@article{BuechnerDosdall2021,
  author    = {B{\"u}chner, Stefanie and Dosdall, Henrik},
  title     = {Organisation und Algorithmus},
  series = {K{\"o}lner Zeitschrift f{\"u}r Soziologie und Sozialpsychologie : KZfSS},
  volume    = {73},
  journal   = {K{\"o}lner Zeitschrift f{\"u}r Soziologie und Sozialpsychologie : KZfSS},
  number    = {Suppl. 1},
  publisher = {Springer VS},
  address   = {Wiesbaden},
  issn      = {0023-2653},
  doi       = {10.1007/s11577-021-00752-0},
  pages     = {333 -- 357},
  year      = {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.},
  language  = {de}
}
@misc{UllrichEnkeTeichmannetal.2019,
  author    = {Ullrich, Andre and Enke, Judith and Teichmann, Malte and Kress, Antonio and Gronau, Norbert},
  title     = {Audit - and then what?},
  series = {Procedia Manufacturing},
  volume    = {31},
  journal   = {Procedia Manufacturing},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2351-9789},
  doi       = {10.1016/j.promfg.2019.03.025},
  pages     = {162 -- 168},
  year      = {2019},
  abstract  = {Current trends such as digital transformation, Internet of Things, or Industry 4.0 are challenging the majority of learning factories. Regardless of whether a conventional learning factory, a model factory, or a digital learning factory, traditional approaches such as the monotonous execution of specific instructions don't suffice the learner's needs, market requirements as well as especially current technological developments. Contemporary teaching environments need a clear strategy, a road to follow for being able to successfully cope with the changes and develop towards digitized learning factories. This demand driven necessity of transformation leads to another obstacle: Assessing the status quo and developing and implementing adequate action plans. Within this paper, details of a maturity-based audit of the hybrid learning factory in the Research and Application Centre Industry 4.0 and a thereof derived roadmap for the digitization of a learning factory are presented.},
  language  = {en}
}