Early Graphical User Interfaces (GUI’s) often took cues from real world objects to help users ride the learning curve associated with using computers. Psuedorealistic knobs, dials, switches and sliders. It was all they knew at the time, but it was enough to help ease the transition from physical interaction to digital. This design concept was known as Skeuomorphism, drawing on tangible objects to create intuitive software interfaces.
As with everything, GUI’s have started to evolve, albeit after a lengthy period of stagnation (ponder this: the concept of the Microsoft Windows ‘Start’ button has remained virtually unchanged since 1992). Users are now able to pick up devices and navigate interfaces without such visual cues as raised buttons, drop shadows and brushed aluminium textures. Personally, I feel there is still some benefit to be gleaned from textures in design (more on that another day), but, such is the nature of technology, it evolves and improves as we understand it better and the ways which people interact with it.
Another era of evolution is happening in the Artificial Intelligence (AI) space. Technology is advancing enough that we can make meaningful improvements to people’s lives with machine learning and smarter user experiences. The responsibility is now on designers and developers to ensure their applications do a lot of the ‘heavy lifting’ for our users. Where possible, we must be able to anticipate their needs before they even know what they want themselves.
The responsibility is now on designers and developers to ensure their applications do a lot of the ‘heavy lifting’ for our users.
Of course this is not a new way of thinking. We should look once again to the real world for inspiration just as we did in the early days of the GUI. To create genuinely impressive machine to human interaction we should look firstly to human → human interaction for our learnings. One such approach which is gaining traction amongst designers is the Japanese art of selfless hospitality and proper etiquette; ‘Omotenashi’.
Omotenashi / Montenashi (roughly translated to mean ‘single hearted’) is a cornerstone of Japanese culture. It describes the ideal guest → host relationship. It laid out the rules for successful dinner parties and permeated throughout the service industry in the country, with hotels, restaurants and retail stores practicing Omotenashi. To be able to welcome someone into your home or establishment and anticipate their every need is seen as a privilege for the host, and working in a service industry is regarded with the utmost respect. There are no menial tasks if the end result produces a great experience for your guest (customer, or user).
Charles Eames once remarked that:
“the role of the architect, or the designer, is that of a very good, thoughtful host, all of whose energy goes into trying to anticipate the needs of his guests.”
What can we learn from this and how can we apply it to design in the modern world?
Around 2009, an interaction designer working for Panasonic in Yokohama, named Kerstin Blanchy — who was inspired by Omotenashi — published an analysis on these guidelines for human-to-human interactions and how this art of careful etiquette and attunement to one’s guests needs could potentially be used to improve machine-to-human experiences. She boiled the concept down to three “principles of attitude”:
Anticipation of the other’s needs: The host should respond to guest’s needs before the latter feels such need himself.
Flexibility to the situation: Refers to the appropriate amount of formality or casualness respectively.
Understatement: The host should not display his efforts, in order to create a natural feeling for the guest.
There are ways you can implement these principles without going too far.
— Recommend products or content based on my browsing history.
— Ensure that my frequently performed actions are accessible faster.
— If I choose to dismiss a certain type of content, try to take that cue and show me less of it.
— If I am performing a certain action for the first time, be aware of where I’m stalling and prompt me if needed.
A fine line exists between smart user experiences and uncomfortable ones, however.
When AI becomes too familiar.
Blanchy herself gives a vivid example of when machine learning can be a little intrusive, and sometimes downright creepy. “I had gotten a new job in the suburbs of Paris and to get there I had to buy a car,” she says. “After one week in traffic jams, I started using Waze [an app to help navigate around traffic]. So you get in the car, launch the App, choose the destination and it says: ‘Let’s go, drive safe!’ Quite motenashi, don’t you agree?
“Then one day,” she continues, “I finish work, get in the car, launch the App and it directly asks: ‘Going home?’ Wow, that scared me. I shut down my phone and thought about how the App can know that I was going home. It’s no great mystery. Yet I felt exposed, vulnerable, somehow observed. For a few days I did not use the App.”
Wow, that scared me. I shut down my phone and thought about how the App can know that I was going home…I felt exposed, vulenerable and somehow observed.
This smart interaction totally creeped Blanchy out precisely because the app was treating her as a casual “regular” when that “rapport” hadn’t been established yet. Sure, she got over it and now considers this kind of behaviour to be convenient. “However, I do not really want interfaces to know me too well,” she admits.
Software will one day be our friend, sort of like the movie Terminator 2. An all-knowing, all-protecting, robotic ally. But for now, it’s probably better when it treats us as its guest.