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Week 2: AI for Search, Discovery, and Recommendation

Topics

AI for Search, Discovery, and Recommendation

  • How AI Enhances Information Retrieval
  • Vocabulary bridging across domains
  • Pattern-based recommendation

Key Takeaways for This Week

  • AI supports content understanding by converting unstructured materials (scanned pages, images, PDFs) into machine-readable text and basic document structure, enabling downstream tasks such as indexing, metadata enrichment, and search.
  • AI-based indexing and metadata enrichment support discovery in large and evolving collections where manual description is limited or inconsistent.
  • AI-enhanced search allows users to ask questions in natural language and supports exploratory searching through interaction and follow-up.
  • Vocabulary bridging helps users find relevant information even when their wording does not match professional or disciplinary terms.
  • Recommendation systems support discovery by surfacing related materials based on learned patterns rather than explicit user queries.

Weekly Discussion

Please submit all graded work via Canvas.
Participation requirements and grading details are provided in Canvas.

Before You Post

Before writing your discussion post, please do the following:

  1. Choose one information system you regularly use
    (e.g., Google, Google Scholar, a library catalog or discovery system, Netflix, Spotify).

  2. Choose one topic or interest, and interact with the system multiple times.

  3. As you interact, simply notice and describe:

  4. What appears first
  5. Whether the system shows summaries, recommendations, or suggested follow-up options
  6. Whether different searches or actions seem to change what you see

You are not expected to explain how the system works internally.
The goal of this activity is to help you reflect on your experience as a user.

This preparation is intended to support your participation in the discussion below.

Discussion - AI for Discovery: How Systems Shape What We Find

Consider how you usually search for information: on Google, your library catalog, or a streaming platform like Netflix or Spotify.

In your original post (approx. 100–300 words), address the following:

  • What do you think determines what you see first in search or recommendation systems?
  • Have you noticed differences in how fair or transparent these systems feel?
  • Share an example where a search or recommendation system surprised you, for better or worse.

Draw on your own system observation from this week where appropriate.
You are not expected to explain technical algorithms. Focus on your experience, observations, and reflections as a user.

Reading materials: