Lionel Michel ⇾ Making sense of human and technological infrastructures

Initial situation — Nowadays, designers create interfaces and services driven by algorithms that gather information in the networks and discretely filter them for the users. As human knowledge can be defined as the personal habits that define how we perceive and process information, it is a matter of fact that the nature of the digital infrastructure does have an influence on how we form our knowledge.

Approach — I decided in my Masters’s Thesis to investigate human knowledge as I consider it as a valuable concept as a practitioner of human-centered design. In my analysis, I first explored various views of human knowledge originating from disciplines like philosophy, psychology or the history of science as well as the intrinsic quality of our medial environment. Then I undertook a series of interviews probing online habits and aspects of general understanding. Download the theoretical analysis (PDF – 173 pages)

Result — Impressed by the barely remembered knowledge-related principles behind the pictorial statistics method Isotype initiated by Otto Neurath in the 1920s, I investigated how they would nowadays apply. Within this process, I prototyped an exhibition format showcasing the complexity hidden in the digital world as well as how this may influence us and our knowledge.

Process

  • Theoretical analysis
  • User interviews
  • Exhibition concept
  • Information architecture
  • Sketching
  • Poster design

Presented at

Supervised by Prof. Dr. Frank Heidmann and Prof. Dr. Marian Dörk at the University of Applied Sciences Potsdam, Germany

More information

Exhibition structure

The exhibition is organized in three parts, including 16 exhibits overall, and is planned to contain participative exhibits:

  • Approaching the topic of knowledge — Historical dimension and video interviews showcasing various opinions on what can be considered as knowledge.
  • Understanding networks and algorithms — Exploration of the internal mechanisms of networks and algorithms as well as their combined use.
  • Reflecting on my knowledge — Summing up and feed-back.
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Visualization: From the website to the network

Networks are hidden in "flat" web interfaces. We use them on a daily basis but we are not always aware of their connected nature. Uncovering and mapping them in different ways may allow us to produce some interesting insights. In the case of a "friendship" network, we can learn at a glance, which of one's friends are also friends with one another.

Visualization: The social prototype

Personal knowledge arises amongst others out of the confrontation with new ideas or concepts that “force” us to evolve. Sometimes, things are simply not like they were before…

Living enmeshed in the digital networks enable us to enjoy a great range of tremendous possibilities. For example, we are constantly being served with content selected according to our behavior and tastes. The downside of it is that getting content that “suits” may, in the end, prevent us from engaging with the complexity of reality. We get stuck in a filter bubble.

Prototyping an exhibit

In a participative exhibit named Programming the algorithm, visitors are invited to contribute to the conception of an algorithm that commands the personalization of search results.

During a workshop at the university, I intended to test a concept enabling visitors to explore the different types of signals that are captured by search engines (e.g. search topics, clicked ads, type of devices used, etc.) and to infer some contextual information. Like an algorithm would do.

In the detail, the participants were first asked to pick a signal (e.g. topic of the clicked ads) and to devise different possible answers (e.g. sport, cars, health, beauty products, etc.). Later they had to infer various interpretations for each of those answers. At this point, it was clear for the participants that any interpretation will always remains superficial. In the end, an algorithm is not a neutral entity but a machinery designed by a programmer. This one, like each of us, may be partial or biased.

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