Ethics, Privacy, and Social Justice in Data Science
Course Details
- Course Title: Ethics, Privacy, and Social Justice in Data Science:
- Course Code: MSDS-640
- Credit Hours: 3
- Pre-requisite: MSDS 600 – Introduction to Data Science
- Offered To: Master of Science in Data Science
- Level: Graduate
- Institution: Regis University, Denver, CO, USA
- Faculty: Marketing and Data Science Department
- Semester Offered: Fall 2024
Objectives
This course explores ethical and privacy issues in data science through case studies and professional conduct codes. It ultimately focuses on data science experiments aimed at promoting social justice. It seeks to develop a thorough understanding of data science ethics, privacy implications, and social justice applications.
Learning Outcomes
Upon completion, students will be equipped to articulate ethics, privacy, and social justice issues within data science. They will apply ethical and privacy standards throughout the data science project lifecycle and identify ethical and privacy concerns associated with Big Data, data mining, and social media analysis. Additionally, students will evaluate ethical and confidentiality standards and codes in data science and connect the discipline to advancing social justice.
Course Outline
| Lecture | Topic |
|---|---|
| 1 | Introduction to Ethics, Privacy, and Social Justice |
| 2 | Ethics, Privacy, and the Data Science Project Lifecycle |
| 3 | Ethics, Privacy, and the Data Science Project Lifecycle |
| 4 | Government Regulations and Governance |
| 5 | Ethics and Privacy in Government Analytics |
| 6 | Social Media and the Internet in Data Science |
| 7 | Data Science for Social Justice |
| 8 | Data Science Social Justice Data Sources |
Final Grand Case Studies by Students
- Ethical AI in Hiring by Pavan Kalyan Reddy Kamasaani, Praveen Goud Angolla, and Karunakar Thammadi
- Data Breach Analysis: A Comprehensive Study by Maryi Palacios, Barsha Kakshapatii, and Villi Sigurdsson
- Ethical Analysis of Predictive Analytics in Retail Industry by Madhuri Kothi, Nahian Arnob, and Chamundeshwari Kottur
- Resume Bias in AI Hiring Systems by Kommineni Rayudu, Sonam Rinjin Sherpa, Karthik Javvaji, and Raji Reddy
- Breast Cancer Patient Bias by Prakriti Dahal, Rabin Acharya, Apurba Poudel, and Adam Khay