Project

Serendipity Engine: towards surprising and interesting urban experiences

Code
3S006323
Duration
01 October 2022 → 30 September 2026
Funding
Research Foundation - Flanders (FWO)
Research disciplines
  • Natural sciences
    • Knowledge representation and reasoning
    • Machine learning and decision making
    • Human-computer interaction
  • Social sciences
    • Communication research methodology
    • Political economy of communication
Keywords
humanities political sciences data discovery Bias in recommendation algorithms data science social sciences Reinforcement learning
 
Project description

Concerns exist regarding the controlling and restricting nature of todays

recommender systems. The trend is towards serving predictable,

popular and homogeneous content, which is often referred to as filter

bubbles. In an urban context, this means that people are no longer

exposed to the diversity of cities and their inhabitants, which has

negative consequences for the open and democratic character of the

city. This is a timely issue that needs urgent attention and there is a

societal call for a transition towards applications that promote

serendipity. However, what is missing today is a clear understanding of

the meaning and value of serendipity in urban environments, and how

this can be engendered in digital applications. In this project, we will

develop such an understanding and identify the potential role of

governing organisations in introducing serendipity to urban information

systems. Additionally, the project will investigate how developers can

design for serendipity. This will be studied on the level of data,

algorithms and design. This approach is inspired by the theory of

affordances and the findings that (digital) environments can be designed

to afford serendipity. The affordances (in terms of data, algorithms and

design) will be designed, developed and validated using Living Lab

methodologies in three urban pilot scenarios. To support this Living Lab

approach, a novel research methodology will be developed to study

users experienced serendipity.