Collaborative Research: FW-HTF-RM: Intelligent Facilitation for Teams of the Future via Longitudinal Sensing in Context

在未来的信息工作场所，团队合作将变得越来越重要，团队合作本身将被重新定义。随着日常工作越来越多地委托给个人数字助理等人工智能（AI）技术，团队将需要提高处理复杂问题的技能。随着零工经济的增长，以及新员工的加入带来了新的文化习俗，团队需要迅速适应不稳定的成员和不断变化的工作结构。随着劳动力变得更加多样化和全球化的增加，个人将需要能够在异质团队中有效地执行。未来的团队合作将需要整合技术进步来促进团队绩效，然而我们在很大程度上依赖于20世纪的工具和技术来促进团队合作。该项目将开发和验证一种智能（基于人工智能的）团队促进者，用于信息工作，利用传感和动态干预来促进更好的团队协调，提高绩效，并最终降低员工倦怠。智能团队促进者将作为信息工作以外的广泛领域的蓝图，包括医疗团队、控制室设置、危机管理和制造业，在这些领域，团队技能将需要与人工智能、机器人和新技术进行交互。促进者还可以用于培训代表性不足的群体，使其在劳动力中取得成功，这是国家的优先事项。本项目除了使用观察和自我报告研究团队的传统方法外，还利用传感器技术来跟踪信息工作场所中的团队行为。使用一套传感器对团队进行纵向精确跟踪，可以提供客观的测量，可以扩展，并且可以深入了解团队如何应对不断变化的环境，团队如何形成和整合新成员，以及他们如何发展团队合作的节奏。该项目广泛考察了团队多样性，考虑了人口统计、态度、昼夜节律和个人责任。该项目的第一个目标是开发关键团队状态和过程的模型（例如，团队凝聚力，团队协调，团队情绪/影响），基于在现实世界环境中对生理，行为和沟通的不引人注意的，持续的，纵向的感知，以及个体差异的测量，以了解导致团队效率的因素。该项目将使用风险缓解战略来保护数据的隐私和安全。这个项目的第二个目标是使用这些见解来开发一个智能的（基于人工智能的）团队促进者。使用智能团队促进者的团队的表现将在纵向原位研究中与匹配的控制进行实验比较。研究结果将有助于对21世纪团队如何管理复杂性、团队异质性如何导致团队效率的新理解，并将确定成功的团队适应性策略。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

In the information workplace of the future, teamwork will become increasingly critical and teamwork itself will be redefined. Teams will need to develop better skills in handling complex problems as routine work will be increasingly delegated to artificial intelligence (AI) technologies such as personal digital assistants. Teams will need to rapidly adapt to fluid membership and changing work structures with the growing gig economy, and as new workers enter the workforce bringing new cultural practices. Individuals will need to be able to perform effectively in heterogeneous teams as the workforce becomes more diverse and as globalization increases. The future of teamwork will require integration of technological advances to facilitate team performance, yet we are largely relying on tools and techniques from the 20th century for team facilitation. This project will develop and validate an intelligent (AI-based) team facilitator for information work utilizing sensing and dynamic intervention to promote better team coordination, higher performance, and ultimately lower worker burnout. The intelligent team facilitator will serve as a blueprint for a broad set of domains beyond information work, including medical care teams, control room settings, crisis management, and manufacturing, where team skills will be needed for interacting with AI, robots, and new technologies. The facilitator can also be used for training underrepresented groups to succeed in the workforce, a national priority. The present project utilizes sensor technologies for tracking team behavior in information workplaces in addition to traditional methods of studying teams using observations and self- reports. Longitudinal precision tracking of teams in situ with a suite of sensors can provide objective measures, can scale, and will enable a deep understanding of how teams respond to changing contexts, how teams form and integrate new members, and how they develop rhythms of teamwork. This project examines team diversity broadly, considering demographics, attitudes, circadian rhythms and personal responsibilities. The first aim of this project is to develop models of critical team states and processes (e.g., team cohesion, team coordination, team mood/affect), based on unobtrusive, continual, longitudinal sensing of physiology, behavior, and communication in a real-world context along with measures of individual differences to understand factors that lead to team effectiveness. This project will use risk mitigation strategies to safeguard privacy and security of data. The second aim of this project is to use those insights to develop an intelligent (AI-based) team facilitator. Performance of teams who use the intelligent team facilitator will be experimentally compared against matched controls in a longitudinal in situ study. The results will contribute to a new understanding on how 21st century teams can manage complexity, how team heterogeneity can lead to team effectiveness, and will identify successful strategies for team adaptability.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.