Privacy and ethics in data management and AI

Module title:

Privacy and ethics in data management and AI

Module overview:

This module aims to provide students with a comprehensive understanding of the ethical and legal considerations surrounding data collection, storage, and utilization in the context of artificial intelligence. Throughout the course, students will focus on developing expertise in designing and implementing ethical frameworks and privacy-enhancing technologies to ensure responsible and accountable data management practices. By completing this course, students will be equipped with the knowledge and skills necessary to navigate complex ethical dilemmas and legal regulations in data science and AI, fostering ethical decision-making and societal responsibility.

In this module students will:
explore foundational concepts of privacy and ethics, including ethical theories, moral reasoning frameworks, and legal principles governing data management and AI
examine case studies and real-world examples of ethical challenges and privacy breaches in data science and AI, critically analyzing their implications and identifying lessons learned
cover a range of privacy-enhancing technologies and techniques, enabling students to implement privacy-preserving solutions in practice

Literature:

Required readings:
1. Davis, K. (2012). Ethics of big data: Balancing risk and innovation. O’Reilly Media.


Supplementary readings:
1. Schneier, B. (2016). Data and Goliath: The hidden battles to collect your data and control your world. WW Norton.
2. Loukides, M., Mason, H., and Patil, D. (2018). Ethics and Data Science. O’Reilly Media.