A Multimodal Approach to Integrating Ethics into an Undergraduate Data Science Curriculum

Oregon Convention Center 

In the age of generative AI and harmful automation tools that enhance existing inequalities, integrating ethics into our data science curricula is imperative. Statistics and data science professors are often not trained in philosophy and ethics and they lack the necessary background knowledge and skills to give a full treatment to ethics in their courses. This presentation discusses different approaches to integrating data science ethics into a statistics and data science curriculum. Partnering with philosophy/ethics departments on campus, one approach might be to create modules where ethics sections of courses could be mixed and matched. This work could be supported over the summer. Another approach may be to re-think our majors, requiring an ethics course. Perhaps an all-of-the above approach is best. The pros and cons of these various approaches, as well as implications for staffing and retraining are discussed.