Preface: Designing for Less Choice

Why anticipatory design is needed

Advancements in technology have brought us much possibilities but also pushed us towards a noisy and increasingly complex world. Back in the days, we used a middleman to process our transactions (e.g. when needing a cab, we called a taxi service and only gave our address and desired time of arrival). Nowadays, much is automated. Both in design as in technology leaving us with much choice. Approximately 35.000 a day (Tierney, 2014). This causes a lot of mental stress and decision fatigue.

This is just the start.

With the dawn of an era where machine and deep learning are more and more intertwined with our products and services, it is likely that soon, devices will know exactly what we want. Based on actions and behavioral patterns from the past. This shift towards machine-learning based predictive systems will provide many possibilities. It may reduce the amount of decisions we have to make and thereby make our lives easier. Automation and predicting our decisions can also have disadvantages more on a psychological level. It may affect our sense of curiosity and wonder because we can end up in a filter or experience bubble.

Design has always been crucial in the experience of a product or service. Design affects how we see, feel and think about things. The current set of design principles are based on products we interact with. It is unclear yet, what design principles are needed for products and services who interact with us and automate our experiences by deciding for us.

Aaron Shapiro introduced the term Anticipatory Design as a new breath of design thinking. The principle behind Anticipatory Design is that services and products decide in name of the user - without the user knowing it. The decision making in this case is based on patterns from the past like attended events, interests, online bought products etcetera.

Shapiro raised an interesting discussion about the importance of choices and how much it affects our quality of life. He refers to decision fatigue as an important problem to solve, because we now make too many decisions a day. 

Why research is needed

Concepts like anticipatory design are happening. Semi-autonomous machine learning-driven predictive systems are now in consumer-facing domains from smart homes to self-driving vehicles. It is just a matter of time until the first fully- autonomous machine learning-driven predictive systems will emerge. The concept of anticipation goes even further because it implies circularity and the ability of identifying, understanding and interpreting needs that individuals itself wouldn’t think of.

Changing roles, changing responsibilities
The role of data will be huge within these emerging fields of technology because full transparency from users is needed in order to learn and decide what to anticipate on. The current data ecosystem and privacy system are not durable and ready for this shift (bron). Now, data storage is vague and our privacy gets more violated with every new privacy agreement. When people are willing and ready to give full disclosure of their data, we need to rethink the current concept of anticipatory design and all underlying data and privacy ecosystems. It is about rethinking our relation with technology and the design challenge lies within human- data interaction and humanization of automated, anticipated experiences.

There’s is much to discover around anticipatory design and machine learning- based predictive systems.