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| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Sebastopol, CA
O'Reilly Media, Inc.
2023
|
| Edition: | [First edition]. |
| Subjects: | |
| Links: | https://learning.oreilly.com/library/view/-/9781098102425/?ar |
| Summary: | The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI--a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public. |
| Item Description: | Includes index |
| Physical Description: | 1 online resource (466 pages) illustrations |
| ISBN: | 9781098102395 1098102398 1098102401 9781098102401 1098102436 9781098102432 |
Staff View
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| 520 | |a The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI--a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public. | ||
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| edition | [First edition]. |
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| illustrated | Illustrated |
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| spelling | Hall, Patrick VerfasserIn aut Machine learning for high-risk applications approaches to responsible AI Patrick Hall, James Curtis, and Parul Pandey ; foreword by Agus Sudjianto [First edition]. Sebastopol, CA O'Reilly Media, Inc. 2023 1 online resource (466 pages) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes index The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI--a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public. Machine learning Risk management Artificial intelligence Apprentissage automatique Gestion du risque Intelligence artificielle risk management artificial intelligence Curtis, James VerfasserIn aut Pandey, Parul VerfasserIn aut Sudjianto, Agus MitwirkendeR ctb |
| spellingShingle | Hall, Patrick Curtis, James Pandey, Parul Machine learning for high-risk applications approaches to responsible AI Machine learning Risk management Artificial intelligence Apprentissage automatique Gestion du risque Intelligence artificielle risk management artificial intelligence |
| title | Machine learning for high-risk applications approaches to responsible AI |
| title_auth | Machine learning for high-risk applications approaches to responsible AI |
| title_exact_search | Machine learning for high-risk applications approaches to responsible AI |
| title_full | Machine learning for high-risk applications approaches to responsible AI Patrick Hall, James Curtis, and Parul Pandey ; foreword by Agus Sudjianto |
| title_fullStr | Machine learning for high-risk applications approaches to responsible AI Patrick Hall, James Curtis, and Parul Pandey ; foreword by Agus Sudjianto |
| title_full_unstemmed | Machine learning for high-risk applications approaches to responsible AI Patrick Hall, James Curtis, and Parul Pandey ; foreword by Agus Sudjianto |
| title_short | Machine learning for high-risk applications |
| title_sort | machine learning for high risk applications approaches to responsible ai |
| title_sub | approaches to responsible AI |
| topic | Machine learning Risk management Artificial intelligence Apprentissage automatique Gestion du risque Intelligence artificielle risk management artificial intelligence |
| topic_facet | Machine learning Risk management Artificial intelligence Apprentissage automatique Gestion du risque Intelligence artificielle risk management artificial intelligence |
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