Artificial Intelligence Theory and Applications

HOME • BIO • RESEARCH • TEACHING • BLOG

This pedagogical structure is tailored for a MIS Master’s course, MIS 811 Artificial Intelligence Theory and Applications. A 2-hour block split into a 1-hour lecture/overview and a 1-hour discussion grounded in weekly 1–2 page reflection papers is ideal for a low-stress, high-engagement Master's environment.

Navigating_Artificial_Intelligence_Overview_Infographic.png

⚠️ Rubric

Weekly_Reflection_Memo_Template.docx

Reflection_Paper_Prompt_and_Rubric.pdf

Syllabus

AI_Theory_and_Applications_Syllabus_and_Readings.pdf

This course develops conceptual AI literacy for master’s students in MIS and related backgrounds. Russell and Norvig’s Artificial Intelligence: A Modern Approach (4th ed.) supplies the technical vocabulary and historical backbone; the two weekly papers provide the intellectual “core,” pairing canonical AI/IS sources with influential organizational and contemporary research. The course is designed as a discussion seminar rather than an exam-driven survey.

Learning outcomes

Explain the principal ideas behind agents, machine learning, deep learning, transformers, generative AI, and agentic AI without advanced mathematics.
Translate AI capabilities and limitations into MIS questions about process design, decision rights, adoption, control, governance, and business value.
Critically evaluate claims about human–AI collaboration, productivity, automation, fairness, and organizational transformation using scholarly evidence.
Compare classical IS/management theories with current AI phenomena and identify where established theory remains useful or needs extension.
Formulate a defensible, evidence-based managerial or research argument about AI in organizations.

Core text and reading philosophy

Base text: Russell, S. J., & Norvig, P. Artificial Intelligence: A Modern Approach, 4th ed. The assigned chapter sections are conceptual anchors, not technical problem sets. Chapter numbers in this package follow the U.S. 4th edition; if you use the Global Edition, map by chapter/section title because the numbering differs.

Artificial Intelligence-A Modern Approach.pdf

Weekly readings are intentionally limited to two. The goal is depth of discussion rather than coverage. Students should read for the paper’s argument, evidence, conceptual model, assumptions, and managerial implications; equations and technical derivations may be skimmed unless they are essential to the argument.