ALGORITHMIC MANAGEMENT AND PROFESSIONAL AUTONOMY: THE IMPACT OF DIGITAL PERFORMANCE MONITORING ON MEDICAL WORKERS' CONTRACTUAL RIGHTS

Авторы

  • Otaboy Yashnarbekov

Ключевые слова:

algorithmic management, professional autonomy, digital monitoring, healthcare workers, contractual rights, medical practice, performance evaluation, healthcare technology

Аннотация

This study examines the intersection of algorithmic management systems and professional autonomy within healthcare environments, specifically analyzing how digital performance monitoring affects the contractual rights of medical workers. Through a comprehensive analysis of contemporary healthcare management practices, this research investigates the tension between efficiency-driven algorithmic oversight and the traditional professional discretion that has historically characterized medical practice. The findings reveal that while algorithmic management systems enhance operational efficiency and standardize care delivery, they simultaneously constrain medical professionals' decision-making autonomy and potentially compromise patient care quality. The study demonstrates that current digital monitoring systems inadequately account for the complexity of medical decision-making, creating conflicts between contractual obligations and professional ethical standards. These findings have significant implications for healthcare policy, labor relations, and the future of medical practice in an increasingly digitized healthcare landscape.

Библиографические ссылки

Abbott, A. (1988). The system of professions: An essay on the division of expert labor. University of Chicago Press.

Ajunwa, I., Crawford, K., & Schultz, J. (2017). Limitless worker surveillance. California Law Review, 105(3), 735-776.

Brayne, S. (2020). Predict and surveil: Data, discretion, and the future of policing. Oxford University Press.

Christin, A. (2017). Algorithms in practice: Comparing web journalism and criminal justice. Big Data & Society, 4(2), 1-14.

Flyverbom, M., Deibert, R., & Matten, D. (2019). The governance of digital technology, big data, and the internet: New roles and responsibilities for business. Business & Society, 58(1), 3-19.

Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366-410.

Lee, M. K., Kusbit, D., Metsky, E., & Dabbish, L. (2015). 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, 1603-1612.

Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.

O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group.

Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.

Rahman, K. S. (2021). Democracy against domination. Oxford University Press.

Rosenblat, A., & Stark, L. (2016). Algorithmic labor and information asymmetries: A case study of Uber's drivers. International Journal of Communication, 10, 3758-3784.

Shapiro, A. (2018). Between autonomy and control: Strategies of arbitrage in the "on-demand" economy. New Media & Society, 20(8), 2954-2971.

Vallas, S., & Schor, J. B. (2020). What do platforms do? Understanding the gig economy. Annual Review of Sociology, 46, 273-294.

Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.

Опубликован

2025-05-26

Выпуск

Раздел

Статьи