Privacy and Artificial Intelligence - Course Outline

Course Outline

 

Part 1: Privacy-Related Problems with Artificial Intelligence

1.1 Excessive Data Collection and Lack of Minimization

1.2 Unauthorized Access and Data Breaches

1.3 Lack of Transparency and Explainability

1.4 Inadequate Consent Management and User Rights

1.5 Algorithmic Bias and Discrimination

1.6 Cross-Border Data Transfers and Compliance Risks

1.7 Vendor and Third-Party Risks

1.8 AI Hallucinations and Data Integrity

1.9 Surveillance and Loss of Autonomy

1.10 Regulatory Complexity and Compliance Burden

Part 2: Best Practices or Solutions

2.1 Privacy and Security by Design

2.2 Data Minimization and Robust Access Controls

2.3 Transparency and Explainability

2.4 Dynamic Consent Management and User Empowerment

2.5 Bias Mitigation and Fairness Audits

2.6 Privacy-Enhancing Technologies (PETs)

2.7 Continuous Monitoring, Auditing, and Incident Response

2.8 Vendor and Third-Party Risk Management

2.9 Cross-Functional Collaboration and Training

2.10 Regulatory Compliance and Adaptive Governance

Part 3: Non-Exhaustive Practical Checklists for Privacy Protection in AI

3.1 Government and Regulatory Authorities

3.2 Organizations and Businesses

3.3 Vendors and Third Parties

3.4 Employees and Internal Teams

3.5 Industry Groups and Professional Bodies

3.6 International and Multilateral Organizations

3.7 Consumers and Users

3.8 Members of the Public