Week 6: Symbolic AI
Topics
- What is symbolic AI
- Logic programming
- Rule-based reasoning and Expert Systems
- Knowledge representation
Weekly Discussion: Knowledge Representation in Practice
Please submit all graded work via Canvas. Participation requirements and grading details are provided in Canvas.
Choose one familiar service, platform, or system and analyze how knowledge is represented within it.
Your goal is to examine how structured categories, labels, rules, and relationships shape what users can see, search, or decide.
Step 1: Choose a familiar context
Select one real-world system or environment you are familiar with. Examples include:
- A library catalog or discovery system
- A digital archive or institutional repository
- A learning management system
- A streaming platform (e.g., Netflix, Spotify)
- An e-commerce site
- A government benefits or eligibility tool
- A healthcare portal
- A knowledge base or internal documentation system
Briefly describe:
- What the system is
- What kinds of “things” it organizes (books, people, cases, products, documents, etc.)
- How users interact with it (search, browse, filter, apply, compare, etc.)
Step 2: Identify forms of knowledge representation
Look closely at how the system structures information.
You may consider:
- Are there defined categories, types, or classifications?
- Are items described using structured fields or attributes?
- Are relationships between items made explicit (e.g., author of, related to, part of, prerequisite for)?
- Are there rules that determine access, eligibility, grouping, or decision outcomes?
Explain whether you think the system is using knowledge representation, and what evidence supports your view.
Step 3: How KR shapes decisions or behavior
Reflect on how this structured representation affects what users can do.
You may address:
- What kinds of questions can the system answer easily?
- What kinds of queries or situations are harder to handle?
- How do categories or rules influence what becomes visible or invisible?
- Does the structure guide, constrain, or simplify decision-making?
Focus on how representation shapes interaction.
Step 4: Limits and boundaries
Consider the limits of this knowledge representation.
- What kinds of nuance or ambiguity are difficult to capture?
- Where might rigid categories create edge cases?
- Does the system rely more on predefined structure, or on flexible interpretation?
You do not need technical vocabulary. Focus on structural features you can observe.
Expected outcome
Your post should present a clear analysis of one familiar system, showing:
- whether it uses knowledge representation,
- how it structures entities, categories, or rules,
- and how that structure shapes user interaction or decisions.
Reading
- Knowledge Acquisition
- Tutorial - HHAI: An Introduction to Computational Argumentation
- Toulmin Argument
- What Is a Knowledge Graph?
- Knowledge Graphs in the Libraries and Digital Humanities Domain
- From Knowledge Representation to Knowledge Organization and Back
- Wikidata: The Making Of
- Symbolic artificial intelligence - Wikipedia
- Expert system - Wikipedia
- Logic programming - Wikipedia
- Logic-Based Artificial Intelligence - Stanford Encyclopedia of Philosophy (optional)