下面 就只对what-if 中 算法公平性这块 进行说明,什么是算法公平性,一句话概括:医生,大家一般会想起是 男性,而护士 一般都是女性,这就是 算法 不公平。 直接看 what-if demo https://pair-code.github.io/what-if-tool/image.html 不多说了,直接上重点: 原文解释:https://pair-code.github.io/what-if...
New fairness metrics You can now configure the following fairness metrics inWatson OpenScale: Statistical parity difference Average odds difference Average absolute odds difference False negative rate difference False positive rate difference False discovery rate difference ...
We conclude that Fair Share does little to alter important performance metrics such as expansion factor. This leads to the question of what Fair Share means on cluster machines. The essential difference between Fair Share on a uni-processor and a cluster is that the workload on a cluster is ...
Incorporate fairness metrics into the development process to assess how different subgroups are affected by the model's predictions. Monitor and minimize disparities in outcomes across various demographic groups. Apply constraints in the algorithm to ensure that the model adheres to predefined fairness cr...
Notebooks: Write and run your own code in managed Jupyter Notebook servers that are directly integrated in the studio. Or, open the notebooks inVS Code, on the web or on your desktop. Visualize run metrics: Analyze and optimize your experiments with visualization. ...
Performance Metrics:Use key performance indicators (KPIs) to measure progress. These are data points that show how well an individual or team is doing. Keep track of these metrics regularly. Flexibility:Be flexible and open to change. Sometimes, a rigid approach to performance management doesn’t...
It's a framework for building AI systems according to six principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. For Microsoft, these principles are the cornerstone of a responsible and trustworthy approach to AI, especially as intelligent ...
Fairness: Procurement should not provide preferential treatment to individuals or suppliers. All bids should be assessed objectively, based on how well they meet the organization’s needs. Competition: Organizations should seek competitive bids from multiple suppliers, unless there are specific reasons ...
Microsoft developed aResponsible AI Standard. It's a framework for building AI systems according to six principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. For Microsoft, these principles are the cornerstone of a responsible and trustworthy...
What are the principles of trustworthy AI? Different organizations and frameworks emphasize various guiding principles and goals for trustworthy AI. Frequently cited principles of trustworthy AI include: Accountability Explainability Fairness Interpretability and transparency ...