CS 1010 Introduction to Artificial Intelligence
This course has not yet been added to the catalog, but it is under development. Everything here subject to change and subject to approval, or both. That said, any queries or suggestions would be most welcome.
It will be piloted as a topics course (CS 1990) in spring of 2027, and if all goes according to plan, it will be added to the catalog for the 2027–2028 academic year.
Description
Introduces students to the practical, critical, and societal dimensions of contemporary AI, and basic AI literacy. Focuses on how people use, evaluate, and make decisions about AI systems. Students will gain practical experience working with various models; learn to select appropriate tools and models for different tasks; develop methods for evaluating and verifying AI-generated output; and examine the effects of AI use on learning, reasoning, creativity, work, and society.
Examples and readings will vary by semester and will be drawn broadly from STEM fields, social sciences, fine arts, philosophy, psychology, anthropology, sociology, economics, environmental studies, and other disciplines.
Prerequisites
None. No programming experience required.
Learning objectives
Through selected readings, lecture, discussion, active learning exercises, homework, and projects, students will be able to:
- explain in general terms how generative AI systems work (e.g., Claude, ChatGPT, others), including concepts such as training data, statistical prediction, language models, context, prompting, embeddings, uncertainty, and model limitations;
- explain significant differences between human learning and machine learning;
- understand the increasing difficulty in identifying fake, false, or misleading information;
- understanding the impact of use on human learning, reasoning, cognitive function, and lived experience;
- make informed decisions about AI use and model/tool choices;
- write effective prompts and manage context when working with AI systems and agents;
- gain practical, hands-on experience with iterative approaches, problem decomposition, adding constraints when iteracting with an AI model;
- be equipped to critically evaluate model output (e.g., independent research, source inspection, verification of calculation, experimentation, and comparison with authoritative references);
- understand power structures surrounding AI and matters of control and model alignment; and
- understand the benefits that AI can offer when used wisely; and
- engage in informed discussion in matters of AI policy and ethics and the influence AI has and will likely have on our lives.
Catamount Core designation
We will apply for Catamount Core GC2: Developing Global Citizens designation. At the completion of this course students should be able to:
- understand different philosophical approaches to moral reasoning and apply abstract moreal concepts or theories to concrete ethical problems, be they problems of personal ethics, vocational ethics, or social and political morality; and
- appreciate the moral complexity of difficult cases, and understand how different approaches to moral reasoning yield different comclusion, and anticipate objections to their own perspectives drawn from other moral points of view.
Tentative sequence of topics
- Introduction; What is generative AI? What is agentic AI?
- Infrastructure: data centers, GPUs; proprietary and open models; edge AI
- Human vs machine learning; cognitive offloading and augmentation
- Choosing a model or agent; interactions
- Critical evaluation of model or agent output
- Identifying fake, false, or misleading output
- Applying AI to problems in specific domains; “vibe” coding; product vs product
- Ethics and policy: environment; intellectual property
- Ethics and policy: stakeholders, control, and alignment; public discourse
- Ethics and policy: accessibility and equity; privacy; other topics
- AI in the arts and humanities
- AI in medicine, personal and public health
- AI in the workplace; AI as public utility
- Speculation: AGI, the singularity; conclusions and future directions, etc.
- Final project presentations