CS 357 - Ethics in Computing

5 CR

This course examines the ethical dimensions of computing, artificial intelligence (AI), machine learning (ML), and cybersecurity, focusing on their societal impact and implications for marginalized and vulnerable populations. Topics include algorithmic bias, data privacy, surveillance, and cybersecurity threats, with an emphasis on ethical decision-making and challenges posed by emerging technologies.

Prerequisite(s): Admission to Computer Science BS program, or permission of the program.

Course Outcomes

Apply ethical theories and frameworks to evaluate challenges in computing, artificial intelligence (AI), machine learning (ML), cybersecurity, and emerging technologies.
Assess trade-offs between competing priorities, such as security vs. privacy or innovation vs. fairness, in the design and deployment of computing systems.
Analyze complex ethical issues in AI/ML systems, such as algorithmic bias, lack of transparency, and accountability, emphasizing their effect on marginalized communities.
Evaluate ethical concerns in cybersecurity, including data privacy, surveillance, and cybersecurity threats, with particular attention to their disproportionate impact on marginalized and vulnerable populations.

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