I suppose it comes as no surprise that the nine-to-five workday is considered outdated and employees instead expect flexibility in their workplaces. Flexible work policies, including opportunities for home office or the possibility to telework away from home in temporary office spaces such as those provided by WeWork or Daysk.com appear attractive for a reason – people value autonomy. The self-determination theory posits that autonomy, together with competence and relatedness, are the basic psychological needs that need to be satisfied for employees to be intrinsically motivated and increase their well-being. Hence, freedom of choice, independence and decreased control, which assumingly come with flexible policies, make us happier as they feed our need for autonomy. In this context, the ongoing rise of gig work also makes perfect sense. What could be better than working when you want, where you want, and on the gigs you choose?!
The implied freedoms and privileges of gig workare unlikely to apply to Uber drivers or food delivery guys, whose work is more likely necessity than choice… instead, we can think about remote gig work. Virtual freelancers, who sit with their computers in a coffee shop or by the beach, may seem the ‘dream job’ holders indeed. Putting this idyllic picture aside, the appeal of remote gig work is still real. For instance, the European Commission survey data indicates that the online labour market has grown globally by approximately 25 percent over the past two years.
A recent Oxford University study on the remote gig economy indicated that, although remote freelancers do indeed perceive autonomy, freedom of choice (how they work, what gigs they choose) and discretion in their work, there are several pitfalls to be aware of. Remote gig work mostly implies the usage of online platforms, which link professionals with customers, hence creating opportunities on both sides. Yet, the same platform algorithms that create these opportunities and grant autonomy, also imply control. As the study authors put it, this is ‘autonomy in the shadow of algorithmic management’ (pg. 64).
The algorithms enable workers to be visible and accessible to a multitude of clients anywhere in the world, which naturally means high competition and ‘bidding for jobs’ among the freelancers. Study data revealed that platform-based rating and ranking technologies contribute to the tendency of completing many tasks as quickly as possible. Work intensity was also fuelled by working for several clients at once and promising working on tighter deadlines than competitors. In general, the study authors brought up the notion of the weak structural power of workers vis-à-vis clients, with 80% of study respondents linking their work intensity to clients’ demands. In essence, in the pool of millions of online workers it is always possible to find someone, who will do the same job for less money and in less time.
The study authors also question the flexibility that remote gig work is supposed to bring. Indeed, in contrast to the idyllic image of doing a few gigs while travelling for instance, the common reality is instead about long unsocial working hours at home. As such, the notion of autonomy and flexibility is rather hypothetical and depends on the bargaining power of the worker (e.g. unique specialization, less economic pressures to earn money, high platform reputation etc.). In reality, the majority of gig workers find themselves in situations of weak structural power, and hence their working time is highly determined by clients. Troubling study data indicates that 54% of respondents lost sleep at night. Study respondents also reported a lack of job security and stability. Given the generally perceived oversupply of workers such platforms provide to its clients, 44% of respondents felt ‘easily replaceable’.
All in all, the remote gig economy does undoubtedly provide an opportunity, the gig. Yet, whether a worker can freely choose to take up this gig or is forced to fight for it in the absence of other relevant options, is a relevant question.