THE GIG ECONOMY
should consider delivering takeaways and avail themselves of the “great opportunities” afforded by gig work. As policymakers continue to grapple with the grand challenge of regulating gig work, a broader understanding of algorithmic control and the multifaceted challenges faced by workers can pave the way for meaningful reforms and improved working conditions. Acknowledging these challenges would be a small but important step towards creating a more equitable and sustainable gig economy. The increasing use of algorithms within traditional work must also be critically examined from multiple stakeholder perspectives. Questions for educators As educators, the implications of this research and the associated rise in how algorithms are used at work raise important questions. Employment should involve opportunities for productive work in conditions of freedom, equity, security and human dignity. People engage in work with the goal of being productive in a way that meets human needs and because it enhances our sense of identity to become healthy, contributing members of society. While a significant number of gig workers are likely to see such roles as temporary arrangements, there are still many who consider it a full-time, long-term endeavour. How likely then are these gig workers to experience the reassurance of decent work? Control underpinned by algorithms allows platform organisations to allocate tasks dynamically and coordinate workers’ activities closely. It also allows them to continuously aggregate data and ratings to monitor worker performance and strategically manage reward systems, based on aggregated ratings and levels of customer demand. While this replaces a lot of the work done traditionally by human managers and provides significant economies of scale, there is substantial potential for workers to be impacted negatively (see box below) . Is this form of hyper-transactional work something that we want to continue growing? Should we be concerned that traditional organisations may seek to move away from more relational employment arrangements with workers to a more distant, harder model of control? Now is the time to consider what factors need to be central in the minds of organisational decision-makers when determining how, and to what extent, they make use of algorithms to manage work and workers. The trouble with gigs • The potential impact on worker wellbeing involves increased job and income insecurity, due to the unpredictability of work demands • Difficulty in exerting autonomous decisions in task performance to comply with given instructions • Accidents and mental distress at work • High work intensity to meet requirements and/or secure sufficient and steady income • Work/life balance difficulties caused by unpredictable scheduling and the prolonged online availability needed to get assigned tasks and secure a reliable income
aligning worker activities with company objectives. This is despite these workers not receiving any of the benefits afforded to direct employees, such as job or income security. Control is, of course, a key feature needed within all organisational forms and the business model of online labour platforms certainly offers a distinct and novel approach in this respect. While one might expect the platforms themselves to hold all the power, our study reveals additional layers of algorithmic control that are markedly different to how organisations in more traditional work contexts operate. Non-organisational actors, including those outside the company’s structure, play a significant role in shaping the fate of gig workers. By feeding the algorithm with important job-specific data based on their direct interactions with workers, these actors hold influence over worker efficiency and contribute to the worker rating systems used by labour platforms. These ratings typically govern ongoing access to further work, or ‘gigs’, and therefore, a worker’s ability to earn. Satisfying demand The findings paint a challenging picture for gig workers, who find themselves at the mercy of multiple stakeholders, each with their own set of unique demands. These non-organisational stakeholders are also unlikely to truly appreciate the influence they are exerting. To maintain access to work and secure a steady income, gig workers engaged in food-delivery services, for example, are compelled to constantly navigate the intricate dance of satisfying labour platforms, customers and even restaurants. Customers, for example, wield a high degree of control by quantitatively rating gig workers’ performance. This influences how workers subsequently approach tasks. Workers with low ratings, for example, may face repercussions from the algorithm that can range from subtle warnings to complete removal from the platform. There is also the impact of restaurant suppliers on food-delivery platforms to consider. In our research, gig economy workers said that lengthy, unpaid waiting times in restaurants – known as ‘dead-waiting’ – significantly reduced their average hourly earnings. This highlights an additional complexity faced by gig workers, where delivery efficiency and earning potential are directly linked to efficiency in supply. There is also very little a worker can do to influence restaurants to be more punctual and keep their own waiting times to a minimum. In this light, algorithmic HRM control, with its ability to monitor, evaluate and shape gig workers’ behaviour is clearly blurring the line between independence and subservience. By prioritising organisational objectives and ensuring task efficiency, the system fosters a complex network of power dynamics that seem largely invisible to those not directly involved in gig work. Acknowledging the power dynamics The myth of ‘being your own boss’ is shattered once gig workers realise that their actions are meticulously guided by technologies that serve the interests of platforms. This is concerning when platform-driven narratives surrounding gig work are repeated and promoted by governments. In the UK, for example, Secretary of State for Work and Pensions Mel Stride has suggested that people over the age of 50 who are looking for work
Ambition | NOVEMBER 2023 | 17
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