Accessibility + IBM Watson?

What’s machine learning and what can designers do with it? The NCSU 1st year Masters of Graphic Design Studio took on just this question over the course of the semester. We began with a series of conversational interface studies, moved on to a Future Artifact workshop with the amazing Krissi Xenakis, and, then, capped off the semester with a 6-week collaboration with IBM’s Watson Health team.

Over the course of this project, the grad students investigated how machine learning might lower barriers to accessibility for blind, visually impaired (BVI) and deaf, hard-of-hearing (DHH) users.

Group of students and team members from IBM Watson

Scenario Videos of Student Work

NICO Project

Designers: Ellis Anderson, Alysa Buchanan, Matt Babb

Here-U Project

Designers: Shadrick Addy, Jessye Holmgren-Sidell, Matt Lemmond, Krithika Sathyamurthy

The Research Process

Matrix, both digital and physical, correlating Watson Products, disabilities, and a specific barriers


Benchmarking and User Interviews


Examples of personas and scenarios from the project


Ideation exercises: What If exercise


Sketches from the project


Rough interface designs


Storyboards of initial concepts


Photos from critiques with IBM in the NCSU studio


Photos from User Testing phase


Examples of "To Be" user journey maps


Examples of hi-fi prototypes


Photos of still frames from scenario video rough cuts.


The Design Process:


  1. Matrix Exercise: mapping Watson tools to problematic tasks for DHH and BVI users
  2. Benchmarking and User Interviews
  3. Personas and Scenarios
  4. User Journey Map of current user experience
  5. Ideation: What If Exercise to explore possibilities improv style
  6. Sketches
  7. Roughs
  8. Storyboard of User Experience
  9. Crits with IBM
  10. User Testing
  11. Revised User Journey Maps
  12. Hi-fi Prototypes
  13. Scenario Videos and Final Presentations