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Many data-intensive applications that use machine learning or artificial intelligence techniques depend on humans providing the initial dataset, enabling algorithms to process the rest or for other humans to evaluate the performance of such algorithms. Not only can labeled data for training and evaluation be collected faster, cheaper, and easier than ever before, but we now see the emergence of hybrid human-machine software that combines computations performed by humans and machines in conjunction. There are, however, real-world practical issues with the adoption of human computation and crowdsourcing. Building systems and data processing pipelines that require crowd computing remains difficult. In this book, we present practical considerations for designing and implementing tasks that require the use of humans and machines in combination with the goal of producing high-quality labels.
A concise introduction to crowdsourcing that goes beyond social media buzzwords to explain what crowdsourcing really is and how it works. Ever since the term “crowdsourcing” was coined in 2006 by Wired writer Jeff Howe, group activities ranging from the creation of the Oxford English Dictionary to the choosing of new colors for M&Ms have been labeled with this most buzz-generating of media buzzwords. In this accessible but authoritative account, grounded in the empirical literature, Daren Brabham explains what crowdsourcing is, what it is not, and how it works. Crowdsourcing, Brabham tells us, is an online, distributed problem solving and production model that leverages the collective intelligence of online communities for specific purposes set forth by a crowdsourcing organization—corporate, government, or volunteer. Uniquely, it combines a bottom-up, open, creative process with top-down organizational goals. Crowdsourcing is not open source production, which lacks the top-down component; it is not a market research survey that offers participants a short list of choices; and it is qualitatively different from predigital open innovation and collaborative production processes, which lacked the speed, reach, rich capability, and lowered barriers to entry enabled by the Internet. Brabham describes the intellectual roots of the idea of crowdsourcing in such concepts as collective intelligence, the wisdom of crowds, and distributed computing. He surveys the major issues in crowdsourcing, including crowd motivation, the misconception of the amateur participant, crowdfunding, and the danger of “crowdsploitation” of volunteer labor, citing real-world examples from Threadless, InnoCentive, and other organizations. And he considers the future of crowdsourcing in both theory and practice, describing its possible roles in journalism, governance, national security, and science and health.
Open innovation and crowd sourcing are the hottest topics in strategy and management today. The concept of capturing ideas in a hub of collaboration, together with the outsourcing of tasks to a large group of people or community is a revolution that is rapidly changing our culture. A Guide to Open Innovation and Crowdsourcing explains how to use the power of the internet to build and innovate in order to introduce a consumer democracy that has never existed before. If a business fails to embrace it, it is at risk of being left behind. Written by an international team of eminent thinkers, writers and practitioners in the field, A Guide to Open Innovation and Crowdsourcing covers the definition of open innovation, how to manage virtual teams and co-create with customers, how to overcome legal and IP issues and common mistakes and pitfalls to avoid. With corporate case studies and best practice advice, A Guide to Open Innovation and Crowd Sourcing is a vital read for anyone who wants to find innovative products and services from outside their organizations, make them work and overcome the practical difficulties that lie in the way.
The phenomenon of volunteered geographic information is part of a profound transformation in how geographic data, information, and knowledge are produced and circulated. By situating volunteered geographic information (VGI) in the context of big-data deluge and the data-intensive inquiry, the 20 chapters in this book explore both the theories and applications of crowdsourcing for geographic knowledge production with three sections focusing on 1). VGI, Public Participation, and Citizen Science; 2). Geographic Knowledge Production and Place Inference; and 3). Emerging Applications and New Challenges. This book argues that future progress in VGI research depends in large part on building strong linkages with diverse geographic scholarship. Contributors of this volume situate VGI research in geography’s core concerns with space and place, and offer several ways of addressing persistent challenges of quality assurance in VGI. This book positions VGI as part of a shift toward hybrid epistemologies, and potentially a fourth paradigm of data-intensive inquiry across the sciences. It also considers the implications of VGI and the exaflood for further time-space compression and new forms, degrees of digital inequality, the renewed importance of geography, and the role of crowdsourcing for geographic knowledge production.
Tap into the global talent pool. Crowdsourcing leverages such social networking tools as Facebook and Twitter to tap into the power of many people to distribute one's work load or gain input. Aliza Sherman, crowdsourcing innovator, has helped her clients harness the incredible power of "crowd-think" and "crowd- do" to achieve goals as diverse as designing new products to test-marketing services to fundraising. In this guide, she explains the theory and practice of crowdsourcing and actually shows readers how to use it. ? A practical, prescriptive guide for those who want to put the ideas in such books as The Wisdom of Crowds and Here Comes Everybody into action. ? Step-by-step instructions. ? Insightful anecdotes from the world of crowdsourcing.
With the growth of information technology, many new communication channels and platforms have emerged. This growth has advanced the work of crowdsourcing, allowing individuals and companies in various industries to coordinate efforts on different levels and in different areas. Providing new and unique sources of knowledge outside organizations enables innovation and shapes competitive advantage. Crowdsourcing: Concepts, Methodologies, Tools, and Applications is a collection of innovative research on the methods and applications of crowdsourcing in business operations and management, science, healthcare, education, and politics. Highlighting a range of topics such as crowd computing, macrotasking, and observational crowdsourcing, this multi-volume book is ideally designed for business executives, professionals, policymakers, academicians, and researchers interested in all aspects of crowdsourcing.
Crowdsourcing, or asking the general public to help contribute to shared goals, is increasingly popular in memory institutions as a tool for digitising or computing vast amounts of data. This book brings together for the first time the collected wisdom of international leaders in the theory and practice of crowdsourcing in cultural heritage. It features eight accessible case studies of groundbreaking projects from leading cultural heritage and academic institutions, and four thought-provoking essays that reflect on the wider implications of this engagement for participants and on the institutions themselves. This book will be essential reading for information and cultural management professionals, students and researchers in universities, corporate, public or academic libraries, museums and archives.
This book offers an in-depth exploration of crowdfunding and crowdsourcing in journalism today, and examines their impacts on the broader media landscape. Crowdfunding and Crowdsourcing in Journalism looks at how these practices disrupt traditional journalism models, including shifting journalistic norms, professional identity, and the ethical issues at play when journalists turn to social media and the Internet to solicit widespread support. While there is often a lot of hype and hope invested in these practices, this book takes a critical look at the labour involved in crowdsourcing journalism practices, and the evolving relationship between audiences and journalists, including issues of civility in online spaces. The author draws on in-depth interviews with journalists in Canada and the United States, as well as examples from the United Kingdom, Germany, Sweden, and Australia, to provide a comprehensive study of increasingly important journalist practices. The book is a valuable resource for academics, researchers, and journalists who are interested in political economy, journalism studies, and labour studies.
“The amount of knowledge and talent dispersed among the human race has always outstripped our capacity to harness it. Crowdsourcing ­corrects that—but in doing so, it also unleashes the forces of creative destruction.” —From Crowdsourcing First identified by journalist Jeff Howe in a June 2006 Wired article, “crowdsourcing” describes the process by which the power of the many can be leveraged to accomplish feats that were once the province of the specialized few. Howe reveals that the crowd is more than wise—it’s talented, creative, and stunningly productive. Crowdsourcing activates the transformative power of today’s technology, liberating the latent potential within us all. It’s a perfect meritocracy, where age, gender, race, education, and job history no longer matter; the quality of work is all that counts; and every field is open to people of every imaginable background. If you can perform the service, design the product, or solve the problem, you’ve got the job. But crowdsourcing has also triggered a dramatic shift in the way work is organized, talent is employed, research is conducted, and products are made and marketed. As the crowd comes to supplant traditional forms of labor, pain and disruption are inevitable. Jeff Howe delves into both the positive and negative consequences of this intriguing phenomenon. Through extensive reporting from the front lines of this revolution, he employs a brilliant array of stories to look at the economic, cultural, business, and political implications of crowdsourcing. How were a bunch of part-time dabblers in finance able to help an investment company consistently beat the market? Why does Procter & Gamble repeatedly call on enthusiastic amateurs to solve scientific and technical challenges? How can companies as diverse as iStockphoto and Threadless employ just a handful of people, yet generate millions of dollars in revenue every year? The answers lie within these pages. The blueprint for crowdsourcing originated from a handful of computer programmers who showed that a community of like-minded peers could create better products than a corporate behemoth like Microsoft. Jeff Howe tracks the amazing migration of this new model of production, showing the potential of the Internet to create human networks that can divvy up and make quick work of otherwise overwhelming tasks. One of the most intriguing ideas of Crowdsourcing is that the knowledge to solve intractable problems—a cure for cancer, for instance—may already exist within the warp and weave of this infinite and, as yet, largely untapped resource. But first, Howe proposes, we need to banish preconceived notions of how such problems are solved. The very concept of crowdsourcing stands at odds with centuries of practice. Yet, for the digital natives soon to enter the workforce, the technologies and principles behind crowdsourcing are perfectly intuitive. This generation collaborates, shares, remixes, and creates with a fluency and ease the rest of us can hardly understand. Crowdsourcing, just now starting to emerge, will in a short time simply be the way things are done.
Many data-intensive applications that use machine learning or artificial intelligence techniques depend on humans providing the initial dataset, enabling algorithms to process the rest or for other humans to evaluate the performance of such algorithms. Not only can labeled data for training and evaluation be collected faster, cheaper, and easier than ever before, but we now see the emergence of hybrid human-machine software that combines computations performed by humans and machines in conjunction. There are, however, real-world practical issues with the adoption of human computation and crowdsourcing. Building systems and data processing pipelines that require crowd computing remains difficult. In this book, we present practical considerations for designing and implementing tasks that require the use of humans and machines in combination with the goal of producing high-quality labels.