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Algorithmic management information


Algorithmic management is a term used to describe certain labor management practices in the contemporary digital economy. In scholarly uses, the term was initially coined in 2015 by Min Kyung Lee, Daniel Kusbit, Evan Metsky, and Laura Dabbish to describe the managerial role played by algorithms on the Uber and Lyft platforms,[1][2] but has since been taken up by other scholars to describe more generally the managerial and organisational characteristics of platform economies.[3][4] However, digital direction of labor was present in manufacturing already since the 1970s and algorithmic management is becoming increasingly widespread across a wide range of industries.[5]

The concept of algorithmic management can be broadly defined as the delegation of managerial functions to algorithmic and automated systems.[6] Algorithmic management has been enabled by recent advances in digital technologies which allow for the real-time and "large-scale collection of data" which is then used to "improve learning algorithms that carry out learning and control functions traditionally performed by managers".[7]

In the contemporary workplace, firms employ an ecology of accounting devices, such as “rankings, lists, classifications, stars and other symbols’ in order to effectively manage their operations and create value without the need for traditional forms of hierarchical control.”[8] Many of these devices fall under the label of what is called algorithmic management, and were first developed by companies operating in the sharing economy or gig economy, functioning as effective labor and cost cutting measures.[9] The Data&Society[10] explainer of the term, for example, describes algorithmic management as ‘a diverse set of technological tools and techniques that structure the conditions of work and remotely manage workforces.[9] Data&Society also provides a list of five typical features of algorithmic management:

  • Prolific data collection and surveillance of workers through technology;
  • Real-time responsiveness to data that informs management decisions;
  • Automated or semi-automated decision-making;
  • Transfer of performance evaluations to rating systems or other metrics; and
  • The use of “nudges” and penalties to indirectly incentivize worker behaviors.[9]

Proponents of algorithmic management claim that it “creates new employment opportunities, better and cheaper consumer services, transparency and fairness in parts of the labour market that are characterised by inefficiency, opacity and capricious human bosses.”[11] On the other hand, critics of algorithmic management claim that the practice leads to several issues, especially as it impacts the employment status of workers managed by its new array of tools and techniques.[2][12][13]

  1. ^ Lee, Min Kyung; Kusbit, Daniel; Metsky, Evan; Dabbish, Laura (2015-04-18). "Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers". Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. CHI '15. New York, NY, USA: Association for Computing Machinery: 1603–1612. doi:10.1145/2702123.2702548. ISBN 978-1-4503-3145-6.
  2. ^ a b Rosenblat, Alex; Stark, Luke (2016-07-27). "Algorithmic Labor and Information Asymmetries: A Case Study of Uber's Drivers". International Journal of Communication. 10 (0): 27. ISSN 1932-8036.
  3. ^ Griesbach, Kathleen; Reich, Adam; Elliott-Negri, Luke; Milkman, Ruth. "Algorithmic Control in Platform Food Delivery Work". Socius: Sociological Research for a Dynamic World. 5: 237802311987004. doi:10.1177/2378023119870041. ISSN 2378-0231.
  4. ^ Stark, David; Pais, Ivana (2020). "Algorithmic Management in the Platform Economy". Sociologica. 14 (3): 47–72. doi:10.6092/issn.1971-8853/12221. ISSN 1971-8853.
  5. ^ Schaupp, Simon (2022-05-23). "COVID‐19, economic crises and digitalisation: How algorithmic management became an alternative to automation". New Technology, Work and Employment: ntwe.12246. doi:10.1111/ntwe.12246. ISSN 0268-1072. PMC 9347406. PMID 35936383.
  6. ^ Jarrahi, Mohammad Hossein; Newlands, Gemma; Lee, Min Kyung; Wolf, Christine T.; Kinder, Eliscia; Sutherland, Will (2021). "Algorithmic management in a work context". Big Data & Society. July–December (2): 1–14. doi:10.1177/20539517211020332. hdl:11250/2976736. S2CID 237760709.
  7. ^ Möhlmann, Mareike; Zalmanson, Lior; Henfridsson, Ola; Gregory, Robert Wayne (2021). "Algorithmic Management of Work on Online Labor Platforms: When Matching Meets Control". MIS Quarterly. 45 (4): 1999–2022. doi:10.25300/MISQ/2021/15333. S2CID 227184033.
  8. ^ Kornberger, Martin; Pflueger, Dane; Mouritsen, Jan. "Evaluative infrastructures: Accounting for platform organization". Accounting, Organizations and Society. 60: 79–95. doi:10.1016/j.aos.2017.05.002. hdl:20.500.11820/1147b691-a371-4a13-a3ab-746c8427dd37. ISSN 0361-3682.
  9. ^ a b c Mateescu, A. & Nguyen, A. (2019). Explainer: Algorithmic Management in the Workplace. Data&Society, datasociety.net, February 2019. Retrieved from: https://datasociety.net/wp-content/uploads/2019/02/DS_Algorithmic_Management_Explainer.pdf
  10. ^ "Data & Society". Datasociety.net. Retrieved 2022-08-17.
  11. ^ O'Connor, Sarah (2016-09-08). "When your boss is an algorithm". Financial Times. Retrieved 2024-03-19.
  12. ^ Rosenblat, A. (2018). Uberland: How Algorithms Are Rewriting The Rules Of Work. Berkeley: University of California Press.
  13. ^ Ajunwa, I. (2018). Algorithms at Work: Productivity Monitoring Applications and Wearable Technology as the New Data-Centric Research Agenda for Employment and Labor Law. Saint Louis University Law Journal, 63(1): 21–54.

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