Published on February 11th, 2019 | by Emergent Enterprise0
UI + AI: Combine UX Design with Machine Learning to Build Smarter Products
In the adoption of new technology, great oversights can happen if all the team members on the project are not communicating. Jarno M. Koponen at venturebeat.com reveals ways to avoid those oversights in the world of machine learning by prioritizing a good user experience. When the AI/ML developers are speaking the same language and sharing common goals with the UX/UI designers good things happen: happy users.
Machine intelligence doesn’t automatically lead to smarter user experience if product designers and machine learning experts don’t talk the same language.
The language and concepts of machine learning are far from intuitive. And user experience design requires an understanding of how people think and behave, simultaneously taking into account the irrationality of human behavior and the messiness of everyday life.
Because of the different skills these two disciplines require, it’s normal to see user experience designers and machine learning experts work in their own separate silos even though they’re building the same product. Often, experts from both fields are not familiar with each other’s methods and tools and so are unable to grasp what can be achieved by combining experience design with machine learning. To break these professional silos, the product team needs to make a steadfast and conscious effort, but how to get started?
Here are four pivotal principles for finding an efficient and fruitful way to combine the best product design methods with the pragmatic applications of machine learning:
1. Develop a shared language
The product vision, essential user experience issues, and business goals need to be shared and understood by the whole team. You can create an intelligent, truly meaningful user experience only if product design and machine learning development methods feed each other through common language and shared concepts.
User experience designers and machine learning experts should join forces to create a common product development blueprint that includes user interfaces and data pipelines. The co-created product blueprint grounds your team’s product planning and decisions concretely to the reality of user experience: how every design decision and machine learning solution affects how the user experiences the product. A great catalyst for cross-pollination of product goals, design ideas, and machine learning concepts is to get the experts on both fields to work in the same space side-by-side.