Anticipatory Design & The Future of Experience — Sarah Doody
The Product Strategist Sarah Doody shared some powerful insights on the influence of technology on our decision making processes. On her Talk at the Productized Conference, in Lisbon, Sarah showed some examples to define the difference between Anticipatory and Automated Design.
So, imagine this is your big day and you won the lottery. Would you keep your day job? When asked, 51% of people tend to say they would. Mostly because they would easily get bored after a certain time or due to the fact that their jobs give them a sense of purpose. On “The Glass Cage”, the author Nicholas Carr mentions the concept of “Paradox of Work” and questions why do we say we hate our jobs even though we get so much fulfilment out of it. A study in Chicago in the 90’s gave 400 people a beeper (yes, a beeper, it was the 90’s after all) that rang 7 times a day. Every time the beeper rang, people needed to tell how they felt at the moment. Surprisingly, most people felt better during work hours.
When researching for the reason to that, the study came to the conclusion that our jobs create an environment for flow. Getting a little bit into neuroscience, they analyzed the Dorsolateral Prefrontal Cortex, the part of the brain that controls self monitoring, responsible for the voice of doubt, defeatist nag and the inner criticism. In a flow state, the self monitoring part of the brain is significantly decreased. Flow leads people to a state of more liberation and less hesitation.
“When you’re in a flow state, the part of our brain responsible for self monitoring dissipates”
Will robots take my job?
Work fulfillment can’t be discussed without considering a key question: what happens when robots take our jobs? Technology is changing the way we work and live and the computed features in our lives can be divided into two different categories, the ones based on Anticipatory Design and the ones based on Automated Design.
Anticipatory Design can be defined as the prediction of people’s needs followed by the offer of the right information at exactly the right time, which is pure UX. Meanwhile, Automated Design takes a step further and instead of giving people the information, it’s making decisions and taking action on behalf of people, without their input.
This way, the automation works in a way that after the Discovery process, that finds out what people need before they do, and the Taking Action Process, that provides action suggestions based on the situation, comes the Understanding part, which interprets information rather than just displaying it.
Technology that takes action on behalf of people can be a good solution for a very contemporary problem, decision fatigue. Aaron Shapiro, CEO of Huge, wrote an article explaining why the next big in design will be less choice. Decision fatigue has been a key driver to our persistent state of overwhelm, statistics show that nowadays we take up to 35.000 decisions a day. The future with Automated Design will be all about creating an environment where a decision is never made.
What happens when the user has to step in?
Automation can fail, therefore the users have to eventually step in and make decisions for themselves. The issue about it is that the more automation acts on the users behalf, the less used to make decisions they are. For instance, statistics from the American Federal Aviation Administration show that 2/3 of all plane crashes occurred between 2000 and 2010 were caused by pilot error. That happens due to autopilot, the automated system that allows pilots to actually fly a plane for only 3 minutes per flight. This type of heavy automation stimulates something called deskilling when you’re not able to perform what you’re supposed to perform. Skills are basically like muscles, if you don’t practice, you lose them.
What happened with the 447 AirFrance flight, flying from Rio to Paris, in 2009, illustrates well the consequences of automation failure. When the airspeed monitors from the aircraft got covered in ice, the autopilot shut off and the pilots had to quickly step in. Their decision led the plane to drop at 10.000 feet a minute. The investigation done by the French concerning this crash concluded that the crash was caused by “loss of cognitive control”, also known as deskilling.
It’s important to be cautious about the possibility of automation failure by creating environments in which the user is able to course correct. Consequences may not be as extreme as the ones in the case of 447 flight, but making course correcting easier is a necessary goal.
Where are new ideas start to come from?
With automation taking over the decision roles, it’s important to think about where will new ideas come from. The role of the observer, a figure that seeks improvement, is very important for innovation.
Toyota spent a lot of money by bringing robots into their factories. It sure improved production and accuracy, but after a certain time the brand brought people back into their production line. The reason for that is simple. Robots can do things over and over again, but they’re not able to have one of those lightbulb moments in which we say “What if we did things the other way?”.
In that sense, robots cannot be sideline observers that seek opportunities for improvement like humans are. Robots can do things over and over. People can do things over and better.
What will become of the human experience?
If the tendency is to have our decisions more and more automated, where will we get our sense of fulfillment from? When going through the path of anticipatory design and automation of decision making processes, there are 3 design principles that should be taken into consideration.
The first principle to be considered is transparency. Making sure that there’s transparency about the decisions that are being made on behalf of the user. This way, people are more conscious about when to regain control over the situation.
Curation is another key principle in order to minimize decision fatigue. Doing recommendations in a more human way, that provides context, can be a great way to improve the decision making process. The choice of a movie on Netflix, for instance, could be less painful if we had a little bit more information about why are those titles being recommended for us. People are skeptical about algorithms, so human curation would aim for quality instead of quantity.
The final and most debated principle nowadays is trust. In order to make successful decisions on behalf of people, it’s necessary to gather the largest amount of information about them.
With users holding tighter and tighter to their personal data, it’s essential to build trust among users by letting them know how their information is being used.
After analyzing those three principles, it’s important to question yourself and your team about the temptations that exist in need anticipation and decision automation. Teams need to constantly reflect about the real reasons that motivate them.
“Are they doing that because it’s a real need from the user or just doing it for the sake of technology?”
When working with technology we have a responsibility to solve problems but also not to create bigger ones that can create long term impact for your people and for your products.
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About Sarah Doody
Sarah Doody is a user experience designer and product strategist. Sarah works with companies of all sizes and stages to help them create results-driven user experiences. She is a contributing author to UX Magazine, InVision, UX Mastery, UX Matters, and has been published in the New York Times. In addition, she co-developed the curriculum for and taught General Assembly’s first 12-week User Experience Design Immersive. She also created and teaches her own UX courses, User Research Fundamentals and the UX Portfolio Formula.
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