowledge is essential to make the most out of this book.
Learn the fundamentals of Design Thinking and how to apply Design Thinking techniques in defining software development and AI solutions. Design Thinking is an approach to innovation which identifies problems and generates solution ideas that can be rapidly proven through prototyping. This book provides a brief history of Design Thinking and an overview of the process. It then drills down into more detail regarding methods and tools used in a Design Thinking workshops leading to useful prototypes. Guidance is provided on: Preparing for a Design Thinking Workshop Uncovering potential business problems that might be solved Prioritizing potential solutions Identifying and characterizing stakeholders Choosing the right prototypes for development Limiting scope and best practices in prototype building The book concludes with a discussion of best practices in operationalizing successful prototypes, and describes change management techniques critical for successful adoption. You can use the knowledge gained from reading this book to incorporate Design Thinking techniques in your software development and AI projects, and assure timely and successful delivery of solutions. What You Will Learn Gain foundational knowledge of what Design Thinking is and when to apply the technique Discover preparation and facilitation techniques used in workshops Know how ideas are generated and then validated through prototyping Understand implementation best practices, including change management considerations Who This Book Is For Business decision makers and project stakeholders as well as IT project owners who seek a method leading to fast development of successful software and AI prototypes demonstrating real business value. Also for data scientists, developers, and systems integrators who are interested in facilitating or utilizing Design Thinking workshops to drive momentum behind potential software development and AI projects.
Book Synopsis Design Thinking in Software and AI Projects by : Robert Stackowiak
Download or read book Design Thinking in Software and AI Projects written by Robert Stackowiak and published by Apress. This book was released on 2020-12-05 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the fundamentals of Design Thinking and how to apply Design Thinking techniques in defining software development and AI solutions. Design Thinking is an approach to innovation which identifies problems and generates solution ideas that can be rapidly proven through prototyping. This book provides a brief history of Design Thinking and an overview of the process. It then drills down into more detail regarding methods and tools used in a Design Thinking workshops leading to useful prototypes. Guidance is provided on: Preparing for a Design Thinking Workshop Uncovering potential business problems that might be solved Prioritizing potential solutions Identifying and characterizing stakeholders Choosing the right prototypes for development Limiting scope and best practices in prototype building The book concludes with a discussion of best practices in operationalizing successful prototypes, and describes change management techniques critical for successful adoption. You can use the knowledge gained from reading this book to incorporate Design Thinking techniques in your software development and AI projects, and assure timely and successful delivery of solutions. What You Will Learn Gain foundational knowledge of what Design Thinking is and when to apply the technique Discover preparation and facilitation techniques used in workshops Know how ideas are generated and then validated through prototyping Understand implementation best practices, including change management considerations Who This Book Is For Business decision makers and project stakeholders as well as IT project owners who seek a method leading to fast development of successful software and AI prototypes demonstrating real business value. Also for data scientists, developers, and systems integrators who are interested in facilitating or utilizing Design Thinking workshops to drive momentum behind potential software development and AI projects.
