This book acts as a compilation of papers presented in the Human Engineering Symposium (HUMENS 2021). The symposium theme, “Human-centered Technology for A Better Tomorrow,” covers the following research topics: ergonomics, biomechanics, sports technology, medical device and instrumentation, artificial intelligence / machine learning, industrial design, rehabilitation, additive manufacturing, modelling and bio-simulation, and signal processing. Fifty-nine articles published in this book are divided into four parts, namely Part 1—Artificial Intelligence and Biosimulation, Part 2—Biomechanics, Safety and Sports, Part 3—Design and Instrumentation, and Part 4—Ergonomics.
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.
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.
A pragmatic framework for nonprofit digital transformation that embraces the human-centered nature of your organization The Smart Nonprofit turns the page on an era of frantic busyness and scarcity mindsets to one in which nonprofit organizations have the time to think and plan — and even dream. The Smart Nonprofit offers a roadmap for the once-in-a-generation opportunity to remake work and accelerate positive social change. It comes from understanding how to use smart tech strategically, ethically and well. Smart tech does rote tasks like filling out expense reports and identifying prospective donors. However, it is also beginning to do very human things like screening applicants for jobs and social services, while paying forward historic biases. Beth Kanter and Allison Fine elegantly outline the ways smart nonprofits must stay human-centered and root out embedded bias in order to success at the compassionate and creative work that only humans can and should do.
“Cukier and his co-authors have a more ambitious project than Kahneman and Harari. They don’t want to just point out how powerfully we are influenced by our perspectives and prejudices—our frames. They want to show us that these frames are tools, and that we can optimise their use.” —Forbes From pandemics to populism, AI to ISIS, wealth inequity to climate change, humanity faces unprecedented challenges that threaten our very existence. The essential tool that will enable humanity to find the best way foward is defined in Framers by internationally renowned authors Kenneth Cukier, Viktor Mayer-Schönberger, and Francis de Véricourt. To frame is to make a mental model that enables us to make sense of new situations. Frames guide the decisions we make and the results we attain. People have long focused on traits like memory and reasoning, leaving framing all but ignored. But with computers becoming better at some of those cognitive tasks, framing stands out as a critical function—and only humans can do it. This book is the first guide to mastering this human ability. Illustrating their case with compelling examples and the latest research, authors Cukier, Mayer-Schönberger, and de Véricourt examine: · Why advice to “think outside the box” is useless · How Spotify beat Apple by reframing music as an experience · How the #MeToo twitter hashtag reframed the perception of sexual assault · The disaster of framing Covid-19 as equivalent to seasonal flu, and how framing it akin to SARS delivered New Zealand from the pandemic Framers shows how framing is not just a way to improve how we make decisions in the era of algorithms—but why it will be a matter of survival for humanity in a time of societal upheaval and machine prosperity.
From straightforward internet access to elaborate makerspaces, libraries have taken center stage when it comes to providing free access to technology to those who visit their physical spaces. But how about people who don’t walk into a library? How do we ensure those members of the community are also being reached by technology programming? It’s time to launch an adventure! Berman, named an ALA Emerging Leader and Library Journal Mover & Shaker, provides readers with a comprehensive plan for creating and implementing successful technology-based outreach. She also teaches readers design thinking skills that can enable library staff to become creative problem solvers. Sharing the methods and experiences of her team at San José Public Library, Berman’s guide presents numerous real-world case studies, including videomaking in a skate park, e-readers for seniors, popup mobile makerspaces, and simple circuits in middle school, that will inspire readers to move technology beyond the walls of the library;offers dozens of design thinking exercises, such as rapid prototyping, empathy mapping, and logic models, as part of a start-to-finish model for developing a new program concept;discusses the origins of and reasons behind the digital divide, then shares outreach fundamentals and best practices that will help ensure success; andprovides information about ways to connect with the community, perform evaluation, offer STEM programming, and additional resources. This guide will empower libraries to design and prototype technology-based outreach ideas safely, quickly, and with confidence, leading to better service for all members of the community.
A guide to understanding the inner workings and outer limits of technology and why we should never assume that computers always get it right. In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally—hiring, driving, paying bills, even choosing romantic partners—that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology. With this book, she offers a guide to understanding the inner workings and outer limits of technology—and issues a warning that we should never assume that computers always get things right. Making a case against technochauvinism—the belief that technology is always the solution—Broussard argues that it's just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding “the cyborg future is not coming any time soon”; uses artificial intelligence to investigate why students can't pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone.
Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow—and show how a human-centered approach can enhance each one, by making the process more transparent, asking questions, and considering the social context of the data. They describe how tools from social science might be incorporated into data science practices, discuss different types of collaboration, and consider data storytelling through visualization. The book shows that data science practitioners can build rigorous and ethical algorithms and design projects that use cutting-edge computational tools and address social concerns.
