Book description
This book is a comprehensive, cutting-edge guide designed to educate readers on the essentials of artificial intelligence (AI) and machine learning (ML), while emphasizing the crucial aspects of security, ethics, and privacy. The book aims to equip AI practitioners, IT professionals, data scientists, security experts, policy-makers, and students with the knowledge and tools needed to develop, deploy, and manage AI and ML systems securely and responsibly.
The book is divided into several sections, each focusing on a specific aspect of AI. It begins by introducing the fundamentals of AI technolgies, providing an overview of their history, development, and various types. This is followed by a deep dive into popular AI algorithms and large language models (LLMs), including GPT-4, that are at the forefront of AI innovation.
Next, the book explores the critical security aspects of AI systems, examining the importance of security and the key challenges faced in this domain. It also delves into the common threats, vulnerabilities, and attack vectors, as well as risk assessment and management strategies. This manuscript covers data security, model security, system and infrastructure security, secure development practices, monitoring and auditing, supply chain security, and secure deployment and maintenance.
Another key focus of the book is privacy and ethical considerations in AI systems. Topics covered include bias and fairness, transparency and accountability, and privacy and data protection. The book also addresses legal and regulatory compliance, providing an overview of relevant regulations and guidelines, and discussing how to ensure compliance in AI systems through case studies and best practices.This book is a comprehensive, cutting-edge guide designed to educate readers on the essentials of artificial intelligence (AI) and machine learning (ML), while emphasizing the crucial aspects of security, ethics, and privacy. The book aims to equip AI practitioners, IT professionals, data scientists, security experts, policy-makers, and students with the knowledge and tools needed to develop, deploy, and manage AI and ML systems securely and responsibly.
Table of contents
- Cover Page
- About This eBook
- Halftitle Page
- Title Page
- Copyright Page
- Credits
- Dedication Page
- Contents
- Preface
- Acknowledgments
- About the Authors
-
1. Historical Overview of Artificial Intelligence (AI) and Machine Learning (ML)
- The Story of Eva
- The Origins
- Advancements of Artificial Intelligence
- Understanding AI and ML
- Concluding the Story of Eva
- Summary
- Test Your Skills
- Exercise 1-1: Exploring the Historical Development and Ethical Concerns of AI
- Exercise 1-2: Understanding AI and ML
- Exercise 1-3: Comparison of ML Algorithms
- Exercise 1-4: Assessing Applications of ML Algorithms
-
2. Fundamentals of AI and ML Technologies and Implementations
- What Are the Leading AI and ML Technologies and Algorithms?
- ChatGPT and the Leading AI and ML Technologies: Exploring Capabilities and Applications
- Understanding the Two Categories of AI: Capability-Based Types and Functionality-Based Types
- Leveraging AI and ML to Tackle Real-World Challenges: A Case Study
- Reflecting on the Societal and Ethical Implications of AI Technologies
- Assessing Future Trends and Emerging Developments in AI and ML Technologies
- Summary
- Test Your Skills
- Exercise 2-1: Algorithm Selection Exercise: Matching Scenarios with Appropriate Machine Learning Techniques
- Exercise 2-2: Exploring AI and ML Technologies
- Exercise 2-3: Capabilities and Benefits of AI-Optimized Hardware
- Exercise 2-4: Understanding the Two Categories of AI
- Exercise 2-5: Future Trends and Emerging Developments in AI and ML Technologies
- 3. Generative AI and Large Language Models
- 4. The Cornerstones of AI and ML Security
- 5. Hacking AI Systems
-
6. System and Infrastructure Security
- The Vulnerabilities and Risks Associated with AI Systems and Their Potential Impact
- AI BOMs
- Data Security Vulnerabilities
- Cloud Security Vulnerabilities
- Secure Design Principles for AI Systems
- AI Model Security
- Infrastructure Security for AI Systems
- Threat Detection and Incident Response for AI Systems
- Additional Security Technologies and Considerations for AI Systems
- Summary
- Test Your Skills
- Additional Resources
-
7. Privacy and Ethics: Navigating Privacy and Ethics in an AI-Infused World
- Why Do We Need to Balance the Benefits of AI with the Ethical Risks and Privacy Concerns?
- What Are the Challenges Posed by AI in Terms of Privacy Protection, and What Is the Importance of Privacy and Ethics in AI Development and Deployment?
- The Dark Side of AI and ChatGPT: Privacy Concerns and Ethical Implications
- Data Collection and Data Storage in AI Algorithms: Potential Risks and Ethical Privacy Concerns
- The Moral Tapestry of AI and ChatGPT
- Preserving Privacy, Unleashing Knowledge: Differential Privacy and Federated Learning in the Age of Data Security
- Harmony in the Machine: Nurturing Fairness, Diversity, and Human Control in AI Systems
- Real-World Case Study Examples and Fictional Stories of Privacy Breaches in AI and ChatGPT
- Summary
- Test Your Skills
- Exercise 7-1: Privacy Concerns and Ethical Implications of AI
- Exercise 7-2: Ethical Privacy Concerns in Data Collection and Storage by AI Algorithms
- Exercise 7-3: Balancing Autonomy and Privacy in the Age of AI
- Exercise 7-4: Safeguarding Privacy and Ethical Frontiers
-
8. Legal and Regulatory Compliance for AI Systems
- Legal and Regulatory Landscape
- Compliance with AI Legal and Regulatory Data Protection Laws
- Intellectual Property Issues in Conversational AI
- Unraveling Liability and Accountability in the Age of AI
- Ethical Development and Deployment of AI Systems: Strategies for Effective Governance and Risk Management
- International Collaboration and Standards in AI
- Future Trends and Outlook in AI Compliance
- Unleashing the Quantum Storm: Fictional Story on AI Cybersecurity, Quantum Computing, and Novel Cyberattacks in Oxford, 2050
- Summary
- Test Your Skills
- Exercise 8-1: Compliance with Legal and Regulatory Data Protection Laws
- Exercise 8-2: Understanding Liability and Accountability in AI Systems
- Exercise 8-3: International Collaboration and Standards in AI
- Appendix A. Test Your Skills Answers and Solutions
- Index
- Code Snippets
Product information
- Title: Beyond the Algorithm: AI, Security, Privacy, and Ethics
- Author(s):
- Release date: January 2024
- Publisher(s): Addison-Wesley Professional
- ISBN: 9780138268442
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