Justice in Data Science Teaching and Practice
Workshop Description
Justice, Diversity, Equity and Inclusion (JEDI) are challenges across STEM and in the emerging field of data science. In this workshop a panel will discuss these issues, covering topics ranging from inclusion and allyship to algorithmic bias and data feminism, and how justice-oriented approaches to data science teaching and learning may promote JEDI.
Prerequisites
None
Learning Outcomes
- Increased understanding of JEDI as it pertains to Data Science (DS);
- Ability to identify some of the systemic bias inherent in DS training, practice and methodologies;
- Ability to describe some personal and professional strategies towards JEDI in DS.
Tools used for this workshop
Zoom