数据风险作为神经科学的一种伦理工具包。
Data Hazards as An Ethical Toolkit for Neuroscience.
作者信息
García Susana Román, Welsh Ceilidh, Di Cara Nina H, Sterratt David C, Romanò Nicola, Stefan Melanie I
机构信息
Centre for Discovery Brain Sciences, College of Medicine & Veterinary Medicine, Biomedical Sciences, University of Edinburgh, Edinburgh, UK.
Department of Oncology, University of Cambridge, Cambridge, UK.
出版信息
Neuroethics. 2025;18(1):15. doi: 10.1007/s12152-024-09580-3. Epub 2025 Feb 19.
UNLABELLED
The Data Hazards framework (Zelenka, Di Cara, & Contributors, 2024) is intended to encourage thinking about the ethical implications of data science projects. It takes the form of community-designed data hazard labels, similar to warning labels on chemicals, that can encourage reflection and discussion on what ethical risks are associated with a project and how they can be mitigated. In this article, we explain how the Data Hazards framework can apply to neuroscience. We demonstrate how the hazard labels can be applied to one of our own projects, on the computational modelling of postsynaptic mechanisms.
SUPPLEMENTARY INFORMATION
The online version contains supplementary material available at 10.1007/s12152-024-09580-3.
未标注
数据风险框架（泽伦卡、迪卡拉及其他贡献者，2024年）旨在鼓励人们思考数据科学项目的伦理影响。它采用了社区设计的数据风险标签形式，类似于化学品上的警示标签，可促使人们思考与项目相关的伦理风险以及如何减轻这些风险。在本文中，我们解释了数据风险框架如何应用于神经科学。我们展示了如何将风险标签应用于我们自己的一个项目，即突触后机制的计算建模。
补充信息
在线版本包含补充材料，可在10.1007/s12152-024-09580-3获取。
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