Anticipatory Design
vs Automated Design

What are the boundaries between anticipatory design and automated design?


*Anticipation can be found in literature and film genres and consists of works whose action takes place in the future, near or far. This genre is often linked to science fiction, but not systematically.
Anticipatory technologies find their first reference in science fiction literature* [1]. The most prolific writer for this submeter is the science fiction author Isaac Asimov which in the 1960s predicted some of the anticipatory technologies that we have today, many of which have become a reality.

Nonetheless, there is no novelty in the term. The term "anticipatory" appears in previous studies in computer science [3], philosophy [5], information science [3], interaction design [2], and even in biology [6].

All the fields discuss anticipation as a notion of predicting future actions, as essential, and as inherent components of systems.

No academic clearness

There is a lack of conceptual clarity in the literature between what defines anticipatory design and automated design.

There is a misleading definition between the two concepts, accordingly, we present a short concept analysis between them.

Accordingly, we should clarify each one's characteristics. Anticipatory design relies on predicting people's needs and actions and providing them with the right information at exactly the right time. While automation design is grounded on making decisions and taking actions, with accuracy, on the user's behalf, without their input.

Anticipatory design relies on automated design.

Yet, automated design is not bound to anticipatory design. We may automate a system without anticipating end-users' behaviors. But anticipatory is intrinsically related to automated users' experiences. In its very essence, anticipatory design is output without much need for user input. It is leveraging past choices to predict future decisions.

Anticipatory Design vision

Anticipatory Design has the determination of predicting user experiences. And to do so, it moves around three elements [2]:

· LearnCollect Data – Get input from user's data points and preferences collected by smart objects and the Internet of Things (IoT);

· PredictionCreate algorithmsMachine Learning (ML) algorithms are created to predict user's actions;

· AnticipationAnticipate choices – The original intentions have now to be foreseen by a User Experience Designer (UXD).

Figure 1: Anticipatory Design structure retrieved from Van Bodegraven [2].
If one of these three elements fail, we cannot design for anticipation.

Streamlined, usefulness, and convenience are a few reasons behind the notion of empowering everyday objects with internet connections. Essentially, smart objects are the framework that unleashed data collection to support anticipatory design. They are the means of execution utility.

These three elements need to be intersected and effectively used. There is a symbiosis between IoT, ML, and UXD:

"smart technology learns within the IoT by observing, while data is interpreted by ML algorithms. Along the way, UXD is crucial for delivering a seamlessly anticipatory experience that takes users away from technology" [2].

To do so, AI will need to support automation design by finding ways to use user's prior data and behaviors to support the design process to have a structured ecosystem to automatically decide successfully on behalf of the user or as close as possible.

We need smart objects to anticipate users' needs and actions. Because with IoT, our phones, personal computers, and smart assistants, are becoming the remote control that controls our environment. Made possible by IoT and big data, interactions have been moving off the screens into context. This raises a new concern for the designer. We need to start foreseeing the behavior we will design and display in this new network of things [4] because other users might be part of the same environment and data privacy will be a challenging topic to address in this new kind of intuitive interactions.

[1] Walorska, A.M.: Turning Data Into Experiences. Pro-active Experiences and their Significance for Customers and Business. Procedia Manuf. 3, 3406–3411 (2015).

[2] Van Bodegraven, J.: How Anticipatory Design Will Challenge Our Relationship with Technology A Future Without Choice. In: The AAAI 2017 Spring Symposium on Designing the User Experience of Machine Learning Systems. pp. 435–438 (2017).

[3] Zamenopoulos, T., Alexiou, K.: Towards an anticipatory view of design. Des. Stud. 28, 411–436 (2007).

[4] Kleber, S.: How to Get Anticipatory Design Right, https://www.hugeinc.com/articles/how-to-get-anticipatory-design-right, last accessed 2020/29/06.

[5] Husserl, E.: On the phenomenology of the consciousness of internal time (1893-1917). (1991).

[6] Gruetzemacher, R.: Rethinking AI Strategy and Policy as Entangled Super Wicked Problems. In: Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2018).
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