%0 Journal Article %1 B_chner_2021 %A Büchner, Stefanie %A Dosdall, Henrik %D 2021 %E Heintz, Bettina %E Wobbe, Theresa %I Springer Science and Business Media %J KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie %K algorithms digitization myown organizations %N S1 %P 333-357 %R 10.1007/s11577-021-00752-0 %T Organisation und Algorithmus %U https://doi.org/10.1007%2Fs11577-021-00752-0 %V 73 %X This article analyzes how organizations endow algorithms, which we understand as digital formats of observation, with agency, thus rendering them actionable. Our main argument is that the relevance of digital observation formats results from how organizations embed them in their decision architectures. We demonstrate this using the example of the Austrian Public Employment Service (AMS), which introduced an algorithm in 2018 to evaluate the chances of unemployed persons being reintegrated in the labor market. In this regard, the AMS algorithm serves as an exemplary case for the current trend among public organizations to harness algorithms for distributing limited resources in a purportedly more efficient way. To reconstruct how this is achieved, we delineate how the AMS algorithm categorizes, compares, and evaluates persons. Building on this, we demonstrate how the algorithmic model is integrated into the organizational decision architecture and thereby made actionable. In conclusion, algorithmic models like the AMS algorithm also pose a challenge for organizations because they mute chances for realizing organizational learning. We substantiate this argument with regard to the role of coproduction and the absence of clear causality in the field of (re)integrating unemployed persons in the labor market.

@article{B_chner_2021, abstract = {This article analyzes how organizations endow algorithms, which we understand as digital formats of observation, with agency, thus rendering them actionable. Our main argument is that the relevance of digital observation formats results from how organizations embed them in their decision architectures. We demonstrate this using the example of the Austrian Public Employment Service (AMS), which introduced an algorithm in 2018 to evaluate the chances of unemployed persons being reintegrated in the labor market. In this regard, the AMS algorithm serves as an exemplary case for the current trend among public organizations to harness algorithms for distributing limited resources in a purportedly more efficient way. To reconstruct how this is achieved, we delineate how the AMS algorithm categorizes, compares, and evaluates persons. Building on this, we demonstrate how the algorithmic model is integrated into the organizational decision architecture and thereby made actionable. In conclusion, algorithmic models like the AMS algorithm also pose a challenge for organizations because they mute chances for realizing organizational learning. We substantiate this argument with regard to the role of coproduction and the absence of clear causality in the field of (re)integrating unemployed persons in the labor market.}, added-at = {2022-03-01T14:30:46.000+0100}, author = {Büchner, Stefanie and Dosdall, Henrik}, biburl = {https://www.bibsonomy.org/bibtex/2432616e088bd6c37e635ca494e91e8ed/stbuech}, description = {(Peer Reviewed)}, doi = {10.1007/s11577-021-00752-0}, editor = {Heintz, Bettina and Wobbe, Theresa}, interhash = {b2b4d110b57a005f70ebeaf1aef86aa6}, intrahash = {432616e088bd6c37e635ca494e91e8ed}, journal = {{KZfSS} Kölner Zeitschrift für Soziologie und Sozialpsychologie}, keywords = {algorithms digitization myown organizations}, language = {german}, month = jun, number = {S1}, pages = {333-357}, publisher = {Springer Science and Business Media }, timestamp = {2022-03-01T15:03:20.000+0100}, title = {Organisation und Algorithmus}, url = {https://doi.org/10.1007%2Fs11577-021-00752-0}, volume = 73, year = 2021 }