Posts tagged design-at-scale
Building Great Machine Learning Experiences in Gmail

Machine learning is arguably the most important trend in technology today. From predicting what you’re going to say before you say it to fabricating lifelike videos, ML is a powerful technology.  

But designing great user experiences for machine learning -powered features presents unique challenges to a product designer: How do you create a mental model for a system with thousands of parameters? How do you explain recommendations from a system that has no rules? How do you provide user control? How do you respect user privacy expectations and tackle issues like ML fairness? 

In this talk, Paul Lambert, Product Manager @ Google discusses the challenges he and his team encountered and techniques they developed in building machine learning features in Gmail and Inbox. He has worked on Smart Compose, Smart Reply, Nudging, Priority Inbox, Highlights and other ML-powered productivity features shipped to over a billion users. 

Watch next Annika Crowley, Interaction Designer @ Google talking about Creating Great UX with Imperfect AI

Designing Effective Collaboration at Scale

Facebook has over 2 billion users who are spending a reasonable amount of time on the app, and for a company of this stage, growth and time spent aren't the biggest problems anymore. When the company scales to this stage, how do you foster a collaborative environment focused on quality and long-term goals?

In this talk, Amanda Linden, Director of Design at Facebook shares examples and lessons learned on aligning teams around what the people problems are, measuring success and performance, as well as establishing a design bug resolution process where the design org works as one to implement pattern changes across the entire app.