Uli: AI Chatbot
Method Visual Design Internship
Timeline: 11 Weeks
Run by the MTA (Metropolitan Transportation Authority), the NYC subway system has a daily ridership of 4.3 million people, forming an essential part of many New Yorkers’ lives. In recent years, its performance has deteriorated with increasing rates of train delays and service breakdowns. While the subway’s technical system will take about 120 years to overhaul, much can be done in the interim to improve commuters’ perception and experience of their journey. During my summer internship with Method, Inc. in New York, I collaborated with IxD intern Zoe Gan to propose and design an AI chatbot concept as a solution for the subway’s info communication system.
User Stories / Invision Demos
The onboard flow is where Uli introduces its bot functionality, obtains basic user profiles, notification and location service permissions, as well as the user’s frequent subway lines. This process is designed to feel as streamlined and human as possible, where Uli is able to obtain core permissions and user data in a natural, conversational setting.
Janice: Good Day
Example of Nth-time user interaction when train service is good; demonstrates features such as push notifications, train condition-watch, service rating, crowdsourcing, and performance report features.
Eric: Bad Day
Example of Nth-time user interaction when train service is bad. This flow includes alternate routes, map preview, train transfer directions, and station reminder features.
Nth-time user interaction as a tourist visiting NYC for a short period of time. This flow demonstrates how Uli can surf and share subway-related content, Uli’s profile popup modal, as well as the second part of Uli’s crowdsourcing feature.