SKU/Artículo: AMZ-B08P15GZX7
When Computers Tell People What to Do: A Work Practice Simulation of the Überlingen Mid-Air Collision
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- What happens when computer programs tell people what to do in safety-critical situations? This book uses a computer simulation of people’s activities—how they typically interact with each other, automated tools, and their environment—to understand what happened during the mid-air collision over Überlingen, Germany in July 2002. With the advent of inexpensive supercomputers and advances in Artificial Intelligence programming, it seems that every month we learn about automated systems with new capabilities that heretofore only people could do—driving automobiles, controlling aircraft systems, delivering packages. As we give computer programs control of complicated vehicles and devices, we need new tools to analyze designs to anticipate and understand how the machines will behave in safety-critical situations—when action may be urgent and lives at stake. To secure the trust of consumers and certification by regulators, engineers need to adopt scientific modeling methods to verify that the behavior of instruments, devices, and programs fits how people perceive, reason, and act in challenging situations. This book describes a two-year project (2011–2013) at NASA Ames Research Center that demonstrated how a computer simulation of people’s practices, their detailed interactive behaviors, could be used to design and verify automated systems that operate in safety-critical situations. Technology often changes practices, so people’s behavior and technology must be analyzed, designed, and verified together. A work practice simulation provides a way to do that early in the design phase. The automated system of interest is the Traffic Collision Avoidance System (TCAS), a system onboard commercial aircraft that plans trajectories without supervision and tells pilots what to do. Our analysis focuses on the Überlingen mid-air collision because it exemplifies how an already complicated situation can become cognitively complex and out of people’s control if AI automation is not designed and tested properly. The modeling methods, analysis of events during the catastrophe, and what we learned are detailed in this book. The resulting tool, called the Brahms Generalized Überlingen Model (Brahms-GÜM), is general, directly applicable for modeling and analyzing an infinite variety of systems and circumstances in the air transportation domain. By simulating processes—people, technology, and the environment—as separate, interacting agents and objects, scenarios combining different system malfunctions and people’s behaviors can be tested to discover when catastrophic failures might result. Since the completion of the Brahms-GÜM project, world events have borne out our concerns that corporations and governments are using inadequate methods to design and certify advanced automation. Self-driving cars have been trusted without merit and operated without proper supervision by people. The US Navy committed billions of dollars to build and deploy “minimal manning” ships without understanding the total-system effects of advanced automation with a reduced crew lacking specialists onboard. And planes have crashed as corporate managers, engineers, and government regulators allowed automation to be hidden from pilots, with woefully insufficient analysis of how people and computers might interact in difficult, life-threatening situations. These are serious, systemic research and development (R&D) failures, caused in part by inadequate scientific modeling and analysis of the total work system design. Corporations and governments spending billions of dollars to develop ever more complicated automated systems should be using a tool like Brahms-GÜM to properly relate people, technology, and the environment in a comprehensive work system design. BOOK CONTENTS —360 pages, 50 figures, 40 tables; references; glossary. Print Replica is viewable on Kindle Fire and Reading Apps for Android & Macintosh devices. On Tablets use the Page function to go to desired page.
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