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Journal Articles Computer Supported Cooperative Work Year : 2022

Design Indirections


Digital products and services now commonly include algorithmic personalization or recommendation features. This has raised concerns of reduced user agency and their unequal treatment. Previous research hence called for increasing the participation of, among others, designers in the development of these features. To achieve this, researchers have suggested the development of better educational material and tools to enable prototyping with data and machine learning models. However, previous studies also suggest designers may find other ways to impact the development and implementation of such features, for instance through collaboration with data scientists. We build on that line of inquiry, through 19 in-depth interviews with designers working in small to large international companies to investigate how they actually intervene in shaping products including algorithmic features. We outline how designers intervene at different levels of the algorithmic systems: at a technical level, for instance by providing better input data ; at an interface or information architecture level, sometimes circumventing algorithmic discussions ; or at a organizational level, re-centering the outcome of algorithmic systems around product-centric questions. Building upon these results, we discuss how supporting designers engagement and influence on algorithmic systems may not only be a problem of technical literacy and adequate tooling. But that it may also involve a better awareness of the power of interface work, and a stronger negotiation skills and power literacy to engage in strategic discussions.
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Dates and versions

hal-03838119 , version 1 (03-11-2022)



Jérémie Poiroux, Nolwenn Maudet, Karl Pineau, Emeline Brulé, Aurélien Tabard. Design Indirections: How designers find their ways in shaping algorithmic systems. Computer Supported Cooperative Work, 2022, Machine Learning and the Work of the User, ⟨10.1007/s10606-022-09459-y⟩. ⟨hal-03838119⟩
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