Course Overview
This course introduces first-year students to generative AI: what it is, how it works, and how to use it responsibly in academic and professional life. Students begin by situating generative AI within the broader landscape of AI types, including agentic, predictive, and rule-based systems, before focusing on the tools they are most likely to encounter. Through a hybrid mix of synchronous sessions and guided online learning, students build foundational knowledge of generative AI capabilities, limitations, ethics, and governance. The course is paced to allow genuine understanding rather than surface familiarity. Students leave with a clear, working knowledge of responsible generative AI use and the confidence to act on it.
Prerequisite(s)
- No prerequisites are required for this course.
Credits
1.5
- Not offered this term
- This course is not offered this term. Notify me to receive email notifications when the course opens for registration next term.
Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Distinguish between different types of AI systems, including generative, agentic, predictive, and rule-based AI, and describe the primary characteristics of each.
- Define key concepts related to how generative AI systems work, including common limitations, risks, and failure modes.
- Describe the ethical considerations associated with generative AI use in academic and professional contexts, including bias, privacy, and accountability.
- Explain the role of AI governance at the institutional, regulatory, and personal level.
- Recognize when generative AI use aligns or conflicts with institutional policies and professional standards in their program context.
- Define academic integrity and explain how it applies to the use of generative AI in assessed work.
- Identify behaviours that constitute academic misconduct, using BCIT's academic integrity policy as a reference.
- Describe how to use generative AI in ways that are consistent with academic integrity expectations in their program.
- Apply guidelines for responsible generative AI use to straightforward academic and workplace scenarios.
- Demonstrate basic critical literacy when reviewing generative AI outputs, including identifying obvious errors or limitations.
- Identify commonly used generative AI tools and describe their key characteristics and apprpriate use cases.
- Distinguish between types of data (public, private, confidential, and restricted) and explain the implications for responsible generative AI use.
- Apply basic prompting strategies to generate relevant and appropriate outputs in academic contexts.
Effective as of Fall 2026
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AI, Integrity, and You: A Foundation for Academic and Professional Life (BSYS 1100) is offered as a part of the following programs:
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