EAGER: Evidence-Based Model of Adoption of Robotics for Pandemics and Natural Disasters

EAGER：采用机器人技术应对流行病和自然灾害的循证模型

• 批准号: 2125988
• 负责人: Robin Murphy
• 金额: $ 23.83万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-15 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2125988&HistoricalAwards=false
• 关键词: EAGER; Evidence; Based; Model; Adoption

Robotics innovations (unmanned ground, aerial, and marine systems) have been sporadically used for disaster response by emergency management agencies since 2001. Disasters pose a dilemma: on one hand, there is often an emotional urge to try anything in the hopes of coping with overwhelming potential loss of life and livelihoods; on the other hand, the poorly considered introduction of a robot into a disaster can lead to worse outcomes than doing nothing. This EArly Concept Grant for Exploratory Research (EAGER) study will bring together leaders in robotics, law, emergency management, and public health with expertise in emergency management and policy to investigate robotics innovations and instances of ethical concerns during the COVID-19 pandemic. The result will be the first theory of responsible robotics innovation for disasters. This will transform how responders select robot technology during a disaster, ultimately saving lives, mitigating long-term environmental and health impacts, and accelerating economic recovery. The project will provide evidence for anticipatory governance, such as new regulations and policies, to accelerate the adoption of safe, effective robots during a disaster while reducing negative consequences from either deploying unsound technology or deferring deployment of technology. The project will impact how engineering, law, and policy is taught, train graduate and undergraduate students in multidisciplinary approaches to science and society, and increase the diversity of students in the research pipeline. The multidisciplinary team will conduct a rigorous analysis, featuring structured interviews with clinical healthcare providers, public health and public safety officials worldwide who deployed robots during the pandemic in order to understand the influences on adoption. The demand analysis will be complemented by prior work in quantitatively classifying the capabilities of the robot for a use case; together these orthogonal sets of user-centric and robot-centric influences will create a novel template for describing future innovation. The project will explore the legal systems and how they adapted to the exigencies of the pandemic, especially any correlations with national policies on robotics, and investigate emergent ethical concerns. The resulting quantitative model is expected to be both prescriptive for policy and predictive for future law and science research into robotics adoption. The model will revolutionize the methodology for constructing innovation theories. It will contribute to foundational responsible innovation research and comparative law, especially how groups interpret legal uses of robotics and how robotics impacts expectations of rights and responsibilities of agencies and developers.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.

自2001年以来，紧急管理机构偶尔使用了机器人创新（无人驾驶地面，空中和海洋系统）。灾难构成了困境：一方面，经常有一种情感冲动来尝试任何事情，以应对应对压倒性的潜在生活和生命和生活的损失；另一方面，被认为不当考虑的机器人将机器人引入灾难可能会导致更糟糕的结果，而不是什么都不做。这项早期的探索性研究概念赠款（急切）将与紧急管理和政策方面的专业知识一起，将机器人技术，应急管理和公共卫生领域的领导者汇集在一起​​，以调查与19日-19大流行期间的机器人学创新和道德问题的实例。结果将是负责任的机器人学创新的第一个理论。这将改变响应者在灾难中选择机器人技术的方式，最终挽救生命，减轻长期环境和健康影响并加速经济复苏。 该项目将为预期治理（例如新法规和政策）提供证据，以加快在灾难期间采用安全，有效的机器人，同时减少部署不符合技术或推迟技术部署的负面后果。该项目将影响工程，法律和政策的教学，培训毕业生和本科生在多学科的科学和社会方法中，并增加了研究管道中学生的多样性。多学科团队将进行严格的分析，以与临床医疗保健提供者，公共卫生和公共安全官员进行结构化访谈，他们在大流行期间部署了机器人，以了解对收养的影响。需求分析将通过对用例机器人的能力进行定量分类的先前工作来补充；这些正交集中的以用户为中心和以机器人为中心的影响将共同创建一个新的模板来描述未来的创新。该项目将探讨法律制度以及它们如何适应大流行的紧急情况，尤其是与机器人技术政策的任何相关性，并调查新兴的道德问题。预计所得的定量模型既具有政策的规定性，又是针对采用机器人技术的未来法律和科学研究的预测。该模型将彻底改变构建创新理论的方法。它将有助于基础负责的创新研究和比较法，尤其是小组如何解释机器人技术的法律用途，以及机器人技术如何影响机构和开发人员对权利和责任的期望。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的智力和更广泛影响的评估来通过评估来获得支持的人。

项目成果

Analysis of the Use of Robots for the Second Year of the COVID-19 Pandemic

COVID-19 大流行第二年的机器人使用情况分析

• DOI: 10.1109/ssrr56537.2022.10018671
• 发表时间: 2022
• 期刊: and Rescue Robotics (SSRR
• 作者: Murphy, Robin;Kathasagaram, Amrita;Millican, Truitt;Clendenin, Angela;deWitte, Paula;Moats, Jason
• 通讯作者: Moats, Jason

AI reflections in 2021

2021 年人工智能反思

• DOI: 10.1038/s42256-021-00435-7
• 发表时间: 2022
• 期刊: Nature Machine Intelligence
• 影响因子: 23.8
• 作者: Buckner, Cameron;Miikkulainen, Risto;Forrest, Stephanie;Milano, Silvia;Zou, James;Prunk, Carina;Irrgang, Christopher;Cohen, I. Glenn;Su, Hao;Murphy, Robin R.
• 通讯作者: Murphy, Robin R.

Adoption of Robots for Disasters: Lessons from the Response to COVID-19

• DOI: 10.1561/2300000062
• 发表时间: 2021
• 期刊: Found. Trends Robotics
• 作者: R. Murphy;Vignesh Babu Manjunath Gandudi;Justin Adams;A. Clendenin;Jason B. Moats

Robotics Responds to the COVID-19 Outbreak [From the Guest Editors]

机器人技术应对 COVID-19 爆发 [来自客座编辑]

• DOI: 10.1109/mra.2020.3048866
• 发表时间: 2021
• 期刊: IEEE Robotics & Automation Magazine
• 影响因子: 5.7
• 作者: Marques, Lino;Murphy, Robin;Althoefer, Kaspar;Tadokoro, Satoshi;Laschi, Cecilia
• 通讯作者: Laschi, Cecilia