**Abstract**

The economy of the Modern Work Platform is becoming increasingly relevant due to the spread of information and communication technology. As a result, digital work has gained popularity as a source of employment, especially in an economy where finding decent work is becoming increasingly difficult. Computer algorithms are now being used to alter and change the way people operate in increasing job specialization, handling large-scale human labour in a distributed manner. In these structures, human works are delegated, supplemented, and analyzed using tracked data and algorithms. Building on emerging algorithmic literature and qualitative examination, this article assesses the mechanisms by which the digital network manages staff in the sense of Uber, Bolt (formerly Taxify). It describes the difference in the degree to which such platforms limit freedoms over schedules and activities relevant to gig work. Based on in-depth interviews with 41 respondents working on different digital media and a survey of 105 staff on the same platform, the study finds that while all digital work platforms use algorithm management to delegate and assess work, substantial cross-platform variation. Uber, the largest network for ride-sharing, exercises a type of control called "algorithmic despotism" that controls the time and activities of staff more strictly than other network distribution firms. We end with a debate on the implications for the future of work of the spectrum of algorithmic power. It also addresses how algorithmic management and data-driven systems can be developed to build an improved workplace with intelligent machines, with implications for future work.

**Keywords:** algorithmic management, digital platform, intelligent systems, on-demand work, performance evaluation
