Have you ever thought about how the web would look like if we could anticipate user needs? The idea to personalize user experience and serve different content to different people based on their interests has lately appeared in the discussions about web design.
The new approach is called anticipatory design, or sometimes context design, and takes experience design to the next level. It anticipates what customers need before the specific need even pops up in their mind, and customizes the content accordingly.
When I heard about the new concept for the first time, I was fascinated, and eager to learn more about it, as it seemed to be an awesome idea. As I’ve read and thought more and more about it, I’ve begun to understand the concerns as well, and my initial enthusiasm has started to turn into skepticism.
Read more: Why Experience Design is the next big thing
Since then my views on anticipatory design have been back and forth between optimism and pessimism. In this post I will demonstrate the opportunities and risks the new approach can bring into the field of design, so you can take your own stance on this yet controversial subject as well.
While reading, please keep in mind, that anticipatory design still takes its baby steps, its rules are not final yet, and still can change in the future a little or a lot.
The term of anticipatory design was coined less than a year ago by Aaron Shapiro in a brilliant post on FastCoDesign. The article claimed that designers tend to give too many choices to users, which distracts them, and makes user experience stressful.
In turn, this leads to poor quality decisions and less satisfied users. The recommended solution for this problem is a new approach called anticipatory design.
In anticipatory design the designer’s job is to create an environment that eliminates as many step-by-step interaction as possible, and to simplify processes. This means people won’t have to run through tons of options in each app they use. Instead, smart algorithms will make most, if possible, all decisions for them.
This smart decision making process will be possible by making use of:
How would fully fledged anticipatory design look like? Let’s imagine the following scenario.
You leave from work, and drive home as usual. By the time you arrive, the ingredients of the dish you talked about with your spouse earlier that day are already delivered to your front door.
During the process there was no need for you to make any decisions. Based on the current traffic data and the distance between your office and your house, an app calculates the time you need to get home; another app downloads the recipe of said dish, orders the ingredients from your local supermarket, and informs them about the time of your arrival.
Sounds more like a dream than real life, doesn’t it?
Okay, maybe anticipatory design is not this advanced yet, but its early implementations are already in the market.
Amazon’s recommendation engine uses machine learning algorithms and big data technology to predict what you need, based on your past searches, ratings, comments, and other online actions.
Amazon’s new hardware, the Dash Button is also a great example of already existing anticipatory design. It’s a tiny plastic button that was invented for automatic product ordering (read more about how it works here).
Google’s learning thermostat, Nest doesn’t eliminate all decisions yet, but it allows you to optimize energy usage in your home without putting too much thought.
Giving too many options to users can make the decision-making process overwhelming and stressful. When this happens, people tend to leave early, and those who stay are usually less satisfied with the overall user experience.
It’s not a coincidence that experts say that the best way to maximize usability is to minimize the cognitive load.
Anticipatory design claims that is better to have fewer choices than it is to have more (to understand this perhaps you should take a look at this video on the Paradox of Choice) and thus it aims to eliminate redundant choices.
This way it can better control information overload and the resulting decision fatigue, which leads to lower bounce rates, fewer complaints, and purchases that are better suited to the individual customer.
Having fewer choices or no choices at all naturally results in simplified user interfaces. The recent popularity of flat design already shows the trend of users wanting less distractions and more intuitive online experiences.
Smartly utilized anticipatory design can save a lot of time for users, and allow them to focus on things that are more important for them, instead of performing mundane, repetitive tasks again and again.
We are living in the age of information, which means tons of personal and public data is at our disposal. We not only can reach loads of media publications, statistics, databases, and analyses, but also gain access to data logged by our wearables, smart devices, and other high tech gadgets that record our preferences, actions, and behaviours.
The human brain has limited capacities though, therefore we are unable to take everything into consideration.
The popularity of business logic software and expert systems in the corporate world already shows that many businesses trust machines better than humans. If anticipatory design is used the right way, it can improve the decision-making process and reduce human mistakes by gathering, aggregating, and making use of way more data than is manually possible.
The most important ethical questions anticipatory design brings up are data security and privacy. Anticipatory design needs data about our preferences and previous actions; moreover content providers can have access to our user profiles, social networks, mobile and web applications.
In short, different kinds of data controllers will hold tons of data about all of us. How will they handle it, and how much control are users willing to give up? In what forms will they be able to control who and how can access their data?
If, as designers, we really care about the needs of our users, we need to take privacy more into consideration than ever before, and build it into the design workflow.
In many cases, second-guessing just doesn’t work. Motives behind human actions can be different in each individual.
For example if someone schedules a meeting, do they need a taxi for sure? If the weather is nice, they might want to go on foot, or they might cancel the meeting last minute due to an emergency or if they felt under the weather.
Previous preferences can also be restrictive when someone wants to try out new things, or pick up new habits.
Companies using anticipatory design certainly need to make a lot of research, and assess responsibly what they can automate, and what they cannot, how they can keep users well-informed and avoid oversimplification.
Fully fledged anticipatory design will be an intuitive technology that probably will know us better than we know ourselves. Having fewer or no choice at all may leave us feeling manipulated, and constantly being assessed based on our past behaviour can hinder self-improvement and even set back our creativity.
If we outsource decision-making to algorithms, we can easily lose an important life skill as well. The most interesting question probably is whether users will recognize at all that they have less options than before. Will they be happy with a more hassle-free life, or mourn their reduced freedom?
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