Advertisement
| artificial intelligence technology landscape: Artificial Intelligence in Society OECD, 2019-06-11 The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises. |
| artificial intelligence technology landscape: WIPO Technology Trends 2019 - Artificial Intelligence World Intellectual Property Organization, 2019-01-21 The first report in a new flagship series, WIPO Technology Trends, aims to shed light on the trends in innovation in artificial intelligence since the field first developed in the 1950s. |
| artificial intelligence technology landscape: Deploying Machine Learning Robbie Allen, 2019-05 Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to big data and artificial intelligence, and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way. |
| artificial intelligence technology landscape: Practical Deep Learning for Cloud, Mobile, and Edge Anirudh Koul, Siddha Ganju, Meher Kasam, 2019-10-14 Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users |
| artificial intelligence technology landscape: Information Technology and the U.S. Workforce National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on Information Technology, Automation, and the U.S. Workforce, 2017-04-18 Recent years have yielded significant advances in computing and communication technologies, with profound impacts on society. Technology is transforming the way we work, play, and interact with others. From these technological capabilities, new industries, organizational forms, and business models are emerging. Technological advances can create enormous economic and other benefits, but can also lead to significant changes for workers. IT and automation can change the way work is conducted, by augmenting or replacing workers in specific tasks. This can shift the demand for some types of human labor, eliminating some jobs and creating new ones. Information Technology and the U.S. Workforce explores the interactions between technological, economic, and societal trends and identifies possible near-term developments for work. This report emphasizes the need to understand and track these trends and develop strategies to inform, prepare for, and respond to changes in the labor market. It offers evaluations of what is known, notes open questions to be addressed, and identifies promising research pathways moving forward. |
| artificial intelligence technology landscape: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| artificial intelligence technology landscape: Radically Human Paul Daugherty, H. James Wilson, 2022-04-26 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. |
| artificial intelligence technology landscape: Artificial Intelligence Harvard Business Review, 2019 Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business. |
| artificial intelligence technology landscape: Architectural Intelligence Molly Wright Steenson, 2017-12-22 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. |
| artificial intelligence technology landscape: OECD Digital Economy Outlook 2017 OECD, 2017-10-11 The OECD Digital Economy Outlook examines and documents the evolutions and emerging opportunities and challenges in the digital economy. It highlights how OECD countries and partner economies are taking advantage of ICTs and the Internet to meet their public policy objectives. |
| artificial intelligence technology landscape: Implications of Artificial Intelligence for Cybersecurity National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Intelligence Community Studies Board, Computer Science and Telecommunications Board, 2020-01-27 In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop. |
| artificial intelligence technology landscape: Artificial Intelligence for a Better Future Bernd Carsten Stahl, 2021-03-17 This open access book proposes a novel approach to Artificial Intelligence (AI) ethics. AI offers many advantages: better and faster medical diagnoses, improved business processes and efficiency, and the automation of boring work. But undesirable and ethically problematic consequences are possible too: biases and discrimination, breaches of privacy and security, and societal distortions such as unemployment, economic exploitation and weakened democratic processes. There is even a prospect, ultimately, of super-intelligent machines replacing humans. The key question, then, is: how can we benefit from AI while addressing its ethical problems? This book presents an innovative answer to the question by presenting a different perspective on AI and its ethical consequences. Instead of looking at individual AI techniques, applications or ethical issues, we can understand AI as a system of ecosystems, consisting of numerous interdependent technologies, applications and stakeholders. Developing this idea, the book explores how AI ecosystems can be shaped to foster human flourishing. Drawing on rich empirical insights and detailed conceptual analysis, it suggests practical measures to ensure that AI is used to make the world a better place. |
| artificial intelligence technology landscape: Turning Point Darrell M. West, John R. Allen, 2021-10-19 Artificial Intelligence is here, today. How can society make the best use of it? Until recently, artificial intelligence sounded like something out of science fiction. But the technology of artificial intelligence, AI, is becoming increasingly common, from self-driving cars to e-commerce algorithms that seem to know what you want to buy before you do. Throughout the economy and many aspects of daily life, artificial intelligence has become the transformative technology of our time. Despite its current and potential benefits, AI is little understood by the larger public and widely feared. The rapid growth of artificial intelligence has given rise to concerns that hidden technology will create a dystopian world of increased income inequality, a total lack of privacy, and perhaps a broad threat to humanity itself. In their compelling and readable book, two experts at Brookings discuss both the opportunities and risks posed by artificial intelligence--and how near-term policy decisions could determine whether the technology leads to utopia or dystopia. Drawing on in-depth studies of major uses of AI, the authors detail how the technology actually works. They outline a policy and governance blueprint for gaining the benefits of artificial intelligence while minimizing its potential downsides. The book offers major recommendations for actions that governments, businesses, and individuals can take to promote trustworthy and responsible artificial intelligence. Their recommendations include: creation of ethical principles, strengthening government oversight, defining corporate culpability, establishment of advisory boards at federal agencies, using third-party audits to reduce biases inherent in algorithms, tightening personal privacy requirements, using insurance to mitigate exposure to AI risks, broadening decision-making about AI uses and procedures, penalizing malicious uses of new technologies, and taking pro-active steps to address how artificial intelligence affects the workforce. Turning Point is essential reading for anyone concerned about how artificial intelligence works and what can be done to ensure its benefits outweigh its harm. |
| artificial intelligence technology landscape: The Myth of Artificial Intelligence Erik J. Larson, 2021-04-06 “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 technology landscape: Information Technology Innovation National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Panel on Artificial Intelligence, Committee on Depicting Innovation in Information Technology, 2020-11-30 Information technology (IT) is widely understood to be the enabling technology of the 21st century. IT has transformed, and continues to transform, all aspects of our lives: commerce and finance, education, energy, health care, manufacturing, government, national security, transportation, communications, entertainment, science, and engineering. IT and its impact on the U.S. economyâ€both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€continue to grow in size and importance. IT’s impacts on the U.S. economyâ€both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€continue to grow. IT enabled innovation and advances in IT products and services draw on a deep tradition of research and rely on sustained investment and a uniquely strong partnership in the United States among government, industry, and universities. Past returns on federal investments in IT research have been extraordinary for both U.S. society and the U.S. economy. This IT innovation ecosystem fuels a virtuous cycle of innovation with growing economic impact. Building on previous National Academies work, this report describes key features of the IT research ecosystem that fuel IT innovation and foster widespread and longstanding impact across the U.S. economy. In addition to presenting established computing research areas and industry sectors, it also considers emerging candidates in both categories. |
| artificial intelligence technology landscape: The AI Book Ivana Bartoletti, Anne Leslie, Shân M. Millie, 2020-06-29 Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important |
| artificial intelligence technology landscape: Artificial Intelligence for Sustainable Value Creation Pagani, Margherita, Champion, Renaud, 2021-09-07 Artificial Intelligence for Sustainable Value Creation provides a detailed and insightful exploration of both the possibilities and the challenges that accompany widespread Artificial Intelligence |
| artificial intelligence technology landscape: Artificial Intelligence for HR Ben Eubanks, 2018-12-03 HR professionals need to get to grips with artificial intelligence and the way it's changing the world of work. From using natural language processing to ensure job adverts are free from bias and gendered language to implementing chatbots to enhance the employee experience, AI has created a variety of opportunities for the HR function. Artificial Intelligence for HR empowers HR professionals to leverage this potential and use AI to improve efficiency and develop a talented and productive workforce. Outlining the current technology landscape as well as the latest AI developments, this book ensures that HR professionals fully understand what AI is and what it means for HR in practice. Covering everything from recruitment and retention to employee engagement and learning and development, Artificial Intelligence for HR outlines the value AI can add to HR. It also features discussions on the challenges that can arise from AI and how to deal with them, including data privacy, algorithmic bias and how to develop the skills of a workforce with the rise of automation, robotics and machine learning in order to make it more human, not less. Packed with practical advice, research and case studies from global organizations including Uber, IBM and Unilever, this book will equip HR professionals with the knowledge they need to leverage AI to recruit and develop a successful workforce and help their businesses thrive in the future. |
| artificial intelligence technology landscape: Artificial Intelligence in Practice Bernard Marr, 2019-04-15 Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce. |
| artificial intelligence technology landscape: The Future of Work Darrell M. West, 2018-05-15 Looking for ways to handle the transition to a digital economy Robots, artificial intelligence, and driverless cars are no longer things of the distant future. They are with us today and will become increasingly common in coming years, along with virtual reality and digital personal assistants. As these tools advance deeper into everyday use, they raise the question—how will they transform society, the economy, and politics? If companies need fewer workers due to automation and robotics, what happens to those who once held those jobs and don't have the skills for new jobs? And since many social benefits are delivered through jobs, how are people outside the workforce for a lengthy period of time going to earn a living and get health care and social benefits? Looking past today's headlines, political scientist and cultural observer Darrell M. West argues that society needs to rethink the concept of jobs, reconfigure the social contract, move toward a system of lifetime learning, and develop a new kind of politics that can deal with economic dislocations. With the U.S. governance system in shambles because of political polarization and hyper-partisanship, dealing creatively with the transition to a fully digital economy will vex political leaders and complicate the adoption of remedies that could ease the transition pain. It is imperative that we make major adjustments in how we think about work and the social contract in order to prevent society from spiraling out of control. This book presents a number of proposals to help people deal with the transition from an industrial to a digital economy. We must broaden the concept of employment to include volunteering and parenting and pay greater attention to the opportunities for leisure time. New forms of identity will be possible when the job no longer defines people's sense of personal meaning, and they engage in a broader range of activities. Workers will need help throughout their lifetimes to acquire new skills and develop new job capabilities. Political reforms will be necessary to reduce polarization and restore civility so there can be open and healthy debate about where responsibility lies for economic well-being. This book is an important contribution to a discussion about tomorrow—one that needs to take place today. |
| artificial intelligence technology landscape: Artificial Intelligence and Global Security Yvonne R. Masakowski, 2020-07-15 Artificial Intelligence and Global Security: Future Trends, Threats and Considerations brings a much-needed perspective on the impact of the integration of Artificial Intelligence (AI) technologies in military affairs. Experts forecast that AI will shape future military operations in ways that will revolutionize warfare. |
| artificial intelligence technology landscape: Applied Artificial Intelligence: Where AI Can Be Used In Business Francesco Corea, 2018-03-09 This book deals with artificial intelligence (AI) and its several applications. It is not an organic text that should be read from the first page onwards, but rather a collection of articles that can be read at will (or at need). The idea of this work is indeed to provide some food for thoughts on how AI is impacting few verticals (insurance and financial services), affecting horizontal and technical applications (speech recognition and blockchain), and changing organizational structures (introducing new figures or dealing with ethical issues). The structure of the chapter is very similar, so I hope the reader won’t find difficulties in establishing comparisons or understanding the differences between specific problems AI is being used for. The first chapter of the book is indeed showing the potential and the achievements of new AI techniques in the speech recognition domain, touching upon the topics of bots and conversational interfaces. The second and thirds chapter tackle instead verticals that are historically data-intensive but not data-driven, i.e., the financial sector and the insurance one. The following part of the book is the more technical one (and probably the most innovative), because looks at AI and its intersection with another exponential technology, namely the blockchain. Finally, the last chapters are instead more operative, because they concern new figures to be hired regardless of the organization or the sector, and ethical and moral issues related to the creation and implementation of new type of algorithms. |
| artificial intelligence technology landscape: Human-Centered AI Ben Shneiderman, 2022 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. |
| artificial intelligence technology landscape: Handbook of Research on Innovations in Technology and Marketing for the Connected Consumer Dadwal, Sumesh Singh, 2019-11-15 Connected customers, using a wide range of devices such as smart phones, tablets, and laptops have ushered in a new era of consumerism. Now more than ever, this change has prodded marketing departments to work with their various IT departments and technologists to expand consumers’ access to content. In order to remain competitive, marketers must integrate marketing campaigns across these different devices and become proficient in using technology. The Handbook of Research on Innovations in Technology and Marketing for the Connected Consumer is a pivotal reference source that develops new insights into applications of technology in marketing and explores effective ways to reach consumers through a wide range of devices. While highlighting topics such as cognitive computing, artificial intelligence, and virtual reality, this publication explores practices of technology-empowered digital marketing as well as the methods of applying practices to less developed countries. This book is ideally designed for marketers, managers, advertisers, branding teams, application developers, IT specialists, academicians, researchers, and students. |
| artificial intelligence technology landscape: Technology and Privacy Philip Agre, Marc Rotenberg, 1998 Over the last several years, the realm of technology and privacy has been transformed, creating a landscape that is both dangerous and encouraging. Significant changes include large increases in communications bandwidths; the widespread adoption of computer networking and public-key cryptography; new digital media that support a wide range of social relationships; a massive body of practical experience in the development and application of data-protection laws; and the rapid globalization of manufacturing, culture, and policy making. The essays in this book provide a new conceptual framework for the analysis and debate of privacy policy and for the design and development of information systems. |
| artificial intelligence technology landscape: Competing in the Age of AI Marco Iansiti, Karim R. Lakhani, 2020-01-07 a provocative new book — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how collisions between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI. |
| artificial intelligence technology landscape: Introduction to Artificial Intelligence Simplilearn, 2020-12-14 This AI beginner’s guide aims to take the readers through the current AI landscape, provides the key fundamentals and terminologies of AI, and offers practical guidelines on why and how you can be a part of the AI revolution, and also the ways in which you can scale up your AI career. |
| artificial intelligence technology landscape: Preparing for the Future of Artificial Intelligence Committee on Technology National Science and Technology Council, Committee on Technology, 2016-10-30 Advances in Artificial Intelligence (AI) technology have opened up new markets and new opportunities for progress in critical areas such as health, education, energy, and the environment. In recent years, machines have surpassed humans in the performance of certain specific tasks, such as some aspects of image recognition. Experts forecast that rapid progress in the field of specialized artificial intelligence will continue. Although it is very unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the next 20 years, it is to be expected that machines will reach and exceed human performance on more and more tasks. As a contribution toward preparing the United States for a future in which AI plays a growing role, this report surveys the current state of AI, its existing and potential applications, and the questions that are raised for society and public policy by progress in AI. The report also makes recommendations for specific further actions by Federal agencies and other actors. |
| artificial intelligence technology landscape: Reinventing Technological Innovations with Artificial Intelligence Adarsh Garg, 2023-09-22 Reinventing Technological Innovations with Artificial Intelligence delves into the transformative impact of Augmented and Virtual Reality (AVR) technology across industries. The book explores the merging of real and digital worlds, paving the way for personalized experiences in areas such as tourism, marketing, education, and more. With the potential to redefine business practices and societal norms in the era of Industry 4.0, AVR technologies hold untapped potential beyond gaming and entertainment. This volume presents a comprehensive overview of the current landscape, challenges, and prospects of integrating AVR with Artificial Intelligence (AI) for innovation and sustainability in various domains. The book presents 11 edited chapters contributed by technology and innovation experts that explore applications of AI, AR and VR technologies in different sectors in both public and private sectors. The editors have included reviews of technologies that impact human resource management, corporate social responsibility, healthcare, supply chain and criminal investigation. The reviews also highlight the role of AI in sustainable agriculture and smart cities. Key Features: Unveils the role of AVR in transforming real surroundings into digitally enhanced personal experiences. Explores AVR's applications beyond gaming in diverse sectors like marketing, construction, education, and more. Discusses challenges such as technical limitations, high costs, and resistance to adopting AVR. Addresses the need to enhance the reliability and effectiveness of AVR technologies in various industries. Provides a comprehensive perspective on AI innovations, AR, and VR technologies with real-world examples. The book is an informative reference for researchers, professionals, and experts in technology, innovation, who are interested in the convergence of Augmented and Virtual Reality with AI for practical applications in diverse industries. |
| artificial intelligence technology landscape: Contemporary Artificial Intelligence Richard E. Neapolitan, Xia Jiang, 2012-08-25 The notion of artificial intelligence (AI) often sparks thoughts of characters from science fiction, such as the Terminator and HAL 9000. While these two artificial entities do not exist, the algorithms of AI have been able to address many real issues, from performing medical diagnoses to navigating difficult terrain to monitoring possible failures of spacecrafts. Exploring these algorithms and applications, Contemporary Artificial Intelligence presents strong AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more. One of the first AI texts accessible to students, the book focuses on the most useful problem-solving strategies that have emerged from AI. In a student-friendly way, the authors cover logic-based methods; probability-based methods; emergent intelligence, including evolutionary computation and swarm intelligence; data-derived logical and probabilistic learning models; and natural language understanding. Through reading this book, students discover the importance of AI techniques in computer science. |
| artificial intelligence technology landscape: Artificial Intelligence Jerry Kaplan, 2016 Over the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it will also upend our labor markets, reshuffle our social order, and strain our private and public institutions. Eventually it may alter how we see our place in the universe, as machines pursue goals independent of their creators and outperform us in domains previously believed to be the sole dominion of humans. Whether we regard them as conscious or unwitting, revere them as a new form of life or dismiss them as mere clever appliances, is beside the point. They are likely to play an increasingly critical and intimate role in many aspects of our lives. The emergence of systems capable of independent reasoning and action raises serious questions about just whose interests they are permitted to serve, and what limits our society should place on their creation and use. Deep ethical questions that have bedeviled philosophers for ages will suddenly arrive on the steps of our courthouses. Can a machine be held accountable for its actions? Should intelligent systems enjoy independent rights and responsibilities, or are they simple property? Who should be held responsible when a self-driving car kills a pedestrian? Can your personal robot hold your place in line, or be compelled to testify against you? If it turns out to be possible to upload your mind into a machine, is that still you? The answers may surprise you. |
| artificial intelligence technology landscape: The Book of Why Judea Pearl, Dana Mackenzie, 2018-05-15 A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence Correlation is not causation. This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why. |
| artificial intelligence technology landscape: Regulating Artificial Intelligence Thomas Wischmeyer, Timo Rademacher, 2019-11-29 This book assesses the normative and practical challenges for artificial intelligence (AI) regulation, offers comprehensive information on the laws that currently shape or restrict the design or use of AI, and develops policy recommendations for those areas in which regulation is most urgently needed. By gathering contributions from scholars who are experts in their respective fields of legal research, it demonstrates that AI regulation is not a specialized sub-discipline, but affects the entire legal system and thus concerns all lawyers. Machine learning-based technology, which lies at the heart of what is commonly referred to as AI, is increasingly being employed to make policy and business decisions with broad social impacts, and therefore runs the risk of causing wide-scale damage. At the same time, AI technology is becoming more and more complex and difficult to understand, making it harder to determine whether or not it is being used in accordance with the law. In light of this situation, even tech enthusiasts are calling for stricter regulation of AI. Legislators, too, are stepping in and have begun to pass AI laws, including the prohibition of automated decision-making systems in Article 22 of the General Data Protection Regulation, the New York City AI transparency bill, and the 2017 amendments to the German Cartel Act and German Administrative Procedure Act. While the belief that something needs to be done is widely shared, there is far less clarity about what exactly can or should be done, or what effective regulation might look like. The book is divided into two major parts, the first of which focuses on features common to most AI systems, and explores how they relate to the legal framework for data-driven technologies, which already exists in the form of (national and supra-national) constitutional law, EU data protection and competition law, and anti-discrimination law. In the second part, the book examines in detail a number of relevant sectors in which AI is increasingly shaping decision-making processes, ranging from the notorious social media and the legal, financial and healthcare industries, to fields like law enforcement and tax law, in which we can observe how regulation by AI is becoming a reality. |
| artificial intelligence technology landscape: 2021 International Conference on Applications and Techniques in Cyber Intelligence Jemal Abawajy, Zheng Xu, Mohammed Atiquzzaman, Xiaolu Zhang, 2021-06-23 This book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to secure our cyberfuture. The book describes approaches and findings that are of interest to business professionals and governments seeking to secure our data and underpin infrastructures, as well as to individual users. |
| artificial intelligence technology landscape: Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance El Bachir Boukherouaa, Mr. Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Mr. Alin T Mirestean, Rangachary Ravikumar, 2021-10-22 This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight. |
| artificial intelligence technology landscape: AI in the Wild Peter Dauvergne, 2020-09-15 Examining the potential benefits and risks of using artificial intelligence to advance global sustainability. Drones with night vision are tracking elephant and rhino poachers in African wildlife parks and sanctuaries; smart submersibles are saving coral from carnivorous starfish on Australia's Great Barrier Reef; recycled cell phones alert Brazilian forest rangers to the sound of illegal logging. The tools of artificial intelligence are being increasingly deployed in the battle for global sustainability. And yet, warns Peter Dauvergne, we should be cautious in declaring AI the planet's savior. In AI in the Wild, Dauvergne avoids the AI industry-powered hype and offers a critical view, exploring both the potential benefits and risks of using artificial intelligence to advance global sustainability. |
| artificial intelligence technology landscape: Robot-Proof, revised and updated edition Joseph E. Aoun, 2024-10-15 A fresh look at a “robot-proof” education in the new age of generative AI. In 2017, Robot-Proof, the first edition, foresaw the advent of the AI economy and called for a new model of higher education designed to help human beings flourish alongside smart machines. That economy has arrived. Creative tasks that, seven years ago, seemed resistant to automation can now be performed with a simple prompt. As a result, we must now learn not only to be conversant with these technologies, but also to comprehend and deploy their outputs. In this revised and updated edition, Joseph Aoun rethinks the university’s mission for a world transformed by AI, advocating for the lifelong endeavor of a “robot-proof” education. Aoun puts forth a framework for a new curriculum, humanics, which integrates technological, data, and human literacies in an experiential setting, and he renews the call for universities to embrace lifelong learning through a social compact with government, employers, and learners themselves. Drawing on the latest developments and debates around generative AI, Robot-Proof is a blueprint for the university as a force for human reinvention in an era of technological change—an era in which we must constantly renegotiate the shifting boundaries between artificial intelligence and the capacities that remain uniquely human. |
| artificial intelligence technology landscape: Artificial Intelligence Dr. Prabhat Kumar, 2019-09-19 Learn how Artificial Intelligence (AI) strikes deeper roots with new products and services DESCRIPTION Our World of personal life and work is set to change dramatically over the next decade as Artificial Intelligence (AI) strikes deeper roots with new products and services; robots take charge of manufacturing and warehouses; and drones reach the remote corners to deliver orders to customers. AI services and robots will particularly facilitate the life of the older people and the visually-impaired. AI has raised the bar of competition in the international market place and countries are busy implementing policies that will keep them ahead in the race of the next-generational change. AI will raise the productivity of the economy and provide a lot more convenience, though there is bound to be a short-term pain in the transformational process. This book explains the concepts of AI with lots of real-life examples. While the big tech companies like Alphabet, Amazon, Apple, Facebook, IBM, Microsoft (3AFIM) of the US and Alibaba, Baidu, JD.com, Tencent (ABJY) of chine are busy re-fashioning their businesses by integrating AI into all products and services they deliver, startups on the other hand are disrupting the traditional business models in finance, e-commerce, healthcare, HR management, fashion, law and even agriculture. AI-driven smart cities would provide a richer quality of living to their residents. This book also provide an insight into various social and ethical issues, such as monopoly of the big tech, ownership of data, personal privacy, job losses and autonomy of technology particularly in military warfare, which poses an existential threat to mankind. Future of AI is also discusses taking a 360-degree approach. Ê AI offers a huge economic opportunity, but a thoughtful approach for democratization of technology is required to provide benefits to all sections of the society. Nations and communities need to come together to evolve models that will be sustainable in the long run. KEY FEATURES The book gives a lucid introduction to the idea of AI. The book is insightful for an academic understanding of AI in the concept of Legal Personality meant for Ê every person, including professionals in the field of Technology, Finance, Healthcare, HR Management, Agriculture.. The book gives a idea about many new AI products and services being released in the market. The book presents various social, ethical, and political challenges including significant risk to humanity. WHAT WILL YOU LEARN Able to solve real-life AI case studies. Understand the future of AI solutions and adapt quickly to them. WHO THIS BOOK IS FOR It is a simple, explanatory, and descriptive guide for developers, technology consultants, and those interested in AI and wants to understand the fundamentals of AI and implement it practically by devising smart solutions. Table of Contents _1. Ê Ê AI, How it is transforming Life and BusinessÊ 2. Ê Ê Understanding AI and Associated TechnologiesÊ 3. Ê Ê AI in the ÔbullÕ run 4. Ê Ê Data, the Engine of AIÊ 5. Ê Ê Big tech bets big on AI 6. Ê Ê AI Startups that transformed Businesses 7. Ê Ê AI Startups in FinanceÊ 8. Ê Ê AI Startups in Healthcare 9. Ê Ê AI Startups in Human ResourceÊ 10. Ê AI Startups in Fashion, Law, Agriculture and Other Areas 11. Ê Ethical, Social and Political issues in AI 12. Ê Future of AI 13. Ê Conclusion |
| artificial intelligence technology landscape: Artificial Intelligence Margaret A. Boden, 2018-08-13 The applications of Artificial Intelligence lie all around us; in our homes, schools and offices, in our cinemas, in art galleries and - not least - on the Internet. The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle. As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. In this Very Short Introduction , Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. |
| artificial intelligence technology landscape: The Atlas of AI Kate Crawford, 2021-04-06 The hidden costs of artificial intelligence, from natural resources and labor to privacy and freedom What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? In this book Kate Crawford reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequality. Drawing on more than a decade of research, award-winning science, and technology, Crawford reveals how AI is a technology of extraction: from the energy and minerals needed to build and sustain its infrastructure, to the exploited workers behind automated services, to the data AI collects from us. Rather than taking a narrow focus on code and algorithms, Crawford offers us a political and a material perspective on what it takes to make artificial intelligence and where it goes wrong. While technical systems present a veneer of objectivity, they are always systems of power. This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world. |
The Artificial Intelligence (AI) global regulatory landscape - EY
Based on EY teams analysis, we identified five key regulatory trends for policymakers and companies to consider as they work toward enhancing confidence in the use of AI.
Navigating the AI landscape - Moody's
We conducted primary research with a view to finding out more and exploring attitudes towards AI within a range of target audiences and regions, covering the following topics: Is AI a passing …
Artificial Intelligence in Government: The Federal and State …
own technology and data infrastructure to ensure the reliability, safety and security of AI applications. This brief reviews the current legislative and regulatory landscape at both federal …
GENERATIVE ARTIFICIAL INTELLIGENCE: THE COMPETITIVE …
The recent success of generative artificial intelligence (GenAI) tools capable of generating human-like content has shaken digital markets and started a new technological race. GenAI is …
The Patent Landscape of Artificial Intelligence
• What is Artificial Intelligence and how do sub-technologies such as Machine Learning or Deep Learning differ from it? • What are the countries in which Artificial Intelligence is being …
Artificial Intelligence Technology Landscape infographic
Artificial Intelligence is computer systems that exhibit human like intelligence. It is a group of science fields and technologies concerned with creating machines take intelligent actions …
Generative AI Governance: Shaping a Collective Global Future
Apr 5, 2023 · The global landscape for artificial intelligence (AI) governance is complex and rapidly evolving, given the speed and breadth of technological advancements, as well as …
HOLONIQ. GLOBAL INTELLIGENCE Global AI Strategy Landscape
released “Artificial Intelligence: Shaping a Future New Zealand.” Norway January 2020, Norway issued its National Strategy for Artificial Intelligence. Pakistan Presidential Initiative for Artificial …
ARTIFICIAL INTELLIGENCE RELATED INVENTIONS - Royal Society
The Royal Society’s Disruptive Technology for Research project aims to understand the landscape of data-driven and artificial intelligence-based technologies across different fields of …
Artificial Intelligence In The 21st Century [PDF]
Artificial Intelligence in the 21st Century: A Journey into the Uncharted Artificial intelligence, Machine learning, Deep learning, Automation, Robotics, Ethics, Societal impact, Future of …
Generative Artificial Intelligence - WIPO
This WIPO Patent Landscape Report provides observations on patenting activity and scientific publications in the field of GenAI and builds on the 2019 WIPO Technology Trends publication …
Re-thinking the Competitive Landscape of Artificial Intelligence
AI is defined as ‘a set of tools and technologies that has the ability to augment and enhance organizational performance’ [5, p3]. This achieved by creating “artificial” systems to solve …
REPORT | ARTIFICIAL INTELLIGENCE, CYBERSECURITY AND …
Artificial intelligence is significantly transforming many areas of our daily lives, from its use in health care and environmental sustainability to education, financial planning and governance. …
Artificial Intelligence: the global landscape of ethics guidelines
Our analysis aims at mapping the global landscape of existing principles and guidelines for ethical AI and thereby determining whether a global convergence is emerging regarding both the …
Number 5, October 2020 Inventing AI - United States Patent …
Artificial intelligence (AI) is increasingly important for invention, difusing broadly across technologies, inventor-patentees, organizations, and geography. In the 16 years from 2002 to …
Evolving landscape of artificial intelligence (AI) and …
Artificial intelligence (ai), Assessment, Bibliometric analysis, Education. Abstract: The rapid evolution of digital technologies and computer sciences is ushering society into a …
The Washington State Artificial Intelligence Landscape
This report focuses on the artificial intelligence (AI) economy in Washington state –however, there is notable focus on the Seattle metropolitan area. Why? • Seattle comprises 95.6% of …
REPORT | ARTIFICIAL INTELLIGENCE, CYBERSECURITY AND …
use and evaluating their own technology and data infrastructure to ensure the reliability, safety and securi-ty of AI applications. This brief reviews the current legislative and regulatory …
The Landscape of Artificial Intelligence in K-12 Education
What is artificial intelligence (AI)? AI refers to the ability of machines or computer programs to perform tasks that normally require human intelligence, such as learning, problem-solving, …
Supplementary Material - Inventing AI: Tracing the diffusion …
We employ a neural network (machine learning) classification model to identify patent documents in this “patent universe” that are relevant to AI. We then analyze this resulting AI patent …
Application of Artificial Intelligence Technology in Landscape ...
In summary, AI technology plays an important role in the landscape architecture industry, which can optimize workflow, improve eficiency and quality, thereby making significant contributions …
The Artificial Intelligence (AI) global regulatory landscape - EY
Based on EY teams analysis, we identified five key regulatory trends for policymakers and companies to consider as they work toward enhancing confidence in the use of AI.
Navigating the AI landscape - Moody's
We conducted primary research with a view to finding out more and exploring attitudes towards AI within a range of target audiences and regions, covering the following topics: Is AI a passing …
Artificial Intelligence in Government: The Federal and State …
own technology and data infrastructure to ensure the reliability, safety and security of AI applications. This brief reviews the current legislative and regulatory landscape at both federal …
GENERATIVE ARTIFICIAL INTELLIGENCE: THE …
The recent success of generative artificial intelligence (GenAI) tools capable of generating human-like content has shaken digital markets and started a new technological race. GenAI is powered …
The Patent Landscape of Artificial Intelligence
• What is Artificial Intelligence and how do sub-technologies such as Machine Learning or Deep Learning differ from it? • What are the countries in which Artificial Intelligence is being …
Artificial Intelligence Technology Landscape infographic
Artificial Intelligence is computer systems that exhibit human like intelligence. It is a group of science fields and technologies concerned with creating machines take intelligent actions based …
Generative AI Governance: Shaping a Collective Global Future
Apr 5, 2023 · The global landscape for artificial intelligence (AI) governance is complex and rapidly evolving, given the speed and breadth of technological advancements, as well as social, …
HOLONIQ. GLOBAL INTELLIGENCE Global AI Strategy …
released “Artificial Intelligence: Shaping a Future New Zealand.” Norway January 2020, Norway issued its National Strategy for Artificial Intelligence. Pakistan Presidential Initiative for Artificial …
ARTIFICIAL INTELLIGENCE RELATED INVENTIONS - Royal …
The Royal Society’s Disruptive Technology for Research project aims to understand the landscape of data-driven and artificial intelligence-based technologies across different fields of scientific …
Artificial Intelligence In The 21st Century [PDF]
Artificial Intelligence in the 21st Century: A Journey into the Uncharted Artificial intelligence, Machine learning, Deep learning, Automation, Robotics, Ethics, Societal impact, Future of work, …
Generative Artificial Intelligence - WIPO
This WIPO Patent Landscape Report provides observations on patenting activity and scientific publications in the field of GenAI and builds on the 2019 WIPO Technology Trends publication on …
Re-thinking the Competitive Landscape of Artificial …
AI is defined as ‘a set of tools and technologies that has the ability to augment and enhance organizational performance’ [5, p3]. This achieved by creating “artificial” systems to solve …
REPORT | ARTIFICIAL INTELLIGENCE, CYBERSECURITY …
Artificial intelligence is significantly transforming many areas of our daily lives, from its use in health care and environmental sustainability to education, financial planning and governance. Among …
Artificial Intelligence: the global landscape of ethics guidelines
Our analysis aims at mapping the global landscape of existing principles and guidelines for ethical AI and thereby determining whether a global convergence is emerging regarding both the principles …
Number 5, October 2020 Inventing AI - United States Patent …
Artificial intelligence (AI) is increasingly important for invention, difusing broadly across technologies, inventor-patentees, organizations, and geography. In the 16 years from 2002 to …
Evolving landscape of artificial intelligence (AI) and …
Artificial intelligence (ai), Assessment, Bibliometric analysis, Education. Abstract: The rapid evolution of digital technologies and computer sciences is ushering society into a technologically …
The Washington State Artificial Intelligence Landscape
This report focuses on the artificial intelligence (AI) economy in Washington state –however, there is notable focus on the Seattle metropolitan area. Why? • Seattle comprises 95.6% of Washington’s …
REPORT | ARTIFICIAL INTELLIGENCE, CYBERSECURITY …
use and evaluating their own technology and data infrastructure to ensure the reliability, safety and securi-ty of AI applications. This brief reviews the current legislative and regulatory landscape at …
The Landscape of Artificial Intelligence in K-12 Education
What is artificial intelligence (AI)? AI refers to the ability of machines or computer programs to perform tasks that normally require human intelligence, such as learning, problem-solving, …
Supplementary Material - Inventing AI: Tracing the diffusion of ...
We employ a neural network (machine learning) classification model to identify patent documents in this “patent universe” that are relevant to AI. We then analyze this resulting AI patent landscape …
Application of Artificial Intelligence Technology in …
In summary, AI technology plays an important role in the landscape architecture industry, which can optimize workflow, improve eficiency and quality, thereby making significant contributions to …
