FW-HTF-P: Transforming Small and Medium-Sized Manufacturing Firms Through Participatory AI Adoption and Implementation

该项目旨在通过分析采用基于人工智能(AI)的技术如何影响制造业中小企业的劳动力和生产率，来改造美国的中小型制造业企业(SME)。基于人工智能的技术引发了对工人再培训和替换的一系列担忧，但也带来了围绕生产率和创造新工作的潜在好处，包括那些对体力要求较低、可能支持目前被排除在制造业工作之外的工人的工作。该项目专注于中小企业而不是大公司，这既是因为中小企业雇用了绝大多数美国制造业工人，也是因为中小企业可能会在这些公司可用来使这些技术为他们工作的资源和技能方面对采用基于人工智能的技术构成独特的挑战。该项目的目标是：(1)了解制造业中小企业及其工人目前在采用和实施新的人工智能技术、重组工作和任务以及学习新技能方面面临的挑战；(2)设计一个受控的制造环境，以支持工人与基于人工智能的技术协作的研究；(3)开发一个框架，供中小企业在采用这些技术时使用；以及(4)发展与行业合作伙伴和社区学院的联系，以确定如何降低工厂采用新人工智能技术的门槛，并制定强有力的劳动力培训计划。为了实现这些目标，项目团队将与印第安纳州南本德-埃尔克哈特地区的制造公司建立合作关系，包括中小企业和拥有多家中小企业的大公司。一个由经济、工程、人工智能、信息技术、分析和运营以及社会学领域的专家组成的团队将与这些当地中小企业合作，并进行现场观察和深入访谈，以了解公司目前的技术使用和需求，以及基于人工智能的技术满足这些需求的机会。这些调查结果将为一项调查提供信息，以收集更广泛的公司财务状况和生产能力、技术先进程度、管理和招聘做法、劳动力构成和流动率以及工作条件的数据。这些信息将被用来识别有前景的基于人工智能的技术进行进一步探索，然后设计一个制造单元，促进对与这些技术合作的工人的受控研究。此外，项目组将开发新的方法来培训制造业中小企业员工，使他们能够更直接地参与这些基于人工智能的技术的采用和使用。这项课程开发工作将与常春藤理工大学合作完成，常春藤理工大学在印第安纳州拥有40个社区大学地点，并正在开发一所先进制造、工程和应用科学学院，以满足该州制造业的需求。在这些活动的基础上，该项目将开发一个名为“参与式人工智能采用和实施”的框架，为工作场所、工人和基于人工智能的技术如何在制造业中小企业中有效地互动提供指导，重点是如何在采用从设计到部署的新技术时让工人参与公司的决策过程。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to transform small and medium-sized manufacturing enterprises (SMEs) in the U.S. by analyzing how the adoption of artificial intelligence (AI)-based technologies impacts manufacturing SMEs’ labor force and productivity. AI-based technologies pose a number of concerns around retraining and replacement of workers, but also potential benefits around productivity and the creation of new jobs, including ones that are less physically demanding and may support workers currently excluded from manufacturing jobs. The project focuses on SMEs rather than larger firms both because SMEs employ a large majority of U.S. manufacturing workers and because SMEs may pose unique challenges for the adoption of AI-based technologies in terms of the resources and skills these firms have available to make these technologies work for them. The goals of the project are to: (1) understand the challenges that manufacturing SMEs and their workers currently face in adopting and implementing new AI technologies, restructuring work and tasks and learning new skills; (2) design a controlled manufacturing environment to support studies of workers collaborating with AI-based technologies; (3) develop a framework that SMEs can use when adopting these technologies; and, (4) develop connections with industry partners and community colleges to identify ways to lower the barriers to the adoption of new AI technologies on the factory floor and to develop a robust workforce training program. To accomplish these goals, the project team will build a collaboration with manufacturing firms, both SMEs and large corporations holding multiple SMEs, in Indiana’s South Bend-Elkhart region. A team of experts in the areas of economics, engineering, AI, information technology, analysis and operations, and sociology will work with these local SMEs and conduct on-site observations and in-depth interviews to understand companies’ current technology use and needs, as well as opportunities for AI-based technologies to meet those needs. These findings will inform a survey to collect data on a wider range of companies’ financial situations and production capacity, technological sophistication, management and hiring practices, workforce composition and turnover, and work conditions. Together this information will be used to identify promising candidate AI-based technologies to explore further, then design a manufacturing cell that facilitates controlled studies of workers collaborating with these technologies. Further, the project team will develop novel approaches to training manufacturing SME employees to allow them to be more directly involved in the adoption and use of these AI-based technologies. This curriculum development work will be done in collaboration with Ivy Tech, which has 40 community college locations in Indiana and is developing a School of Advanced Manufacturing, Engineering and Applied Science in response to the needs of the state’s manufacturing industry. Based on these activities, the project will develop a framework called “Participatory AI Adoption and Implementation” with guidelines for how workplaces, workers, and AI-based technologies can productively interact in manufacturing SMEs, focusing on ways to involve workers in the firm’s decision process when adopting new technologies from design to deployment.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.