NRT-HDR: Detecting and Addressing Bias in Data, Humans, and Institutions

NRT-HDR：检测和解决数据、人类和机构中的偏见

• 批准号: 2125295
• 负责人: Susan Brennan
• 金额: $ 299.95万
• 依托单位: SUNY at Stony Brook
• 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: 2021-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2125295&HistoricalAwards=false
• 关键词: NRT; HDR; Detecting; Addressing; Bias

Data science has become a powerful tool for generating new knowledge, fueling innovation, and dealing with society's most pressing problems. Harnessing this data revolution requires broadening the participation of U.S. citizens in the data science workforce, especially of women and other under-represented groups. This National Science Foundation Research Traineeship (NRT) award to Stony Brook University (the State University of New York at Stony Brook) will prepare a diverse pool of students to become fluent in both data sciences and human-centered sciences. The program will enable students to conduct convergent research in problem domains that blend data science with deep disciplinary knowledge. The project anticipates training sixty-eight (68) Ph.D. students, including thirty-four (34) NRT-funded trainees, recruited from both the human-centered sciences (HCS, consisting of Psychology, Linguistics, Economics, Neurobiology & Behavior, Political Science, and Sociology) and the data sciences (DS, consisting of Computer Science and Applied Mathematics & Statistics). In the U.S., scientifically oriented domestic students tend to gather in distinct siloes, with significantly higher proportions of women in HCS than in DS fields. HCS students are well-trained in the traditional empirical methods of their fields. However, many do not identify as "data scientists." These HCS students may lack the preparation to dive into graduate coursework in computer science to acquire cutting-edge research skills in areas such as artificial intelligence, machine learning, and big data that could empower their research. And many DS students lack a deep theoretical and practical understanding of how datasets are collected and their limitations. Moreover, DS students may lack the skills to assess the impacts of data-based technology upon human beings and society. In this two-pathway training model, DS trainees will take graduate coursework in an HCS domain, earning a certificate in the Human-Centered Sciences. Meanwhile, HCS trainees will take any needed intensive bridge courses to prepare them for graduate coursework in DS and earn an Artificial Intelligence certificate. Trainees will come together in three team-taught research practica centered on a relevant and inclusive theme: bias—in data, in humans, and in institutions. These practica will focus on discovering how the use of powerful quantitative methods can camouflage biases (both implicit and explicit) that, in a given context, advantage some human beings and disadvantage others. Both trainees and trainers will practice techniques for detecting and addressing biases in themselves and their research, as well as within social and institutional settings. Together, they will join convergent research collaborations that target pervasive problems of inequity and the ethical uses of technology. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.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.

数据科学已经成为产生新知识、推动创新和处理社会最紧迫问题的强大工具。利用这场数据革命需要扩大美国公民在数据科学劳动力中的参与，特别是女性和其他代表性不足的群体。这个国家科学基金会研究培训（NRT）奖给斯托尼布鲁克大学（纽约州立大学斯托尼布鲁克）将准备一个多元化的学生池，成为流利的数据科学和以人为本的科学。该计划将使学生能够在问题领域进行融合研究，将数据科学与深入的学科知识相结合。该项目预计将培养68名博士。学生，包括三十四（34）NRT资助的学员，从两个以人为本的科学（HCS，包括心理学，语言学，经济学，神经生物学行为，政治学和社会学）和数据科学（DS，包括计算机科学和应用数学统计学）招募。在美国，以科学为导向的国内学生往往集中在不同的领域，高等科学领域的妇女比例明显高于发展科学领域。HCS学生在各自领域的传统经验方法方面训练有素。然而，许多人并不认为自己是“数据科学家”。“这些HCS学生可能缺乏深入计算机科学研究生课程的准备，以获得人工智能，机器学习和大数据等领域的尖端研究技能，这些技能可以增强他们的研究能力。许多DS学生对数据集的收集方式及其局限性缺乏深入的理论和实践理解。此外，DS学生可能缺乏评估基于数据的技术对人类和社会的影响的技能。在这种双途径培训模式中，DS学员将参加HCS领域的研究生课程，获得以人为本的科学证书。同时，HCS学员将参加任何必要的强化桥梁课程，为DS的研究生课程做好准备，并获得人工智能证书。学员将聚集在三个团队授课的研究实践集中在一个相关的和包容性的主题：偏见在数据，在人类和机构。这些实践将侧重于发现如何使用强大的定量方法来掩盖偏见（包括隐性和显性），在给定的背景下，有利于一些人，不利于其他人。学员和培训员都将练习检测和解决自身及其研究中以及社会和机构环境中的偏见的技术。他们将共同加入针对普遍存在的不平等问题和技术道德使用的趋同研究合作。NSF研究培训（NRT）计划旨在鼓励为STEM研究生教育培训开发和实施大胆的，新的潜在变革模式。该计划致力于通过创新的、基于证据的、与不断变化的劳动力和研究需求相一致的综合培训模式，在高优先级的跨学科或融合研究领域对STEM研究生进行有效培训。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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• 发表时间: 2023
• 期刊: Society for Affective Science 2023 Conference
• 作者: Sekine Ozturk, M.A.

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• 发表时间: 2023
• 期刊: Society for Personality and Social Psychology (SPSP
• 作者: Carl J. Wiedemann & Antonio L. Freitas, Ph.D.