By Juan R. de Laiglesia and Caroline Tassot, OECD Development Centre

Wolfgang von Kempelen built an impressive chess-playing automat in 1770 known as the “mechanical Turk.’’ Dressed in its fancy turban, the “Turk’’ would move the pieces on the chessboard, playing (and beating) such notables as Napoleon, Catherine the Great and Benjamin Franklin. The unfortunate use of this national stereotype (which we in no way support) was meant to enchant imaginations with exoticism in the face of the automat’s extraordinary prowess in 18^th century Europe. As suspected, the automat was an elaborate hoax, although this was discovered only much later. Several chess grandmasters operated it during its rather long history until its demise in a Philadelphia fire in July 1854.

What’s the relevance? In 2005, Amazon’s catalogue started to get unwieldy, and the Internet company realised that it needed better tagging on its items for sale. For example, if one searched for a crimson shirt, shirts labelled “red” should be displayed as well as those tagged as “crimson.” Even Amazon faced tasks that computers could not do more quickly and accurately than people. 

So, Amazon launched its version of the “mechanical Turk.’’ The “Amazon Mechanical Turk” or “Mturk,” as it is known, provides solutions by splitting a job into very small tasks (called Human Intelligence Tasks or HITs) that can be “crowdsourced” usually for a small fee (sometimes a very small fee). The “Mturk’’ can label your pictures, sort or categorise data, or even generate a database for further computer treatment. This is, according to Amazon, how DARPA (the Defense Advanced Research Projects Agency in the United States) generated a database to machine-translate colloquial Arabic.

Like Amazon, many companies in recent years have become prominent actors in what is called the gig economy. The gig economy is made up of companies providing digitally enabled marketplaces for just-in-time services. These marketplaces connect buyers and sellers as well as vet providers and customers, and they often handle payments too. The gig economy is based on work contained in bite-sized tasks, compared to transactions with business providers who employ staff on a more or less regular basis. The phenomenon has become internationalised because of both the model’s replication for local purposes worldwide as well as the globalisation of marketplaces: 20% to 30% of “turkers’’ were reportedly Indian in 2009, earning on average USD 1.58 per hour ^[1] , although the market and the system have changed in recent years, restricting foreign participation.

In developed and developing countries, the surge in the gig economy is causing a stir. Transportation services are at the forefront. Whether lending a drill or providing a ride, new services are emerging with potentially tremendous consequences for societies as a whole. How?

In terms of benefits, the gig economy offers a wide range of economic opportunities. Economic opportunities arise when previously idle capital, even human capital, is activated. Otherwise unemployed individuals could find work through these platforms. The gig economy also expands markets, providing transportation services locally or offering global work platforms for “turkers.’’ Finally, the gig economy offers important opportunities thanks to its use of geolocalisation. This feature is being used widely by private companies and apps to create new markets or activate capital. Such geolocalisation features also could be used to increase the efficiency of public services.

The gig economy, on the other hand, poses major questions for the world of work. It makes labour a commodity and challenges the economic and social value of the employment relationship.  The gig economy has no employment relationships, only commercial transactions. This is an issue for skills formation, for mechanisms to provide and finance social protection, and for the social inclusion value of work. Some may view this commodification of tasks and services as particularly relevant for development models that side-step manufacturing and transition straight from agriculture, where casual work is the norm, to services. Others may argue that gig-economy jobs reflect a higher formalisation level than typical informal jobs in developing countries. In India, for example, trucking aggregators have flourished: TruckSuvidha, Porter, Truckmandi or GogoTruck provide transportation services through gig-economy platforms. In an atomised and unstructured market, like the one for Indian transport services, transactions made via aggregators are more visible and traceable than the average. Therefore, they provide an avenue to formalise, rather than informalise, the market.

We actually know little about the gig economy, how its development differs across sectors and countries, and what its ultimate impact will be. And we have little certainty about the validity of what we do know. What is clear is that an increasing share of the working population earns income via online platforms, at least in the United States. According to a JP Morgan report, 1% of U.S. adults earn money through the gig economy in any given month, a tenfold increase since late 2012. Investments into gig-economy actors have surged: Uber, the ride hailing platform, is the world’s most valuable start-up, worth over USD 60 billion; its Chinese competitor, Didi Chuxing, recently raised USD 7 billion from investors and lenders. The steady surge worldwide in Internet access, especially mobile Internet, increases opportunities for individuals to use gig-economy platforms to provide or purchase services. Quantifying the magnitude – and hence, potentially modelling the impact – of the gig economy is at this stage mainly speculative.

All this raises a number of issues for policy makers. For instance, how should they respond to the growing phenomenon of the gig economy? Would policy responses differ between OECD and non-OECD countries?

To answer these questions, we have more to explore and discover. We have an opportunity to create a new dialogue – and conduct further analysis and research – to build on what we know and suggest a framework for the way forward. Looking at what the gig economy means specifically for developing countries could offer fresh perspectives on advancing sustainable and inclusive development.

[1] The figure is from Ross, Irani, Silberman, Zaldivar and Tomlinson (2010). The authors have since identified a number of issues with this paper.