Explore the Basics of Data EthicsThis 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.
Learn the Art of Data Ethics PrinciplesThe 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 EthicsFree
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.Ethics issues across data life cycle50 xpThe ethics advantage50 xpBest practices all along100 xpValid consent50 xpWhat's in a consent form?100 xpThat doesn't seem valid50 xpData privacy and security50 xpPrivacy or security?100 xpBetter be safe than sorry50 xpTransparency and accountability50 xpNothing to hide!50 xpA role for everyone!100 xp
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.What do we do with data biases?50 xpAll is not fair in data100 xpCan we fix it all?50 xpFair data or FAIR data?50 xpReusing data50 xpWhat's FAIR again?100 xpOpen data for science and society50 xpWhy share?50 xpSharing is caring100 xpEvolving accountability and impact50 xpMeaningful accountability50 xpThrough ethics and thin100 xpCongratulations!50 xp
Shalini KurapatiSee More
Co-founder, Clearbox AI
Shalini Kurapati is the co-founder of Clearbox AI, a synthetic data company for privacy preservation and data quality augmentation. Shalini has studied and researched the impact of technology on society and policy and specializes in transparency, privacy, and fairness issues across data life cycles and algorithms. She is a researcher, trainer, and speaker on these topics. Shalini is a Certified Informational Privacy Professional (Europe) covering data protection regulation in the EU, focusing on GDPR. In her free time, Shalini likes to explore the Piedmontese (Italy) mountains, food, and culture.