DAT 115 - Ethics of Machine Learning, Experimental
Credits: 3
3 Lecture Hours
Description
Students will be introduced to ethical models and the impact of Machine Learning on the evolution of society and cultures. In this course students examine and determine Machine Learning practices and how the human-computer interactive elements work together to make ethical deicisions. This will prepare students to develop and implement Machine Learning in an ethical manner in their own careers. Futher, students in this course will gain an understanding of different forms ethical considerations can take in different disciplines.
Learning Outcomes
Upon successful completion of the course, the student will:
- Compare and contrast ethics and morales.
- Analyzie application of machine learning in interdisciplinary environments.
- Explain algorithmic biases.
- Implement ethical decision models for machine accountability.
- Assess cultural implications of machine learning.
- Produce case studies that analyze current machine learning issues.
Listed Topics
- Ethical models
- Comparing ethics and morales
- Cultural implementations on societal perceptions of Artifical Intelligence
- Fairness and Human Computer Interactions (HCI)
- Interpretability across disciplnes
- Algorithms and Social Impact
- Machine mind and identity
Reference Materials
Instructor approved textbooks and materials.
Students who successfully complete this course acquire general knowledge, skills and abilities that align with CCAC’s definition of an educated person. Specifically, this course fulfills these General Education Goals: - Critical Thinking and Problem Solving
- Culture Society and Citizenship
- Information Literacy
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