Gavin Lew

As UX researchers, we are asked tocapture experiencesand the method can vary tremendously and sample size as well. Since this course provides some of thescience behind UX, I ask that you post your project(s) so we can have a sense for the diversity of applications for UX research and accompanying same size. The best way for us to be great researchers is to have confidence in what we do and learn from each other.

By Robert M. Schumacher and Gavin Lew November 4, 2019 AI systems always need training data to ensure their algorithms produce the right outcomes. Such data can frequently be hard to come by. For machine-learning (ML) scientists to train artificial intelligence (AI) systems and algorithms, they need data. They collect many of the datasets they use to build AI systems from human behaviors and people’s interactions with the technology they use in their everyday lives.

Mobile Matters Mobile Dark Patterns A column by Steven Hoober In addition to the misuse, misunderstanding, and bad implementations of perfectly good UX design patterns, we’ve long understood the concept of anti-patterns. These are things that we know don’t work well for users. We’ve clearly defined and documented them so we can avoid using them.