AI and Privacy Navigating Data Ethics Challenges: Address privacy concerns in AI-driven data processing

Independently published
SKU:
9798262318162
|
ISBN13:
9798262318162
$18.08
(No reviews yet)
Usually Ships in 24hrs
Current Stock:
Estimated Delivery by: | Fastest delivery by:
Adding to cart… The item has been added
Buy ebook
Powerful AI. Respectful data. Zero excuses.In AI and Privacy: Navigating Data Ethics Challenges, you'll get a practical, no-nonsense playbook for building AI systems that earn trust-from dataset to deployment. This guide shows you how to ship models that deliver value without violating user privacy, running afoul of regulators, or damaging your brand.Inside, you'll learn how to: Design privacy by default: data minimization, purpose limitation, retention controls, and data contracts that actually stick.Apply privacy-preserving ML at scale: differential privacy, federated learning with secure aggregation, synthetic data, and robust de-identification.Protect sensitive information with cryptographic safeguards: homomorphic encryption and secure multi-party computation.Build resilient systems against AI-specific privacy threats: model inversion, membership inference, and data leakage in LLMs.Operationalize compliance across regions (GDPR, CCPA/CPRA, HIPAA): DPIAs, DSAR workflows, RoPA, consent management, and audit-ready evidence.Integrate privacy with MLOps: lineage, reproducibility, governance, red-teaming, monitoring, incident response, and human-in-the-loop approvals.Communicate clearly with users: transparent UX, meaningful notices, and controls that reduce risk and improve adoption.Featuring field-tested checklists, templates, and step-by-step workflows, this book turns abstract principles into buildable, defensible practices-so your AI is innovative, compliant, and worthy of trust.Who This Book Is ForPrivacy & security leaders (DPOs, CISOs, counsel) aligning AI with policy and lawML engineers & data scientists embedding privacy into pipelines and modelsProduct & platform teams accountable for trustworthy, auditable AIStudents & researchers seeking a modern, practical foundation in AI privacyShip AI that respects people-and stands up to scrutiny.


  • | Author: Corwin Halesworth
  • | Publisher: Independently Published
  • | Publication Date: Aug 26, 2025
  • | Number of Pages: 248 pages
  • | Binding: Paperback or Softback
  • | ISBN-13: 9798262318162
Author:
Corwin Halesworth
Publisher:
Independently Published
Publication Date:
Aug 26, 2025
Number of pages:
248 pages
Binding:
Paperback or Softback
ISBN-13:
9798262318162