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Accepted Paper:

Limits of transparency and depths of opacity in the use of APIs in information infrastructures  
Alain Sandoz (University of Neuchâtel) Léa Stiefel (IRIN.CH)

Paper short abstract:

The user of an API only knows what it gives, what it controls, and what it gets back. What it does not control makes up the opaque side of the API. The contribution identifies the limits of transparency and probes the depths of opacity that come with the use of APIs in information infrastructures.

Paper long abstract:

An Application Programming Interface is a technical mechanism that enables a calling program to trigger the execution of a called program, the former possibly supplying data to, and receiving data from, the called system.

The question of transparency (or of opacity) for the actor that controls the calling program is twofold: (1) who executes the called program? and (2) what does that program do?

The only way for that actor to be able to answer these two questions is to directly or indirectly fully control the execution of the called program.

In other words, users of an API only know what they give, what they control, and what they get back. What remains, i.e., what they do not control, makes up the opaque side of the API.

This « lack of control » spreads spatially and temporally out of the caller’s reach through the information infrastructure.

Based on extensive fieldwork on digitisation projects in Swiss agriculture between 2017 and 2019 and on subsequent research on the politics of digital architectures, the authors (a computer scientist and a social scientist working in an interdisciplinary dialogue) discuss the socio-technical concepts underlying the assertions above.

The notions of data owner vs. data user, digital service provider vs. digital service user, or control vs. dependency, are defined and contextualised.

In doing so, the authors identify the limits of transparency and probe the depths of opacity that come with the use of APIs in information infrastructures.

Panel P318
Opaque APIs: biases, blind spots, and instability
  Session 1 Wednesday 17 July, 2024, -