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代理人不断参与工程系统，并且，以类似的方式，工程系统越来越多地成为交互人类系统的组成部分。一个特别难以捉摸的问题需要理解和预测人类和工程系统之间的合作，在行为和技术领域的演变。该奖项支持实验和理论研究，通过整合动力系统理论，机器人技术和人机交互来阐明人类工程系统中的协作动力学。人类将在工程环境中与工程系统进行社会互动，而这反过来又将由工程基础设施实现。这项研究将有助于为下一代自主环境监测系统奠定基础，该系统利用人类智能和低成本分布式机器人快速准确地监测环境。 作为研究的补充，跨学科的正式和非正式教育活动将有利于贫困学生的培训，并深入到经济困难的当地社区。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的合作的演变。在一个新颖的众包基础设施中，由真实的人类和人工专家组成的在线小组将通过在纽约布鲁克林污染的运河中虚拟巡逻移动的水生机器人来合作进行水环境监测，以探索水盆地，收集和分类野生动物图像，并识别污染源。 类似于一个力学实验，其中一个施加一系列的机械力到固体和测量其机械变形，该项目将研究人类对人工专家的控制行动的反应，并调查他们交织的动态，在社会互动和任务表现方面。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对技术介导的社会互动和绩效的作用。一个基于信号处理、网络科学和信息理论的新的数据驱动数学框架将被制定出来，以揭示人类的个人属性和可塑性之间的相互作用，他们与工程系统的相互作用，以及如何更好地设计一个人类工程系统以获得集体专业知识。

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.