The average amount of remotely conscious decisions an adult makes per day is 35,000.
In today’s hectic lifestyle, making choices became much more overwhelming. More and more people, including powerful entrepreneurs and politicians, are adopting what is called the Decision-Making Diet.
It is clear that the internet changed our lives for the better, I can order pizza at 11 pm from the comfort of my home and I can plan my trip to a country I have never been to at the last minute and manage not to get lost once there. But the internet has also done a terrible job at reducing the cognitive load and the mental fatigue that comes with it. It is exposing us to an abundance of information and decisions to make.
To the point that Decision Fatigue is becoming more and more of a serious issue and I can say that 99% of my surroundings are suffering from it, including myself.
I remember my mother always telling me to go to the doctors first thing in the morning, because they’re fresh out of a good night sleep, therefore better at making a good diagnosis. I used to find this a little too much, but I have come to realize that she is right. The irony with Decision Fatigue is that not only does it damage the overall health and quality of life on the long run, but it also damages the decision making in itself. The more choices we make in a certain amount of time the less effective we become at it.
Now imagine an app that syncs with your schedule to call a cab for you so that once you are out of work or the airport it’s already there waiting, coffee shop lights that adapt to the outside natural lights so that when it’s gloomy by day they increase the brightness inside, or a playlist that syncs with your day plans and suggests songs according to your mood at a certain time of day.
A design that anticipates my behavior and spares me deciding of every single step of the process? Sign us in! If you ask me what’s the next major Design trend and breakthrough I’d totally reply “Predictive Design” without any hesitation. It is now needed more than anytime before. And soon enough, brands will compete based on how well automated their services are rather than how beautiful their platforms are (not that it doesn’t count)!
The concept was first introduced as a new breath for design thinking by Huge CEO Aaron Shapiro. Predictive design is simply when decisions are made and executed on behalf of the user. The goal is not to help the user make a decision based on a step-by-step interaction (the current UX Design trend), but to create an ecosystem where a decision is automatically taken without requiring the user’s attention (the future).
One step ahead!
While researches are still conducted on predicting users actions and fully automating them, there are some existing semi-predictive designs that just seem to anticipate user needs: Netflix recommends shows and movies based on your prior views, Spotify creates playlists for you based on past likes, Mealime suggests meals and shopping lists based on your family size and preferences.
The IoT market, however, seems to know a more advanced behavior-anticipating devices. One predictive design veteran is Google’s Nest: the smart thermostat, like any other digital assistant, responds to user’s requests but in addition to that, it predicts their preferences and actions and executes them without any need for the user. Based on prior user’s choices, Nest automatically adjusts room temperature according to a certain time of day. Other good examples are Amazon’s Echo, Alexa, Siri and Cortana.
Data Privacy and “Filter Bubble”
However, for the system to be predictive, it needs to learn and adjust on given user’s actions and behavioral patterns from the past.
“Anticipatory Design is a design pattern that moves around learning (Internet of Things), predicting (Machine Learning) and anticipation (UX Design),” says Joël van Bodegraven.
The problem with this is that one wonders, to what extent can a user let go of private information for a system to anticipate their behavior. While a lot of confidentiality is involved, UX designers can find themselves challenged by the ethical side of Predictive Design.
Another aspect that needs to be taken into consideration is what we call the “Experience Bubble” or “Filter Bubble”. I have already experienced this by using the suggested playlists, I realized after a while that I was stuck in some kind of loop of the same music genres, sometimes repeating in a brain-washing style the same songs over and over. This becomes an issue when the predictive system ends up shaping the user’s preferences instead of only using them for reference. Wikipedia defines Filter Bubble as follows:
“A state of intellectual isolation that can result from personalized searches when a website algorithm selectively guesses what information a user would like to see based on information about the user, such as location, past click-behavior and search history.”
The first goal when designing these types of system is allowing the user to make as few choices as possible in a way that they would appreciate. A simplified, clutter-free interface with just the right amount of information is, therefore, mandatory.
You also want to present a smooth experience where options are already decided for the user but in a way that doesn’t feel pushy. If the suggesting elements seem too informed, that can creep out the users and turn them off. You must balance usability and user privacy wants.
It all goes to making the user’s life easier and decreasing that cognitive load but this shouldn’t go the extent of stripping them away of their curiosity and wonder. Designers still must think about presenting the users with the broad options they have even if the platform’s aim is to anticipate. But anticipation doesn’t mean control.
It is up to today’s designers to define the standards for what tomorrow’s users will expect from their interfaces. And as the designer, you should find just the right middle ground to make all this come together for your users.
Challenge accepted !
With the users appreciating more their time and energy more than ever before, there is no doubt that fully- autonomous machine learning-based designs will grow in popularity in the upcoming years.
Although there is still room for improvement, the UX Design sphere is filled with talented people who love to solve user-related bumps. And I believe that, like always, they will not only be up to the challenge but take this concept even a step further. Maybe anticipate users needs that they wouldn’t even think of themselves?
If this topic interests you, you can join the movement and share your thoughts about Predictive UX and Anticipatory Design at Anticipatory Design.
Further reading suggestion: Anticipated Travel Experiences.