道德使命：揭示负责任数据科学实践中的道德决策策略
Moral Missions: Surfacing Moral Decision-Making Strategies for Responsible Data Science Practice
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中文总结 AI 辅助
本研究通过访谈15名从业者，提出将负责任数据科学视为道德使命，揭示具身内省、规避制度期望和注重关系性等决策策略，并呼吁建立颠覆性社区以支持可持续实践。
中文摘要 AI 辅助
为帮助数据科学家考虑数据驱动技术的社会影响，一个由技术、工具包和指南组成的生态系统已日益发展壮大。然而，先前文献强调，即使向专业数据科学家提供这一技术生态系统，他们仍难以持续采用负责任的数据科学实践。我们认为，实现可持续的负责任数据科学实践的关键在于将其视为一种道德使命：一种由信念驱动的技术实践，力求以任何可能的程度改变社会状况。在本文中，我们开展了一项半结构化访谈研究，对象为15名负责任的数据科学家和人工智能从业者，以了解他们用于阐述和实现其道德使命的道德决策程序。通过对参与者叙述的现象学分析，我们发现参与者在整个道德使命过程中进行具身内省、规避制度期望并注重关系性。我们还展示了参与者如何在负责任实践中采用类似程序来应对生成式人工智能（GenAI）。最后，我们呼吁建立颠覆性数据科学社区，并确定社会技术设计启示，以更好地支持可持续的负责任数据科学实践。
英文摘要
A growing ecosystem of techniques, toolkits, and guidelines has been developed to help data scientists consider the social implications of data-driven technologies. However, prior literature highlights that even when this ecosystem of techniques is provided to professional data scientists, they still struggle to consistently adopt a responsible data science practice. We posit that the key to sustained responsible data science practice is to approach it as a moral mission: a conviction-driven technical practice that seeks to transform social conditions by any degree possible. In this paper, we present a semi-structured interview study with 15 responsible data scientists and AI practitioners to understand the moral decision-making procedures they use to articulate and actualize their moral missions. Through a phenomenological analysis of our participants' accounts, we find participants engage in embodied introspection, circumvent institutional expectations, and center relationality throughout their moral missions. We also present how our participants engage in similar processes to contend with generative AI (GenAI) in their responsible practice. We conclude by calling for subversive data science communities and identifying sociotechnical design implications to better support sustainable responsible data science practice.
