Ethical Data Science - Major

Data science is an interdisciplinary field combining elements of statistics, mathematics, computer science, information science, machine learning, and artificial intelligence. The B.S. in Ethical Data Science program will give students an understanding of the tools and methods used to analyze data in order to help organizations find useful insights and make better, well-informed decisions.  Our undergraduate major is unique in that it integrates the social and ethical considerations of data science in every course.

Student Learning Outcomes

• Evaluate and construct data-centered arguments.
• Understand and implement an ethical data science life cycle process: posing a question; collecting, cleaning, and storing data; performing analysis and visualization; making inferences and predictions; communicating results; and making decisions.
• Explore how data, artificial intelligence and other analytical tools can be used to solve social problems and know when these approaches may be inappropriate.
• Assess the institutional contexts and practices of ethical data collection, classification, storage, analysis, and use. 
• Define “big data” and articulate the advantages and disadvantages of using large datasets in data analysis. 
• Critically evaluate power, fairness, accountability, trustworthiness, transparency, and other ethical considerations when using mathematical, computational, and/or sociotechnical approaches to data analysis.  
• Be able to connect emerging issues in big data analytics to interdisciplinary theories, debates, and frameworks.
• Demonstrate ethical self-awareness, personal conviction, and responsible action in the use of data science practices and technologies.