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

尽管越来越多的人意识到扩大STEM领域参与的价值，并为此采取了行动，但招聘中的歧视仍然是一个问题。在高科技行业，女性、非裔美国人和西班牙裔美国人的计算机科学家和工程师数量非常少，这一点尤为引人注目。参与率低的一个关键原因是，在招聘的不同阶段，隐性偏见使不公平的现状长期存在。要开始解决这个问题，必须详细了解招聘中的歧视。这项工作旨在通过改进培训，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，从而改善人力资源（HR）实践。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。这样的改进可以增加多元化团队的招聘，从而提高工作场所的创造力和创新能力。此外，更多样化的团队可以帮助减少刻板印象威胁，因为当更多来自代表性不足的群体的人被包括进来时，刻板印象就会被打破。为了实现这些目标，研究小组计划与行业代表和来自人力资源管理、社会科学和计算机科学的专家举行跨学科研讨会，以确定偏见的来源并提出解决方案。预计这次研讨会将奠定基础和必要的研究议程，以提交一份完整的人类技术前沿工作的未来提案。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，这个融合研究团队计划深入了解高科技员工招聘过程中出现的偏见。参与者将探索通过使用虚拟现实、增强现实和人工智能驱动的工具等未来技术来识别或防止偏见的潜在干预措施。研究团队将试图通过这个项目回答以下问题：技术行业的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？会出现哪些类型的偏见？有偏见的招聘实践产生了哪些类型的证据？哪些技术对识别和预防偏见有用？该项目由人类-技术前沿跨部门计划的未来工作资助，旨在促进融合研究，促进对相互依赖的人类-技术伙伴关系的更深层次的基本理解，通过推进与人类工人和谐运行的智能工作技术的设计来促进社会需求。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。

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.