EAGER: Dynamics of collaboration between humans and engineered systems: system design for collective expertise

1547864（Porfiri）人类作为认知和社会主体不断参与到工程系统中，同样，工程系统也越来越成为人类互动系统的一部分。一个特别难以捉摸的问题需要理解和预测跨越行为和技术领域的人类和工程系统之间协作的演变。该奖项支持实验和理论研究，通过动力系统理论、机器人和人机交互的集成，阐明人类工程系统中协作的动力学。人类将在工程环境中与工程系统进行社会互动，而这将反过来由工程基础设施实现。这项研究将为下一代自主环境监测系统奠定基础，该系统将利用人类智能和低成本的分布式机器人快速准确地监测环境。与研究相辅相成的是跨学科的正规和非正规教育活动，这些活动将有利于培训贫困学生并向经济上处于不利地位的当地社区伸出援助之手。该研究计划旨在建立一个变革性的实验和理论框架，以理解、预测并最终控制人类与工程系统之间协作的演变。在一种新颖的众包基础设施中，由真人和人工专家组成的在线小组将协同执行水生环境监测，通过虚拟巡逻移动水生机器人在纽约布鲁克林被污染的运河中探索流域，收集和分类野生动物图像，并确定污染源。类似于将一系列机械力应用于固体并测量其机械变形的力学实验，该项目将研究人类对人工专家控制动作的反应，并从社会互动和任务表现的角度研究它们相互交织的动力学。一系列假设驱动的研究将探讨人类认知能力、性格因素和行为可塑性在技术介导的社会互动和表现中的作用。一个基于信号处理、网络科学和信息论的新的数据驱动数学框架将被制定，以揭示个人属性和人类可塑性之间的相互作用，它们与工程系统的相互作用，以及如何更好地为集体专业知识设计一个人类工程系统。

1547864(Porfiri)Humans are being continuously involved as cognitive and social agents in engineered systems, and, in a similar vein, engineered systems are becoming increasingly integral to systems of interacting humans. A particularly elusive issue entails understanding and predicting the evolution of the collaboration between humans and engineered systems, across behavioral and technological domains. This award supports experimental and theoretical research to elucidate the dynamics of collaboration in human-engineered systems, through the integration of dynamical systems theory, robotics, and human-computer interactions. Humans will socially interact with engineered systems in an engineering context, which will be, in turn, enabled by an engineering infrastructure. This research will contribute to lay the foundation for the next generation of autonomous environmental monitoring systems, which capitalize on human intelligence and low-cost distributed robots for rapidly and accurately monitoring the environment. Complementing the research are interdisciplinary formal and informal education activities that will benefit the training of underprivileged students and reach out to economically-disadvantaged local communities.This research program seeks to establish a transformative experimental and theoretical framework for understanding, predicting, and, ultimately, controlling the evolution of the collaboration between humans and engineered systems. In a novel crowdsourcing infrastructure, online groups comprised of real humans and artificial experts will collaboratively perform aquatic environmental monitoring, by virtually patrolling mobile aquatic robots in a polluted canal in Brooklyn, NY, to explore the water basin, collect and classify wildlife images, and identify sources of pollution. Similar to a mechanics experiment in which one applies a sequence of mechanical forces to a solid and measures its mechanical deformation, this project will study the response of humans to the controlled actions of artificial experts and investigate their intertwined dynamics, in terms of social interactions and task performance. A series of hypothesis-driven studies will explore the roles of human cognitive abilities, dispositional factors, and behavioral plasticity on technology-mediated social interactions and performance. A new data-driven mathematical framework based on signal processing, network science, and information theory will be formulated to uncover the interplay between personal attributes and plasticity of humans, their interactions with engineered systems, and how to better design a human-engineered system for collective expertise.