In response to the growing recognition of the social, legal, and ethical impacts of new AI-based technologies, major AI and ML conferences and journals now encourage or require submitted papers to include ethics impact statements and undergo ethics reviews. This move has sparked heated debate concerning the role of ethics in AI and data science research, at times devolving into counter-productive name-calling and threats of "cancellation." We argue that greater focus on the moral education of data scientists may help bridge the ideological divide separating the data science community. We diagnose this deep ideological conflict as one between atomists and holists. Among other things, atomists espouse the idea that facts are and should be kept separate from values, while holists believe facts and values are and should be inextricable from one another. With the goals of encouraging civil discourse across disciplines and reducing disciplinary polarization, we draw on a variety of historical sources ranging from philosophy and law, to social theory and humanistic psychology, to describe each ideology's beliefs and assumptions. Finally, we call on atomists and holists within the data science community to exhibit greater empathy during ethical disagreements and propose four targeted strategies to ensure data science research benefits society.
翻译:由于人们日益认识到以AI为基础的新技术的社会、法律和伦理影响,因此,主要的AI和ML会议和期刊现在鼓励或要求提交论文,以纳入道德影响声明,并进行道德审查。这一举动引发了有关伦理在AI和数据科学研究中的作用的激烈辩论,有时还演变成反作用的点名和“取消”的威胁。我们争辩说,对数据科学家的道德教育的更多关注可能有助于弥合数据科学界之间的意识形态鸿沟。我们把这种深刻的意识形态冲突诊断为原子学家和集邮者之间的意识形态分歧。除其他外,原子学家主张将事实与价值观分开,并且应该将事实与价值观分开,而“黑名单”相信事实和价值观是而且应该不可分割地相互分离。为了鼓励跨学科的民间对话,减少学科的两极分化,我们从哲学和法律、社会理论以及人文心理学等各种历史渊源出发,描述每一种意识形态的信仰和假设。最后,我们呼吁数据科学界内的原子学家和集成者在伦理分歧中表现出更大的同情心,并提出四项有针对性的战略,以确保数据研究利益。