helpResearch question机器学习公平性与数据开发实践数据标注中,标注者的多样性如何影响数据集的质量和机器学习模型的公平性?CHI '23A hunt for the Snark: Annotator Diversity in Data Practices
helpResearch question机器学习公平性与数据开发实践如何通过引入公众参与改善机器学习(ML)管道设计中的公平性和透明性?CHI '25Preventing Harmful Data Practices by using Participatory Input to Navigate the Machine Learning Multiverse
helpResearch question机器学习公平性与数据开发实践公众参与在约束ML多元宇宙决策空间上是否能够提高模型的公平性与性能?CHI '25Preventing Harmful Data Practices by using Participatory Input to Navigate the Machine Learning Multiverse
helpResearch question机器学习公平性与数据开发实践在社会性算法设计中,如何有效减少“懒惰数据处理”导致的偏见问题?CHI '25Preventing Harmful Data Practices by using Participatory Input to Navigate the Machine Learning Multiverse
helpResearch question机器学习公平性与数据开发实践如何在数据增强和偏差消除过程中有效引入领域专家以减少AI系统中的表示偏差?CHI '25Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems
helpResearch question机器学习公平性与数据开发实践哪些引导方式可以使领域专家更好识别、生成和验证数据,以提高数据质量和模型公平性?CHI '25Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems
helpResearch question机器学习公平性与数据开发实践在高风险领域(如医疗健康)中,引入领域专家的偏差消除设计框架如何影响AI模型性能和公平性?CHI '25Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems