UXPA Boston 2018 Conference Recap
I attended UXPA Boston 2018, a one-day conference hosted at the Sheraton Boston. This was a highly anticipated event for me as it was my first year attending despite being interested in previous years. What’s more, this year’s conference happened to land on my birthday, so it was a real treat to break from the day-to-day routine!
I was especially looking forward to sessions by UXers from notable companies like LogMeIn, Google, and IBM on the topics of user research workshops, collaboration and the future of UX.
Attendees of this conference ranged from content writers, product managers to marketing professionals and beyond. I chatted with folks there, and it was interesting to learn how people in different roles and companies prioritized different topics.
Purpose Before Action – Why you need a Design Language System
Designers from IBM opened this session by outlining the definitions and benefits of using a design system. They posed a question that designers often ask at the start of a design system project, “Should I use someone else’s system or create a new one?” The answer largely depends on whether or not you need to fit into an existing ecosystem and what resources you have available.
Learn more about why we use design systems and how they can benefit a product.
The design team at IBM described the challenges they faced in creating a design system with a distributed team to serve an even more widely distributed company. They used the digital collaboration tool Mural (see more below) to in conjunction with design thinking to help the team to work collaboratively across various cities. One of the key lessons the team learned from IBM’s design system project was to code as you go for an immediate feedback loop between designers and developers. Doing so allows developers across all projects to use the code as it’s completed to minimize technical debt.
Drawing Insights: Bringing Co-Creation to an Enterprise Context
The design team from LogMeIn discussed their method of co-creation with users and stakeholders. At LogMeIn, co-creation sessions allow the team to evangelize customer empathy among the stakeholders, add structure to blue sky scenarios, and break cross-functional silos. In their typical 2-hour session, a handful of team members are in the room with one user. Everything is video recorded while all other team members observe from another location. During the session, the designers and user co-design artifacts and visual representations of the user’s thoughts as they relate to the project at hand.
Digital Whiteboarding and Other Techniques for Remote Collaboration and Ideation
IBM’s Design team held a session focusing on Mural, the tool they use for digital whiteboarding with distributed teams. They leverage Mural for group exercises like brainstorming, emotional matrix, empathy mapping, feature grouping, and prioritization. Project teams leveraging Mural can diverge during wireframe and moodboard phases and converge for reviews and critiques.
IBM has found it ideal to couple Mural with a phone conference for exercises with teams of 8-12 people. Technically it can be used for exercises with 50+ people, but IBM stated that they would not recommend it. I can’t imagine what could have gone wrong!
Participatory Paradigm Shifts: Workshop Methods to Design Innovative Products and Services
Lisa Otto from EchoUser discussed practical workshop methods for exploring user needs and potential solutions where there are no existing paradigms. Typical research methods ask users about the current state of a product and what features they would like to use. Users tend to default to concepts they are familiar with so Lisa focuses on extracting user values through explorative exercises like Scenario Framing, Wicked Solution Mapping, 2×2 Futures Matrix, and Extreme Profile Cards. These exercises guide the users as they move from a concrete solution space (where am I now and where do we want to be?) to an abstract problem space (what challenges might arise and how do we get to our solution?).
Learning Machine Learning: Implications for Design and UX
Mahima Pushkarna is a Visual Designer on Google Brain’s People and AI Research (PAIR) team and her talk on ML and UX piqued my interest. She explained the core concepts of machine learning but even such an introductory talk became very dense, very quickly. When she reached the cornerstone of her presentation, I expected to learn about downstream design considerations of ML, but I was surprised to hear her flip that concept on its head. Mahima focused on the idea that “Machine Learning Problems are Design Problems”. That is to say, for machines to perform well, you must design the model correctly and be purposeful in choosing the inputs for it.
That’s a generalized explanation of Mahima’s point, so here’s a more detailed version from the Brain Team at Google:
“Machine learning is the science of making predictions based on patterns and relationships that have been automatically discovered in data… Every facet of ML is fueled and mediated by human judgement; from the idea to develop a model in the first place, to the sources of data chosen to train from, to the sample data itself and the methods and labels used to describe it, all the way to the success criteria for the aforementioned wrongness and rightness.” Josh Lovejoy, The UX of AI, Google PAIR
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