DATA PRIVACY AND ETHICS

Course Description

This course explores the many ethical dilemmas that arise in the contemporary practice of data science and creates a framework for comprehending these concerns. The impact of unethical behavior and how data are used ethically in society will be covered. The Findable, Accessible, Interoperable, and Reusable (FAIR) data principles are described. By the end of the course, students will be able to recognize and carefully differentiate between problems unique to data science and those that arise as a result of using other related computational methods of analysis, such as machine learning and artificial intelligence. They will also be able to distinguish between ethical misconduct unique to data science methods and those that may result from the contexts in which these methods are used.

DATA PRIVACY AND ETHICS

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

No course outcomes have been defined yet.

Course Syllabus

Reference Books & Course Materials

1. 01 Loukides, M., Mason, H., & Patil, D. J. (2018). Ethics and data science. " O'Reilly Media, Inc.".
2. 02 Payton, T., & Claypoole, T. (2023). Privacy in the age of Big data: Recognizing threats, defending your rights, and protecting your family. Rowman & Littlefield Publishers.
3. 03 Slussareff, M. (2022). O'Neil, Cathy. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown.
4. 04 Kearns, M., & Roth, A. (2019). The ethical algorithm: The science of socially aware algorithm design. Oxford University Press.

Learning Outcomes

1. L01 Explain fundamental ethical concepts, principles, and frameworks relevant to computing, data science, and emerging technologies. SOLO 2
2. L02 Apply ethical frameworks and professional codes to ethical dilemmas in computing and data-related practices. SOLO 3
3. L03 Analyze ethical issues related to artificial intelligence, big data, predictive analytics, social media, virtual/augmented reality, and generative AI. SOLO 3
4. L04 Evaluate the ethical implications of data collection, processing, sharing, and use with respect to privacy, fairness, transparency, consent, and accountability. SOLO 4
5. L05 Assess the ethical and legal responsibilities associated with intellectual property, software risks, professional practice, and data protection. SOLO 4
6. L06 Design ethically responsible approaches to data and technology use that incorporate privacy protection, bias mitigation, security, and principles such as FAIR data. SOLO 4

Program Outcomes

1. P01 Be able to understand and apply security protocol and tools to security challenges faced in organizations
2. P02 Be able to design security software to combat security issues
3. P03 Be able to identify, categorize, and develop security solutions for computer orientated challenges.
4. P04 Be able to demonstrate autonomy and responsibility in managing computer security projects
5. P05 Be able to follow the state of the arts concepts in computer technology security
6. P06 Be able to design, implement, and evaluate a computational system to meet desired security needs within realistic constraints
7. P07 Be able to use appropriate security techniques, protocols, skills, and tools necessary for securing computer systems
8. P08 Be able to apply effective communication skills consistent with the professional environment
9. P09 Be able to apply effective collaboration skills in teamwork consistent with the professional environment
10. P10 Be able to apply appropriate security technology and techniques to facilitate a safe operation in an organization

Po-Lo Matrix