Data Privacy and Security Training: Safeguarding Sensitive Data in AI
- Equip participants with a comprehensive understanding of data privacy and security considerations in AI.
- Provide practical strategies and best practices to ensure compliance with the EU AI Act's requirements for data protection.
- Empower teams to effectively handle and safeguard sensitive data throughout the AI lifecycle.
Training Duration: 1-day workshop
Training Fee: €1500
Module 1: Introduction to Data Privacy and Security in AI
- Understanding the significance of data privacy and security in AI systems.
- Exploring the implications of the EU AI Act's data protection mandates on AI practices.
Module 2: GDPR and Beyond: Legal Landscape for Data Protection
- A deep dive into GDPR regulations and their implications for AI data handling.
- Navigating other global data protection regulations and their alignment with the EU AI Act.
Module 3: Identifying Sensitive Data in AI
- Recognizing the types of sensitive data commonly used in AI models.
- Understanding the ethical and legal responsibilities of handling personal and sensitive data.
Module 4: Data Collection and Processing Best Practices
- Guidelines for ethically collecting, processing, and storing data in compliance with privacy regulations.
- Strategies to ensure data minimization, purpose limitation, and user consent.
Module 5: Securing Data Infrastructure in AI
- Exploring cybersecurity measures to protect data stored and processed by AI systems.
- Encryption, access controls, and monitoring for data security.
Module 6: The EU AI Act and Data Privacy Compliance
- Analyzing the EU AI Act's requirements related to data privacy and security.
- Mapping AI data practices to the Act's mandates to ensure compliance.
Module 7: Handling Data Breaches and Incidents
- Strategies for responding to data breaches and security incidents effectively.
- Preparing incident response plans to mitigate risks and minimize impact.
Module 8: Interactive Workshops and Case Studies
- Collaborative discussions on real-world scenarios related to data privacy and security in AI.
- Analyzing case studies to identify best practices for handling sensitive data.
Module 9: Building a Data Privacy Culture
- Strategies for fostering a culture of data privacy and security awareness within the organization.
- Empowering participants to champion data protection principles.
Expert presentations on data privacy and security regulations, practices, and case studies.
Group discussions to explore practical scenarios and ethical dilemmas.
Q&A sessions to address participant queries and concerns.
Comprehensive understanding of data privacy and security regulations in AI.
Practical skills in handling and securing sensitive data throughout the AI lifecycle.
Alignment with the EU AI Act's data protection requirements.
Empowerment to build a data privacy culture within the organization.