Standard: Collaborative Research: Emerging Cultures of Data Science Ethics in the Academy and Industry

“大数据”时代创造了“数据科学家”形式的新科学角色-专业信息知识工作者，他们应用技术和研究技能从大型数据库中获取知识。然而，与这些新角色的创建相伴而来的是，围绕大数据及其创建算法的潜在滥用的备受瞩目的争议的兴起。因此，该项目的重点是“数据科学伦理”，并致力于了解如何最好地培养数据科学的伦理文化。它将评估教育和工业环境中数据伦理的状态，结构和实质。在学术领域，该项目将与教师和本科生进行访谈，并分析相关教学大纲，以了解学院中的数据伦理构成。将这些数据在教师和学科之间进行比较，将显示出关于数据伦理教育应该包括什么的主要共识和分歧。在工业部门，该项目将研究数据道德如何开始融入企业实践，研究公司如何定义数据道德，并试图将道德考虑纳入日常工作。数据将来自对业内人士的深入采访，以及对公开承诺解决数据道德问题的公司文件的分析。然后，PI将比较这两种背景下的数据和发现，以确定共同点，差异和有用的策略，以促进社会背景和专业部门的数据道德。该项目将汇集一批不同的研究人员，他们将与教育工作者和数据科学从业者合作：（1）记录和评估将伦理纳入数据科学实践的障碍和机会;（2）评估工业和学术环境之间出现的连续性和不连续性;（3）为连贯，全面，综合的数据伦理教育奠定基础。调查人员将使用一系列补充方法来做到这一点，包括定性访谈，专家判断，以及对学术界和工业界文件的潜在主题和主题结构进行定量计算分析。项目成果和发现将通过会议、期刊以及在数据收集和分析完成后举办综合研讨会的方式进行传播。该奖项反映了NSF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。

The 'big data' era has created new scientific roles in the form of 'data scientists' - specialized information knowledge workers who apply technical and research skills to derive knowledge from large-scale databases. Concomitant with the creation of these new roles, however, has been the rise of high-profile controversies around the potential abusive use of big data and of the algorithms whose creation they enable. This project thus focuses on 'data science ethics' and works to understand how to best cultivate a culture of ethics in data science. It will assess the state, structure, and substance of data ethics in both educational and industrial contexts. Within the academic sector, the project will conduct interviews with faculty and undergraduates and analyze relevant syllabi to develop an account of what constitutes data ethics in the academy. Comparing these data across faculty and disciplines will show major areas of agreement and disagreement over what data ethics education should entail. Within the industrial sector, the project will research how data ethics are beginning to figure into corporate practice and study how companies define data ethics and attempt to integrate ethical considerations into everyday work. Data will come from in-depth interviews with those in industry and analyses of corporate documents from companies that have made public commitments to addressing data ethics. The PIs would then compare data and findings from across these two contexts to identify commonalities, differences, and useful strategies for advancing data ethics across social contexts and professional sectors. This project will draw together a diverse group of researchers who in collaboration with educators and data science practitioners will: (1) document and assess barriers and opportunities for integrating ethics into data science practice; (2) assess the continuities and discontinuities emerging between industrial and academic contexts; and (3) develop a foundation for cohesive, comprehensive, integrative data ethics education. The investigators will use a range of complementary methods to do so, including qualitative interviews, expert judgement, and quantitative computational analyses of the latent thematic and topical structure of documents from academia and industry. Project outcomes and findings will be disseminated through conferences, journals, and through holding a synthetic workshop after the completion of data collection and analysis.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.