INFO 6940

INFO 6940

Course information provided by the Courses of Study 2020-2021. Courses of Study 2021-2022 is scheduled to publish by July 1.

Study of topics not currently covered in INFO offerings, as determined by faculty and student interest.

When Offered Fall or Spring.

View Enrollment Information

Enrollment Information
Syllabi: 1 available
  •   Regular Academic Session.  Combined with: INFO 4940

  • 3 Credits Stdnt Opt

  • Topic: Knowledge Infrastructure

  • 18227INFO 6940  SEM 101

    • TRTo Be Assigned
    • Aug 26 - Dec 7, 2021
    • Payette, S

  • Instruction Mode: In Person

Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Combined with: INFO 4940

  • 3 Credits Stdnt Opt

  • Topic: Human-AI Interaction Design Research

  • 18228INFO 6940  SEM 102

    • TRTo Be Assigned
    • Aug 26 - Dec 7, 2021
    • Yang, Q

  • Instruction Mode: In Person
    Today’s research on the promises and perils of AI is often held separate, speaking to different venues and fields of expertise. This course draws upon both threads of work and helps technologists -- UX designers and AI engineers -- to synthesize human-centered considerations mindfully as they develop and innovate novel human-AI interactions. Through wide-ranging readings, discussions, and hands-on exercises, this course will (i) introduce diverse research approaches to understand and shape data-driven algorithms’ impact on their users, (ii) help students practice connecting their own AI technical and interaction design choices with broader human implications. Students will be encouraged to collaborate with different fields of expertise (e.g. AI engineering, UX design, accessibility and fairness, social sciences) and to focus on subject domains of personal interest (e.g. healthcare, NLP, robotics, etc.) Prerequisite knowledge: Course participants should have taken one or more entry-level HCI courses (e.g. INFO3450) and have a basic understanding of AI/machine learning algorithms. For example, you should understand the difference between supervised and unsupervised learning; You should understand what F-score is and how machine learning model performances are typically evaluated broadly. There is no coding or math requirement for this course.

Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Combined with: INFO 4940

  • 3 Credits Stdnt Opt

  • Topic: Privacy and Security in the Data Economy

  • 18230INFO 6940  SEM 104

    • MWTo Be Assigned
    • Aug 26 - Dec 7, 2021
    • Cheyre Forestier, C

  • Instruction Mode: In Person

Enrollment Information
Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Stdnt Opt

  • Topic: Online Communities

  • 18231INFO 6940  SEM 105

    • MWTo Be Assigned
    • Aug 26 - Dec 7, 2021
    • Fussell, S

  • Instruction Mode: Planned for In Person

Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Choose one seminar and one studio. Combined with: COML 4281ENGL 4705INFO 4940

  • 4 Credits Stdnt Opt

  • Topic: Hum Ctred Des and Engaged Med

  • 19082INFO 6940  SEM 106

    • WTo Be Assigned
    • Aug 26 - Dec 7, 2021
    • McKenzie, J

  • Instruction Mode: Planned for In Person

  • Topic: Hum Ctred Des and Engaged Med

  • 19083INFO 6940  STU 501

    • FTo Be Assigned
    • Aug 26 - Dec 7, 2021
    • McKenzie, J

  • Instruction Mode: Planned for In Person