RAPID: Accelerating the Future of Work? Understanding Future Shifts in Technology Adoption in the Seafood Industry in Response to the COVID19 Pandemic

这项快速反应研究（RAPID）资助将收集短暂的数据，以调查海鲜行业加速采用新技术，以应对COVID-19大流行引起的工人和食品安全问题。随着供应链继续面临COVID-19大流行造成的中断，美国提供安全、快速和国内采购食品（包括海鲜）的能力变得至关重要。海鲜加工仍然主要依赖于人类在以肮脏，寒冷和危险条件而闻名的工厂中彼此靠近工作。研究团队在这段前所未有的经济混乱时期收集的短暂数据将为海鲜加工厂的未来工作提供新的知识，包括采用人类协作自主系统的需求和可行性，以便在生产的各个阶段更安全，更有效地加工和包装食品。这一新知识的结果将用于为海产品加工以及农业和医疗保健领域的其他系统提供信息，这些系统可能正在经历快速的技术变革以应对这一流行病。通过这项研究收集的短暂数据也可以为FW-HTF的下一代系统提供一套新的设计要求。为收集数据而开展的研究活动还将有助于培养新一代工程师和社会科学家，通过研究生研究人员的参与，解决机器人技术、人机协作和劳动经济学融合方面的跨学科挑战，研究生研究人员将学习将不同领域的元素纳入他们的思维。包括来自东北大学国家认可的合作教育项目的学生在内的多代团队将通过专门面向本科生的创新实践研究经验来加强STEM教育的渠道。2018年，美国进口了220亿美元的海鲜，由于无法满足国内消费者的需求，这一数字超过了历史上的任何时候。该项目将提升美国在全球竞争激烈、国内服务不足的行业中的领导地位，同时促进对与技术采用快速加速相关的关键科学、工程和社会挑战的理解。由于迫切需要收集数据，以告知公司如何应对COVID-19大流行，本研究将采用一个被破坏的社会技术系统（STS）框架来研究企业如何重新评估其系统中的人和技术组成部分、它们之间的关系以及用于塑造和重塑这些系统的价值观和设计原则。本研究的贡献源于以下相互关联的目标：（1）收集关于COVID-19大流行如何改变海鲜加工业中人类互动动态的短暂数据，（2）开发新知识，以提高我们对STS变化程度的理解，因为应对COVID的技术采用加快了-19大流行在海产品行业和其他类似的系统，包括农业和医疗保健。(3)评估综合机器人同事的替代用途的可行性，以解决当前的流行病在短期内以及未来的长期工作。这些短暂的数据将通过对海产品行业大约100家公司的调查沿着5-7次后续访谈和三个案例研究来重新评估整个系统。具体而言，该项目将衡量企业在疫情爆发前如何评估系统中的人力和技术要素，以及他们的观点如何随着相关的经济破坏而发生变化。这些新数据将有助于开发技术，在未来18-24个月内促进海鲜加工厂的社交距离，同时确保这些解决方案与设计保持一致，以推动海鲜行业在当前疫情之后的未来工作。在企业采用任何新技术之前收集这些数据，将有助于研究企业修改STS框架以应对这种破坏的过程。这样做将使这项研究所创造的新知识能够为其他行业的系统提供信息，这些系统也将通过加速采用新技术来应对COVID-19大流行而重塑。该奖项反映了NSF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而被认为值得支持。

This Rapid Response Research (RAPID) grant will collect ephemeral data to investigate the accelerated adoption of new technologies in the seafood industry in response to both worker and food safety concerns arising from the COVID-19 pandemic. As supply chains continue to face disruption due to the COVID-19 pandemic, the ability of the U.S. to provide safe, fast, and domestically sourced food—including seafood—has become of paramount importance. Seafood processing still relies primarily on humans working in close proximity to one another in plants that are known for dirty, cold, and dangerous conditions. The ephemeral data collected by the research team during this period of unprecedented economic disruption will be provide new knowledge regarding the future of work in seafood processing plants, including the demand for, and feasibility of, adopting human-collaborative autonomous systems to process and package food more safely and efficiently at all stages of production. The result of this new knowledge will be used to inform both seafood processing as well as other systems in agriculture and healthcare that are potentially undergoing rapid technological change in response to the pandemic. The ephemeral data collected through this research can also inform a new set of design requirements for next generation systems at the FW-HTF. The research activities undertaken to collect the data will also help train a new generation of engineers and social scientists to address interdisciplinary challenges at the convergence of robotics, human-robot collaboration, and labor economics through the participation of graduate student researchers who will learn to incorporate elements of different domains into their thinking. Multi-generational teams that include students from Northeastern University’s nationally recognized cooperative education program will enhance the pipeline for STEM education through innovative hands-on research experience specifically geared towards undergraduates. The U.S. imported $22 billion of seafood in 2018—more than at any point in history due to an inability to meet domestic consumer demand. This project will advance US leadership in a globally competitive and domestically underserved industry, while simultaneously advancing understanding of key scientific, engineering, and societal challenges associated with the rapid acceleration of technology adoption.Motivated by the urgency to collect data that can inform how firms are responding to the COVID-19 pandemic, this project will adopt a disrupted socio-technical systems (STS) framework to study how firms are re-evaluating the human and technology components of their systems, their relationships, and the values and design principles that are used to shape and reshape those system. The contributions of this research stem from the following interconnected goals: (1) Collect ephemeral data on how the COVID-19 pandemic has changed the human interaction dynamics in the seafood processing industry, (2) Develop new knowledge to advance our understanding of the degree to which STS will change as technology adoption is accelerated in response to the COVID-19 pandemic in both the seafood industry and other similarly situated systems, including agriculture and healthcare. (3) Assess the feasibility of alternative uses of integrated robot co-workers to address both the current pandemic in the near-term as well as the future-of-work in the longer-term. This ephemeral data will capture the reassessment of this overall system through a survey of roughly 100 firms in the seafood industry along with 5-7 follow-up interviews and three case studies. Specifically, this project will measure how firms valued the human and technology elements of the system before the pandemic, and how their views have changed with the associated economic disruption. This new data will help develop technologies to facilitate social distancing in seafood processing plants over the next 18-24 months while also ensuring that these solutions are aligned with designs to advance the future of work in the seafood industry beyond the current pandemic. Collection of this data before firms adopt any new technology will enable the study of processes by which firms revise their STS frameworks in response to such disruptions. Doing so will allow the new knowledge created by this research to inform extrapolations to systems in other industries that will also be reshaped by accelerated adoption of new technologies in response to the COVID-19 pandemic.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.