Ethics And Legal Issues In Data Science
Legal and ethical consequences of applying Data Science. Current techniques such as Digital Data Repositories and Digital Object Identifiers as well as FAIR principles for Open Science, Open Data. Data ownership and transparency; privacy concerns and consent; and addressing unintended bias. Topics:…
Learning outcomes
At the end of the course, the students should be able to: 1. identify ethical challenges and considerations when working with data of various sources, context, and compositions; and 2. contribute to global debates regarding best practices for handling sensitive data in a way that avoids harm to data subjects, while also not eroding the utilities that such data could present for various decision-making processes.
Course contents
Legal and ethical consequences of applying Data Science. Current techniques such as Digital Data Repositories and Digital Object Identifiers as well as FAIR principles for Open Science, Open Data. Data ownership and transparency; privacy concerns and consent; and addressing unintended bias. Topics: Legal aspects of data ownership and privacy concerns, Data transparency, Ethical considerations for Data Science, Introduction to Data Repositories and New Computing 111 Digital Object Identifiers, Introduction to Open Science, Open Data, and Introduction to FAIR data.