Big Data Ethics and Governance
Description
Comprehensive understanding of ethical considerations, legal compliance, privacy protection, and governance frameworks for responsible big data analytics and artificial intelligence applications.
Learning Objectives
Students will understand the ethical implications of big data analytics, implement privacy protection and data security measures, ensure compliance with data protection regulations like GDPR and CCPA, develop data governance frameworks, address algorithmic bias and fairness issues, and create responsible AI practices for big data applications while balancing innovation with ethical considerations.
Topics (8)
Understanding and addressing bias in algorithms and AI systems to ensure fairness, equity, and non-discrimination in big data applications.
Structured approaches to data governance including organizational frameworks, policies, and procedures for managing big data assets responsibly.
Proactive privacy protection measures built into big data systems from the design phase including technical and organizational measures.
Advanced security measures and cybersecurity practices specifically designed for protecting big data systems and sensitive information from threats.
Methods for making AI and big data analytics more transparent, interpretable, and explainable to stakeholders and affected individuals.
Ethical frameworks and social responsibility considerations for data scientists and organizations using big data analytics for social good and responsible innovation.
Comprehensive understanding of global data privacy regulations and their implications for big data processing, storage, and analytics operations.
Systematic approaches for evaluating and monitoring the ethical implications of big data projects throughout their lifecycle including review processes and impact assessments.