FW-HTF-P: A Socio-technical Approach to Help the HR Function of the Future: Identifying and Preventing Discriminatory Recruitment Practices in the Technology Industry

FW-HTF-P：帮助未来人力资源职能的社会技术方法：识别和防止技术行业中的歧视性招聘做法

• 批准号: 2026652
• 负责人: Tracy Hammond
• 金额: $ 15万
• 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: 2020
• 资助国家: 美国
• 起止时间: 2020-08-15 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2026652&HistoricalAwards=false
• 关键词: FW; HTF; Socio; technical; Approach

Despite greater awareness of the value of broadening participation in STEM fields and movements to do so, discrimination in hiring remains a problem. The high technology sector is particularly notable for the very low numbers of women, African American, and Hispanic American computer scientists and engineers. A key reason for the low participation is that implicit biases at different stages of recruitment perpetuate the inequitable status quo. To begin to solve this problem, discrimination in recruiting must be understood in detail. This work aims to work toward improving human resources (HR) practices by improving training that uses state-of-the-art technologies to help people avoid unconsciously falling into discriminatory behavior. A potential long-term societal benefit of this work would be more equitable hiring processes. Such an improvement could increase hiring of diverse teams, thus increasing creativity and innovation in the workplace. In addition, more diverse teams can help to reduce stereotype threat, since sterotypes break down as more people from underrepresented groups are included. Toward these goals, the research team plans to conduct an interdisciplinary workshop with industry representatives and experts from HR management, the social sciences, and computer science to identify sources of bias and propose solutions to address them. This workshop is expected to lay the foundation and the research agenda necessary to submit a full Future of Work at the Human-Technology Frontier proposal. By leveraging the expertise of HR management, psychology, and sociology professionals, in partnership with computer scientists and engineers, this convergent research team plans to gain a deep understanding of where and what kinds of bias occur in the recruitment process for high technology workers. Participants will explore potential interventions to identify or prevent bias through the use of future technologies such as virtual reality, augmented reality, and artificial intelligence-powered tools. The research team will attempt to answer the following questions through this project: What are the standard practices of the technology industry's recruitment process? How much do practices vary from company to company? In what phases of the recruitment process does bias occur, and what types of biases occur? What types of evidence are produced by biased recruiting practices? What technologies are useful for identifying and preventing bias? This project has been funded by the Future of Work at the Human-Technology Frontier cross-directorate program to facilitate convergent research to promote deeper basic understanding of the interdependent human-technology partnership to advance societal needs by advancing design of intelligent work technologies that operate in harmony with human workers.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.

尽管人们越来越认识到扩大STEM领域参与的价值，并为此开展运动，但招聘中的歧视仍然是一个问题。在高科技部门，女性、非裔美国人和西班牙裔美国人计算机科学家和工程师的人数非常少。参与率低的一个关键原因是，招聘的不同阶段存在隐性偏见，使不公平的现状长期存在。要开始解决这一问题，必须详细了解招聘中的歧视。这项工作旨在通过改进培训来改善人力资源（HR）实践，使用最先进的技术来帮助人们避免无意识地陷入歧视行为。 这项工作的一个潜在的长期社会效益将是更公平的招聘过程。 这种改进可以增加对不同团队的雇用，从而提高工作场所的创造力和创新。此外，更多样化的团队可以帮助减少刻板印象的威胁，因为当更多来自代表性不足的群体的人被包括在内时，刻板印象就会被打破。 为了实现这些目标，研究团队计划与来自人力资源管理，社会科学和计算机科学的行业代表和专家进行跨学科研讨会，以确定偏见的来源并提出解决方案。本次研讨会预计将奠定基础和必要的研究议程，以提交一个完整的未来工作在人类技术前沿的建议。通过利用人力资源管理，心理学和社会学专业人士的专业知识，与计算机科学家和工程师合作，这个融合的研究团队计划深入了解高科技员工招聘过程中发生的偏见。参与者将探索潜在的干预措施，以通过使用未来的技术，如虚拟现实，增强现实和人工智能驱动的工具来识别或防止偏见。研究团队将试图通过这个项目回答以下问题：科技行业招聘过程的标准做法是什么？不同公司的做法有多大差异？在招聘过程的哪些阶段会出现偏见，以及会出现哪些类型的偏见？有偏见的招聘做法会产生什么样的证据？哪些技术有助于识别和防止偏见？ 该项目由人类技术前沿跨部门计划的未来工作资助，以促进融合研究，促进对相互依存的人类社会的更深入的基本理解。技术合作伙伴关系，通过推进与人类工人和谐运作的智能工作技术的设计来推动社会需求。该奖项反映了NSF的法定使命，并通过使用基金会的学术价值和更广泛的影响审查标准。