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Machine Learning for High-Risk Applications - Techniques for Responsible AI (Paperback)
Loot Price: R1,318
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Machine Learning for High-Risk Applications - Techniques for Responsible AI (Paperback)
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The past decade has witnessed a wide adoption of artificial
intelligence and machine learning (AI/ML) technologies. However, a
lack of oversight into their widespread implementation has resulted
in harmful outcomes that could have been avoided with proper
oversight. Before we can realize AI/ML's true benefit,
practitioners must understand how to mitigate its risks. This book
describes responsible AI, a holistic approach 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. It's an ambitious undertaking
that requires a diverse set of talents, experiences, and
perspectives. Data scientists and nontechnical oversight folks
alike need to be recruited and empowered to audit and evaluate
high-impact AI/ML systems. Author Patrick Hall created this guide
for a new generation of auditors and assessors who want to make AI
systems better for organizations, consumers, and the public at
large. Learn how to create a successful and impactful responsible
AI practice Get a guide to existing standards, laws, and
assessments for adopting AI technologies Look at how existing roles
at companies are evolving to incorporate responsible AI Examine
business best practices and recommendations for implementing
responsible AI Learn technical approaches for responsible AI at all
stages of system development
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