Building Responsible AI Algorithms (eBook)
XVII, 190 Seiten
Apress (Verlag)
978-1-4842-9306-5 (ISBN)
- Build AI/ML models using Responsible AI frameworks and processes
- Document information on your datasets and improve data quality
- Measure fairness metrics in ML models
- Identify harms and risks per task and run safety evaluations on ML models
- Create transparent AI/ML models
- Develop Responsible AI principles and organizational guidelines
?Toju Duke is a Responsible AI Program Manager at Google with over 17 years of experience spanning across advertising, retail, not-for-profits, and tech industries. She designs Responsible AI programs focused on the development and implementation of Responsible AI frameworks, processes, and tools across Google's product and research teams. Toju is also the Founder of Diverse in AI, a community interest organization with a mission to provide inclusive and diverse AI through humanity. She provides consultation and advice on Responsible AI practices to organizations worldwide.
This book introduces a Responsible AI framework and guides you through processes to apply at each stage of the machine learning (ML) life cycle, from problem definition to deployment, to reduce and mitigate the risks and harms found in artificial intelligence (AI) technologies. AI offers the ability to solve many problems today if implemented correctly and responsibly. This book helps you avoid negative impacts - that in some cases have caused loss of life - and develop models that are fair, transparent, safe, secure, and robust.The approach in this book raises your awareness of the missteps that can lead to negative outcomes in AI technologies and provides a Responsible AI framework to deliver responsible and ethical results in ML. It begins with an examination of the foundational elements of responsibility, principles, and data. Next comes guidance on implementation addressing issues such as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers. What You Will LearnBuild AI/ML models using Responsible AI frameworks and processesDocument information on your datasets and improve data qualityMeasure fairness metrics in ML modelsIdentify harms and risks per task and run safety evaluations on ML modelsCreate transparent AI/ML modelsDevelop Responsible AI principles and organizational guidelinesWho This Book Is ForAI and ML practitioners looking for guidance on building models that are fair, transparent, and ethical; those seeking awareness of the missteps that can lead to unintentional bias and harm from their AI algorithms; policy makers planning to craft laws, policies, and regulations that promote fairness and equity in automated algorithms
Erscheint lt. Verlag | 31.8.2023 |
---|---|
Zusatzinfo | XVII, 190 p. 5 illus., 1 illus. in color. |
Sprache | englisch |
Themenwelt | Geisteswissenschaften ► Philosophie ► Ethik |
Informatik ► Theorie / Studium ► Algorithmen | |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Schlagworte | AI and ML Ethics • AI Transparency • Algorithmic fairness • Data Quality • explainability • Fairness Metrics • Humans in the Loop • Interpretability • Machine Learning Fairness • Machine Learning Safety • responsible AI • Responsible AI Frameworks • Transparent AI Models |
ISBN-10 | 1-4842-9306-1 / 1484293061 |
ISBN-13 | 978-1-4842-9306-5 / 9781484293065 |
Haben Sie eine Frage zum Produkt? |
Größe: 3,2 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich