How Can ML Help Knowledge Workers to Efficiently Enter Their Workflow?
Master of Graphic Design (MGXD) students collaborated with the Laboratory of Analytic Sciences (LAS) here at NC State to explore the potential of a Tailored Daily Report (TLDR)—an intelligent, interactive interface that might assist intelligence analysts as they begin their day.
Students moved through a human-centered research process to determine current analyst needs and opportunities and then prototyped interfaces exploring the potential of ML to assist analysts in a variety of scenarios, from a critical hostage situation to a language analyst assisting with ongoing diplomatic efforts.
This research is part of a larger initiative led by LAS, the Summer Conference on Applied Data Science (SCADS). This conference presents a multi-year challenge: to develop and optimize a TDLR for thousands of individual needs and interests. The project brings together expertise from academia, industry, and government in order to collaboratively address this data science challenge.
MGD students will share their prototypes during the initial conference to inspire possible features for the TLDRs created by SCADs participants.
The core research question of the project:
How might the design of an interface use the affordances of machine learning to provide a personalized user experience (ML) so that the analyst might quickly and knowledgeably enter the day’s workflow?
Designers: Amanda Williams, Liz Chen, Riley Walman. ©NCSU MGD, College of Design
Designers: Elizabeth Gabriel, Brian Sekelsky, Jillian Swaim. ©NCSU MGD, College of Design
Designers: Katie Denson, Jeff Wilkinson, Jacob Williams. ©NCSU MGD, College of Design