Introduction to Data Ethics

Explore data ethics with this comprehensive introductory course, covering principles, AI ethics, and practical skills to ensure responsible data use.

This introductory course on data ethics will provide learners with the essentials of data ethics concepts and what they mean in practice- be it in business, R&D, or for societal benefit. The course covers the principles of data ethics, its relationship with AI ethics, and its characteristics across the different stages of the data lifecycle. The course highlights how data ethics can promote fairness, reduce biases, and promote social good while addressing data protection, security, trust, and transparency. Learners will gain practical skills, including drafting informed consent forms and identifying the ethical impacts of data operations. By the end of the course, learners will have an essential understanding of data ethics. The course will equip them to identify and improve data ethics-related situations professionally and personally.

• Understanding Data Ethics
• In today's data-driven AI era, compliant and ethical use of data is more crucial than ever. We will explore and understand the impact and importance of data ethics for individuals, companies, and the wider society. We will highlight the nuanced relationship between ethics and data ethics. Using practical examples we will discuss the harms of unethical innovation and data practices as well as the benefits of data ethics. We will also highlight the relationship between data ethics and AI ethics, and introduce the strategies to implement them.
• Data Ethics: Now and Forever
• The chapter provides learners with practical knowledge and examples of the importance and implementation of data ethics in the different stages of the data lifecycle. The chapter covers the practical aspects of crucial data ethics concepts of data protection and security, informed consent, trust and transparency, and accountability.
• Data for Good
• This chapter focuses on data ethics that go beyond the usual discussions on data bias and fairness. Learners will better understand data-related biases and how to deal with them. They will also learn about the FAIR- Findable, Accessible, Interoperable, and Reusable data principles for sharing data openly. They will also understand the benefits of open data for science and society. Finally, learners will explore the evolving accountability and impact of data operations, emphasizing the moral responsibility of company leaders and data scientists and preparing for the future of data ethics.