Subscribe  by sending the message "subscribe cpsc532c" to Majordomo@cs.ubc.ca.

This course explores  research on supporting Human-AI collaboration by  devising  AI-driven, human-centered interactive  systems capable of both performing useful tasks as well as  being well accepted by their users. A key aspect of this endeavour is enabling AI systems to predict and monitor relevant properties of their users (e.g., states, skills, needs) and personalize the interaction accordingly, in a manner that maximizes both task performance as well user satisfaction, abiding to principles  of transparency, interpretability, predictability and   user-control

Tackling these challenges requires an interdisciplinary effort that integrates research in different areas of Artificial Intelligence (e.g., machine learning, reasoning under uncertainty, natural language processing, planning, Explainable AI) with research in Human  Computer Interaction, and  Cognitive Science. During the course we will explore representative work in this field, spanning the above disciplines

Discussion on the assigned readings will be the main activity in the course. To provide good ground for the discussion, participants must

• send   at least N questions and a brief summary as specified on the course readings page 

  • Details on which material to send for each class  will be posted on the course readings page. 

  • Questions for a given class should be posted in the Piazza folder labelled with the date for that class

  • Summaries are to be uploaded in Canvas

• The readings page will also specificy the deadlines for sending the material for each paper

  • Material sent after the deadline will be marked as zero. However

  • Each student has 2 "no paper" bonuses:  can avoid  sending the material for 2 papers with no penalty.

• Clarification questions are welcome. However, in addition there should be  at least N  questions on each paper  that do one or more of the following:

  • identity and discuss weaknesses in the presented research

  • relate the research to general issues in the field

  • make connections/comparisons with other readings

  • propose alternative approaches/solutions

  here are  some sample questions

•  Each paper summary must follow this summary template and be no more than 2 pages long. As shown in the summary emplate, the summary should address the following points, described in more details here

  • What are motivations for this work?
  • What is the proposed solution?
  • Has the proposed solution been evaluated, and if so how ?
  • What are the contributions of this work?

Beside improving  participation to the discussion, the objective of these activities  is to help participants learn how to read papers with a critical eye, as a reviewer for a conference or journal would do.

• Participants will  be expected to complete a course project. The project will be decided in consultation with the instructor and will typically involve implementing a simple example of AI-driven persnalization

• Projects can be done in teams

• Each student/team  is  expected to set up individual meetings with the instructor to discuss project options. The earlier this is done, the easier it will be  to come up with a suitable proposal, but plan to schedule at least one meeting before  the date that will be given soon

• The project will include the following stages:

• a project proposal (max. 3 pages in the following format)

• a  presentation on project progress

• a presentation on the complete project and submission of  written report (max. 20 pages using  the same format as above) 

 

For a team project,  the proposal must clearly define  the contribution of  each group member. Each group member must present his/her contribution during project presentations

• GUIDELINES for selecting a  project

• proposal (written + presentation) 20%
• final presentation 20%
• report 60%