Course Instructor Class Time
Class Location Online Discussion Anthony’s Office Office Hours Teaching Assistant

Xiang ‘Anthony’ Chen ([email protected]) Winter 2022, Monday/Wednesday, 4:00-5:50 PM PST WGYOUNG 4216 / Zoom link BruinLearn Boelter Hall 6730A or Zoom Tentatively, MW 3-4 PM PST (Send me a calendar invite if you’d like to chat!) Ruolin (Violynne) Wang ([email protected], Zoom)

Quick Links

• Literature review sign-up sheet
• Project team sign-up sheet

Course Objectives

• Introducing you to the fundamentals of HCI: what is HCI, the history, how to design and evaluate an interactive system, how to prototype, input/output devices and techniques;
• A specific focus on Human-AI Interaction: how to make AI comprehensible to humans, how to enable humans to control AI, and how to enable human-AI collaboration.

Prerequisites

• You should have already taken at least one programming course (e.g., C, C++, Java);
• For implementing interactive systems, you are free to use whatever programming languages, frameworks, libraries or toolkits;
• If you are unclear what to use for implementation, the default option is HTML/JavaScript, in which case you are required to take the following online tutorials before the quarter begins:
  • HTML/CSS: https://www.youtube.com/watch?v=UB1O30fR-EE (~1 hour)
  • JavaScript: https://www.codecademy.com/learn/introduction-to-javascript (~2 days)
  • jQuery: https://www.udacity.com/course/intro-to-jquery--ud245 (~2 days)
• Since a specific focus is on Human-Centered AI, it will be beneficial (though not strictly required) for you to get familiar with programming intelligent systems, by learning/using one or more of the following:
  • Weka: https://www.cs.waikato.ac.nz/ml/weka/
  • scikit-Learn: https://scikit-learn.org/
  • TensorFlow (Python or JavaScript)
  • PyTorch: https://pytorch.org/tutorials/

Schedule

All deadlines are due at 11:59 PM on the dates

Grading

• Course project (50%):
  • Phase 1: low-fi prototype (5%) and think-aloud report slide (5%);
  • Phase 2: minimum viable product prototype (15%), evaluated by
    • Completeness (5%): does it have all the required pieces? Full (5%), partial (3%), none (1%)
    • Quality ****(5%): does it work usably/robustly/creatively? Good (5%), fair (3%), poor (1%)
    • Clarity (5%): can you clearly present your product and describe your approach? Good (5%), fair (3%), poor (1%)
  • Phase 3: adding an intelligent feature (10%)—50% instructor & 50% peer graded;
    • Motivation (2%): is this feature motivated by a well-defined user-centered problem?
    • Usefulness (2%): does this feature provide useful functionalities for the user?
    • Usability (2%): is this feature usable (has very few usability problems)?
    • Innovativeness (2%): is this feature innovative compared to existing note-taking apps?
    • Robustness (2%): is this feature working robustly?
  • Phase 4: adding/changing a feature to be human-AI interaction (15%)
• Literature review (30%):
  • Each student will sign up to read and present two papers (each paper has two student presenters)
  • Each presentation will be in class for about 15-20 minutes + Q&A;
  • For your own papers:
    • An in-class presentation (10%), evaluated along these dimensions: soundness, sufficient details, use of visuals, use of examples, fluidity, engagement, and clarity;
    • Posting summary + discussion topics online before class and moderating discussion (5%)
    • Moderating in-class discussion (5%);
  • For others' papers:
    • Participating in online or in-class discussion (10%);
• Giving feedback (11%):
  • Grading and giving feedback during Phase 2-4 demos (3% x 3 = 9%)
  • Mid-term feedback (1%) extra
  • Final teaching evaluation (1%) extra
• Pop quizzes (10%):
  • There will be two quizzes following some lectures;

Please also read detailed requirements below.