标题： 人工智能、人类与数据科学：优化工作流程和劳动力中的角色 显示英文标题

标题： AI, Humans, and Data Science: Optimizing Roles Across Workflows and the Workforce

摘要： 人工智能正在改变研究。 它被用于构建调查、综合数据、进行分析并撰写结果的总结。 虽然其潜力在于提高效率和提升质量，但现实并不总是那么明确。 利用我们用于评估人工智能、机器学习和计算模型以实现有效和道德使用的核心框架——真理、美与正义（TBJ）（Taber和Timpone 1997；Timpone和Yang 2024），我们考虑分析型、生成型和代理型人工智能在增强数据科学家或承担传统上由人类分析师和研究人员完成的任务方面的潜力和局限性。 尽管人工智能可以被用来协助分析师完成任务，但我们对“一键式自动化”提出了一些警告。 正如早期的调查分析时代在统计软件使用变得更加简便时引发了一些问题，使得研究人员进行了他们并不完全理解的分析，新的AI工具可能会造成类似但更大的风险。 在整个数据科学工作流程中，我们强调人机协作的视角（Daugherty和Wilson 2018），并特别指出在VUCA决策领域中数据科学家的关键作用。 我们最后鼓励推进人工智能工具以补充数据科学家，但倡导持续培训和方法的理解，以确保通过最有效和伦理的方式应用、解释和采取行动来充分实现研究的实际价值。 显示英文摘要

摘要： AI is transforming research. It is being leveraged to construct surveys, synthesize data, conduct analysis, and write summaries of the results. While the promise is to create efficiencies and increase quality, the reality is not always as clear cut. Leveraging our framework of Truth, Beauty, and Justice (TBJ) which we use to evaluate AI, machine learning and computational models for effective and ethical use (Taber and Timpone 1997; Timpone and Yang 2024), we consider the potential and limitation of analytic, generative, and agentic AI to augment data scientists or take on tasks traditionally done by human analysts and researchers. While AI can be leveraged to assist analysts in their tasks, we raise some warnings about push-button automation. Just as earlier eras of survey analysis created some issues when the increased ease of using statistical software allowed researchers to conduct analyses they did not fully understand, the new AI tools may create similar but larger risks. We emphasize a human-machine collaboration perspective (Daugherty and Wilson 2018) throughout the data science workflow and particularly call out the vital role that data scientists play under VUCA decision areas. We conclude by encouraging the advance of AI tools to complement data scientists but advocate for continued training and understanding of methods to ensure the substantive value of research is fully achieved by applying, interpreting, and acting upon results most effectively and ethically.