Here are some interesting finds on UI/UX of the week!
Designing for Human Error. Interesting article from the WebDesignerDepot, focused on relevant features to consider, particularly when designing products where human error is always a consideration (and as a reminder, it’s important to consider when designing products, all states should be contemplated, from the ideal, partial, blank, loading and error states). Highlight of the article includes:
“Form validation, while imperfect, is a powerful thing, and a great way to gently guide the user in the right direction. While proper form design can help keep users from simply putting the wrong text in the wrong form, form validation is great for double-checking information, and catching typos and forgotten fields.”
Emotional and Anticipatory Design in UX. Great read. This article focuses on the concepts of anticipatory and emotional design, and how these influence how product experiences are conceived. This is particularly relevant as AI and even Natural Language Processing comes into play, when users are going through the flow of a product to actually perform a task or purchase an item. Highlight of the article includes:
“Until they have incredibly sophisticated predictive algorithms, fully developed AI constantly monitoring millions of data points, and machine learning, businesses can mine existing data for anticipatory design opportunities, thereby reducing potential pain points and barriers. Deeper user research will also tell us a lot — contextual observation, perhaps, or ethnographic studies — where we could observe what users are inclined to do in their flow from moment to moment. We could map these user journeys step by step and design the interaction accordingly. The ideal outcome of applying such data mining and personalization, coupled with user-centered design methods, would create fluid and seamless anticipatory experiences that would please customers and generate loyalty by having the right things appear at the right time for them to interact with… as if by magic.”
The UX of AI. Impeccable article hailing from Google, which details how UX will have a profound effect on how AI and Machine Learning will be rendered more effectively. If a lot of what guides some of these technologies relies on pattern recognition and behavior grasping, how the experiences are conceived and outlined, is more important than ever. Highlight:
“In order to thrive, machine learning must become multi-disciplinary. It’s as much–if not more so — a social systems challenge as it’s a technical one. Machine learning is the science of making predictions based on patterns and relationships that’ve been automatically discovered in data. The job of an ML model is to figure out just how wrong it can be about the importance of those patterns in order to be as right as possible as often as possible. But it doesn’t perform this task alone. 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. Suffice to say, the UX axiom “you are not the user” is more important than ever.”