| 书目名称 | Responsible AI | | 副标题 | Implementing Ethical | | 编辑 | Sray Agarwal,Shashin Mishra | | 视频video | | | 概述 | Hands-on approach to ensure easy practical implementation of the concepts discussed.Most of the techniques covered are new, with only a few that refer to existing packages. For the techniques covered, | | 图书封面 |  | | 描述 | .This book is written for software product teams that use AI to add intelligent models to their products or are planning to use it. As AI adoption grows, it is becoming important that all AI driven products can demonstrate they are not introducing any bias to the AI-based decisions they are making, as well as reducing any pre-existing bias or discrimination. .. The responsibility to ensure that the AI models are ethical and make responsible decisions does not lie with the data scientists alone. The product owners and the business analysts are as important in ensuring bias-free AI as the data scientists on the team. This book addresses the part that these roles play in building a fair, explainable and accountable model, along with ensuring model and data privacy. Each chapter covers the fundamentals for the topic and then goes deep into the subject matter – providing the details that enable the business analysts and the data scientists to implement these fundamentals. ..AI research is one of the most active and growing areas of computer science and statistics. This book includes an overview of the many techniques that draw from the research or are created by combining different res | | 出版日期 | Book 2021 | | 关键词 | Ethical AI; explainable AI; Fair Machine Learning; Bias in AI; Black box AI; Data Privacy; Ethical AI; fair | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-76860-7 | | isbn_softcover | 978-3-030-76859-1 | | isbn_ebook | 978-3-030-76860-7 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 16:50:57
