Information Governance For Ai: Ethical And Compliant Handling Of Ai-generated Data

Introduction

Information Governance for AI: Ethical and Compliant Handling of AI-Generated Data equips professionals with the knowledge to manage the unique challenges of AI-generated information. This course focuses on analyzing ethical frameworks, implementing data governance policies, and understanding the impact of AI on data security and compliance. Participants will learn to utilize AI governance tools, ensure transparency and accountability in AI operations, and understand the intricacies of data provenance and bias mitigation. By mastering information governance for AI, professionals can enhance trust, mitigate risks, and contribute to the responsible development and deployment of AI technologies.

The increasing prevalence of AI and the need for ethical and compliant data management necessitate a comprehensive understanding of information governance for AI. This course delves into the intricacies of AI data lifecycle management, algorithmic transparency, and regulatory compliance, empowering participants to develop and implement effective AI governance frameworks. By integrating ethical principles with data governance best practices, this program enables individuals to lead AI governance initiatives and contribute to the creation of a trustworthy and sustainable AI ecosystem.

Target Audience:

• Data governance professionals
• AI developers
• Compliance officers
• Legal professionals
• Data scientists
• IT managers
• Risk managers
• Privacy officers
• Information security professionals
• Students of AI ethics and data science
• Individuals interested in AI governance
• Policy makers
• Auditors
• Business analysts
• Project managers

Course Objectives:

• Understand the principles and importance of information governance for AI.
• Implement techniques for analyzing ethical considerations in AI data handling.
• Understand the role of data governance policies in managing AI-generated data.
• Implement techniques for developing and implementing AI data governance frameworks.
• Understand the principles of AI data lifecycle management and data provenance.
• Implement techniques for ensuring data provenance and traceability in AI systems.
• Understand the role of algorithmic transparency and accountability in AI governance.
• Implement techniques for promoting transparency and accountability in AI operations.
• Understand the legal and regulatory frameworks surrounding AI data and its use.
• Implement techniques for ensuring compliance with AI-related regulations and standards.
• Understand the role of bias mitigation and fairness in AI data governance.
• Understand the challenges and opportunities of implementing AI governance in diverse industries.
• Develop strategies for implementing and scaling up AI data governance initiatives.

DURATION

10 Days

COURSE CONTENT

Module 1: Foundations of Information Governance for AI

• Principles and importance of information governance for AI.
• Understanding the evolution of AI and its impact on data management.
• Benefits of ethical AI data handling in enhancing trust and compliance.
• Historical context and emerging trends in AI governance.

Module 2: Ethical Considerations in AI Data Handling Analysis

• Techniques for analyzing ethical considerations in AI data handling.
• Implementing ethical frameworks and impact assessments.
• Utilizing ethical guidelines and principles.
• Managing ethical AI data reviews.

Module 3: Data Governance Policies in AI-Generated Data Management

• Understanding the role of data governance policies in managing AI-generated data.
• Implementing data quality, security, and privacy policies.
• Utilizing data governance tools and methodologies.
• Managing AI data policy development.

Module 4: AI Data Governance Framework Development and Implementation

• Techniques for developing and implementing AI data governance frameworks.
• Implementing data lifecycle management and access controls.
• Utilizing governance best practices and standards.
• Managing AI data governance programs.

Module 5: AI Data Lifecycle Management and Data Provenance

• Understanding the principles of AI data lifecycle management and data provenance.
• Implementing data lineage and traceability techniques.
• Utilizing metadata management and data cataloging.
• Managing data provenance records.

Module 6: Data Provenance and Traceability Assurance in AI Systems

• Techniques for ensuring data provenance and traceability.
• Implementing data audit trails and version control.
• Utilizing blockchain and other provenance technologies.
• Managing traceability compliance.

Module 7: Algorithmic Transparency and Accountability

• Understanding the role of algorithmic transparency and accountability.
• Implementing explainable AI (XAI) and model documentation.
• Utilizing transparency reporting and audit trails.
• Managing algorithmic transparency.

Module 8: Transparency and Accountability Promotion in AI Operations

• Techniques for promoting transparency and accountability.
• Implementing AI governance dashboards and reporting.
• Utilizing stakeholder engagement and feedback mechanisms.
• Managing AI accountability frameworks.

Module 9: Legal and Regulatory Frameworks

• Understanding the legal and regulatory frameworks surrounding AI data.
• Implementing compliance with data privacy laws and AI regulations.
• Utilizing regulatory reporting and documentation.
• Managing legal and regulatory risks.

Module 10: AI-Related Regulation and Standard Compliance Assurance

• Techniques for ensuring compliance with AI-related regulations and standards.
• Implementing compliance monitoring and reporting tools.
• Utilizing regulatory audits and examinations.
• Managing regulatory compliance.

Module 11: Bias Mitigation and Fairness in AI Data Governance

• Understanding the role of bias mitigation and fairness.
• Implementing fairness metrics and bias detection techniques.
• Utilizing data debiasing and algorithmic fairness tools.
• Managing bias mitigation strategies.

Module 12: Implementation Challenges in Diverse Industries

• Understanding the challenges of implementing AI governance in diverse industries.
• Implementing AI governance in different sectors and applications.
• Utilizing AI governance in multinational and global operations.
• Managing implementation in diverse contexts.

Module 13: AI Data Governance Initiative Scaling

• Techniques for developing AI data governance project roadmaps.
• Implementing pilot project testing and evaluation.
• Utilizing scalability and performance optimization techniques.
• Managing AI data governance team and governance.

Module 14: Case Studies: Information Governance for AI

• Analyzing real-world examples of AI governance implementations.
• Highlighting best practices and innovative solutions.
• Documenting project outcomes and impact.
• Industry and AI governance leader testimonials.

Module 15: The Future of AI Data Governance

• Exploring emerging technologies and trends in AI governance.
• Integrating AI governance tools and platforms.
• Adapting to evolving regulatory landscapes and ethical considerations.
• Building resilient and trustworthy AI ecosystems.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 5 working days before commencement of the training.