CAREER: The Future of Work in Health Analytics and Automation: Investigating the Communication that Builds Human-Technology Partnerships

物联网、机器人和人工智能等技术的进步正在通过数据密集型自动化改变工作，这可能会在不创造新工作或技能的情况下消除工作，并减少现有工作。这个项目将研究工作是如何自动化的，以鼓励有利于工作和工人的形式。该项目将扩展关于日常对话的知识，这些对话塑造了自动化的实现，以及领导者如何选择如何首先进行这些对话。该项目将重点关注健康和医疗保健工作，其背景可能会受到数据化和自动化的影响，并可能为拥有合适技能的个人提供与stem相关的职业。在医疗保健领域，自动化可以帮助提供者预防医疗差错，降低护理成本，增加或创造新的工作形式，但这些系统的成功取决于它们的设计和实现方式。通过关注自动化中涉及的实际沟通，该项目将为卫生和分析组织的领导者提供理论见解和实用建议，涉及(a)如何使数据密集型自动化中涉及的沟通有效与否，以及(b)如何构建和促进这种沟通。这项研究将用于制作短片和一个学习模块，供学生做出关键的职业决定。这些影片和模块将被设计用于接触STEM中代表性不足的群体，并提供有关受自动化和STEM相关沟通能力影响的STEM职业的信息。该项目将帮助社区学院和大学的学生了解并为自动化带来的机遇和挑战做好准备。最近的研究表明，自动化不仅取决于新技术的特点或提高工作效率的压力，还取决于工人和管理者对市场力量、专业标准、监管、行业知识以及人力和技术工作流程等因素的复杂、沟通协商的混合想法。自动化涉及技术和工作组织的相互交织的变化。这些变化在关于工作是如何完成和应该如何完成的日常交流中展现出来。结合访谈和观察方法，该项目将调查两个理论和实践上重要的背景：(1)开发和实施自动化指标仪表板和临床决策支持系统等技术的医疗保健组织；(2)量化自我社区，其中个人分析从业者正在通过自动化创建新的人类技术合作伙伴关系，新的工作和娱乐形式。该项目的见解将推动自动化、数据密集型工作、通信设计以及组织和技术变革方面的研究。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。

Advances in technologies such as the internet of things, robotics, and artificial intelligence are transforming work through data-intensive automation, which may eliminate jobs without creating new ones or deskill and diminish existing work. This project will investigate how work is automated to encourage forms that benefit work and workers. The project will expand knowledge about the everyday conversations that shape the implementation of automation, and how leaders make choices about how to have those conversations in the first place. The project will focus on health and healthcare work, with is a context likely to be affected by datafication and automation and likely to provide STEM-related careers for individuals who have the right skills. In healthcare, automation may help providers prevent medical errors, lower the costs of caregiving, and augment or create new forms of work, but the success of such systems depends on how they are designed and implemented. By focusing on the actual communication involved in automation, the project will generate theoretical insights and practical recommendations for leaders in health and analytics organizations, regarding (a) what makes the communication involved in data-intensive automation effective or not, and (b) how to structure and facilitate that communication. The research will be used to create short films and a learning module for students making key career decisions. The films and module will be designed to reach groups underrepresented in STEM and to provide information about STEM careers affected by automation and STEM-related, communication competencies. The project will help students at community colleges and universities understand and prepare for the opportunities and challenges of automation.Recent research has demonstrated that automation is determined not merely by the features of new technology or pressures to make work more efficient, but by a complex, communicatively-negotiated mix of workers' and managers' ideas about factors such as market forces, professional standards, regulation, industry knowledge, and human and technology workflows. Automation involves intertwined changes in the technologies and organization of work. These changes unfold in and through everyday communication about how work is and ought to be accomplished. Using a combination of interview and observational methods, the project will investigate two theoretically and practically important contexts: (1) Healthcare organizations that develop and implement technologies such as automated metrics dashboards and clinical decisions support systems, and (2) Quantified Self communities where practitioners of personal analytics are creating new human-technology partnerships, new forms of work and play, through automation. Insights from this project will advance research on automation, data-intensive work, communication design, and organizational and technological change.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.