Product Information
Description
Privacy in Conversational AI: The Hidden Cost of Eavesdropping Machines — a survey of a frontier of autonomous AI in the Agents in the Wild series.
Book framework (chapter themes):
- Introduction — The Origins and Scope of Privacy Issues in Conversational AI Agents
- Technical Architecture of Conversational AI Agents and the Privacy Exposure Surface
- User Privacy Perception, Attitudes, and Behavior Patterns
- Mechanisms of Personally Identifiable Information Leakage in Conversational Interaction
- Contextual Privacy and the Theoretical Framework of Contextual Integrity
- Long-Term Memory and Privacy-Protection Mechanisms of Conversational Agents
- Prompt-Level Privacy Protection Techniques
- Federated Learning and Privacy-Preserving Training in Conversational AI
- On-Device Deployment and Localized Privacy Protection Solutions
- Adversarial Attacks and Privacy Defenses for Conversational Agents
- Evaluation Benchmarks and Datasets for Privacy-Preserving Conversational Systems
- Empirical Research and Measurement Methods for User Privacy Behavior
- Privacy Policy Transparency and Informed User Decision-Making
- Privacy Challenges in Specific Application Domains: Mental Health and Finance
- Privacy Protection in Voice and Multimodal Conversation
- The Personalization–Privacy Trade-off in Conversational Recommender Systems
- Legal, Ethical, and Societal Impact Analysis
- System Integration and Engineering Practice of Privacy-Preserving Technologies
- Open Problems, Challenges, and Future Research Directions
- Conclusion — Toward Privacy-by-Design Conversational AI Agents
Who it is for. For researchers, engineers, and advanced enthusiasts with a foundational knowledge of AI and privacy protection, who seek a systematic understanding of the full landscape of privacy issues in conversational AI agents.
