After God and Man, Algorithms will make the decisions.– Historian Yuval Noah Harari
From taxi drivers to restaurant food delivery couriers and order-pickers at grocery stores or warehouses, the ever-larger role of artificially intelligent (AI) algorithms in allocating, overseeing and managing how service work is conducted brings new considerations to service management.
In this article, we, Haaga-Helia’s researchers Aarni Tuomi and Mário Passos Ascenção team up with University of Surrey’s Doctoral Researcher Brana Jianu to discuss how algorithmic management is influencing service management. The article also introduces Haaga-Helia’s latest project, AlgoAmmatti, which aims to understand the phenomenon of algorithmic management better.
The original concept of algorithmic management is often attributed to Lee, Kusbit, Metsky & Dabbish (2015) who define algorithmic management as “software algorithms that assume managerial functions and surrounding institutional devices that support algorithms in practice.” According to them, algorithmic management allows companies to oversee large numbers of workers at unprecedented scale and systematic precision.
In their review of literature looking at algorithmic management practices, Kellogg, Valentine & Christin (2019) highlight six mechanisms through which AI algorithms assert control over human workers:
- Directing workers by restricting and recommending
- Evaluating workers by recording and rating
- Disciplining workers by rewarding and replacing
For example, in the context of restaurant food delivery, different types of search and rank algorithms allocate delivery tasks to couriers. Another set of algorithms monitors the progress and completion of the delivery task in real time. A third set of algorithms rates and records the performance of the worker.
In some contexts, the rating is made explicit as with Uber, where both drivers and customers can see each other’s rating. This in turn influences how tasks are allocated. However, in many other platforms, the ratings come into play only behind the scenes.
No service business or context escapes the power of the algorithm
The accommodation subsector of hospitality is well-known for being labour intensive, with unpredictable working hours, complex compliance requirements, and high personnel turnover. Thus, making it a particularly enticing candidate for algorithmic management.
The idea of hotel housekeepers scurrying around corridors at breakneck speed in response to their algorithmic supervisor’s task allocation directive is becoming increasingly common. Hotel workers’ shifts are scheduled, compliance tracked, and even the vaccination status of hotel personnel is monitored by algorithms.
Further, algorithms can also undertake real-time conversational streaming analysis in hotel reservations and call centres to analyse employees’ interactions with callers for elements of mimicry, consistent turn-taking, tone, energy level and empathy cues. Workers are then ranked in their performance against these criteria.
The human says no
Algorithmic management fits like a glove with all new forms of digitally mediated work. The kind of work that allows workers with a high degree of flexibility and autonomy, while simultaneously shifting the power balance away from the workers themselves due to new forms of control and surveillance.
Therefore, one of the key issues and points of debate in algorithmic management is the lack of transparency on how the underlying algorithm makes management decisions: what data is used and how it is collected and processed.
In response to the use of data-hungry code to algorithmically nudge the behaviour of human workers, a counter-movement dubbed algoactivism has risen in recent years. Algoactivists aim to raise awareness of algorithmic management practices and their impacts on peoples’ wellbeing. Algorithm Watch, a Berlin-based non-profit research and advocacy organisation, is one of the drivers of critical debate in the context of Europe.
To illustrate what algoactivism might look like in practice, Bucher, Schou and Waldkirch (2020) studied what they dubbed as anticipatory compliance. Their study found that workers managed by algorithms adopted a myriad of direct and indirect strategies to outsmart the algorithm. For example, they note that workers might change the way they carry out their tasks, e.g. to purposefully undervalue their own work or to stay under the radar of the algorithm by not publicly voicing their concerns or sending support requests to the system, in order to maximise how the system records, rates and rewards their behaviour.
Ritzer (2019) advocates that in the later part of the 20th century the socially-structured form of McDonalds became the organizational force representing and extending the process of rationalization into the realm of everyday interaction and individual identity. This McDonaldization of society followed similar principles – efficiency, calculability, predictability, and control – to the ones used by digital labour platforms. It seems, the first part of the 21st century is going through a similar process, which we designate as the “Uberisation” of society.
New questions to consider
Algorithmic management brings several new considerations to service management.
- Who should own the data that is generated through stakeholders’ interaction on digital labour platform?
- How could transparency of how the system works be increased, from all users’ points of view?
- What kinds of informal interactions and relationships form between workers as they learn, over time, how to best tiptoe around the algorithm?
These are just some questions and the ones that we seek to answer in our AlgoAmmatti – Algorithmic Management and Professional Growth in Platform Economy -project.
- Bucher, E. L., Schou, P. K., & Waldkirch, M. 2020. Pacifying the algorithm – Anticipatory compliance in the face of algorithmic management in the gig economy. Organization, 28(1), 44-67. Doi:10.1177/1350508420961531
- Kellogg, K. C., Valentine, M. A., & Christin, A. 2019. Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366-410. Doi:10.5465/annals.2018.0174
- Lee, M. K., Kusbit, D., Metsky, E., & Dabbish, L. 2015. Working with machines: The impact of algorithmic and data-driven management on human workers (pp. 1603-1612). Paper presented at the Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Seoul, Republic of Korea. Doi:10.1145/2702123.2702548
- Ritzer, G. 2019. The McDonaldization of Society: Into the Digital Age (9th ed.). Thousand Oaks: SAGE Publishing.
Dr. Aarni Tuomi is the Principal Investigator (PI) in the AlgoAmmatti-project. He works as a Senior Lecturer at Haaga-Helia University of Applied Sciences. Aarni’s research explores the intersection of emerging technology and service business.
Dr. Mário Passos Ascenção is a Principal Lecturer in Experience Design, Imagineering and Serious Play in Haaga-Helia University of Applied Sciences and a Play Chief Evangelist and Tool Factory Chief Alchemist in the university’s Service Experience Laboratory, LAB8.
Brana Jianu is a Ph.D. Researcher at the University of Surrey. Her Ph.D. research focuses on algorithmic management in the context of hospitality business.