Key takeaways from the Blum-Brookings roundtable on the future of work in the developing world

brookings

 

Last August, Giraffe was privileged to attend the 13th Blum-Brookings roundtable on global poverty. Each year, a small, select group of policy-makers, investors, NGOs, academics and entrepreneurs gathers for a focused discussion on a theme related to poverty alleviation. The theme for 2016 was the future of work in the developing world.

 

Participants included former US secretary of state Madeleine Albright, former President of Ireland Mary Robinson, former Prime Minister of New Zealand and UN Secretary General candidate Helen Clark as well as the CEOs and founders of several startups operating in the employment and education space.

 

The diverse combination of attendees made for a fascinating discussion on a range of issues pertaining to the very real crisis of unemployment, skills shortage and poverty in the developing world. The ensuing dialectic combined insight from academic thought leadership, policy frameworks and the reality on the ground in specific markets. Below are some of the key questions explored and the consequent takeaways from our perspective:

 

The jury is out on the extent of the impact of automation and AI on jobs- and how to manage it

 

Automation and the rise of AI threatens to replace jobs in both developed and developing world. Will this result in mass unemployment? Will jobs that have been offshored to the developing world (eg: manufacturing in China) be re-shored and conducted by robots? How should we respond to these threats? It is unclear as to the extent of the impact of automation on unemployment: history has shown that automation has actually created jobs- by enabling greater productivity eg: the invention of the loom made knitters redundant but the subsequent growth in the production of garments increased the need for garment sales people and delivery workers. However the rise of AI suggests that the trend might not apply this time around- because automation will replace a much broader range of roles- including salespeople and delivery drivers. Varying estimates suggest that anything between 10% and 47% of jobs in the US may be replaced by robots, with the figure reaching as high as 77% in developing countries. In anticipation of this, several parties have proposed that a universal basic income (UBI) be applied to people whose jobs become redundant. However, tax revenues in their current form will not be sufficient to fund this. Alternative sources of funding are not yet clear. However, a fairly unanimous view was that no matter how much automation and robotics proliferate, there will always be a need for human interaction- the question is how much and in which fields. The risk, however, is increased inequality, with wealth accruing to the owners of AI technology and away from everywhere else- further confounding the UBI solution.

 

The sharing economy can unlock value in large sectors of society that have hitherto faced constraints

 

Contrasting with the threat of unemployment by AI is the recent surge in the growth of the sharing economy- bringing with it significant opportunities for unlocking underutilised resources. Uber and Airbnb are probably the most famous examples of sharing economy models. In both cases, value from partially utilised assets is unlocked by connecting them with aggregated demand. How can the sharing economy unlock value in the developing world? In the developing world, this concept can bring many benefits. Specifically, key sections of society remain underutilised or unproductive for, eg: most educated women in Pakistan are not in the formal workforce due to cultural reasons. However, the advent of freelancing platforms such as Upwork and Empower Pakistan facilitate working from home and flexible working, enabling women to work from home in a manner that suits them. This unlocks productivity, creates employment and drives growth.

 

Job matching platforms can have a powerful impact on reducing unemployment- but alone are not sufficient

 

Job matching platforms have been shown to reduce frictional employment and significantly streamline the recruitment process. How can such platforms be used to reduce unemployment? Can they help address the shortage of skilled workers in the developing world? A fundamental change in the developing world within the last 5-7 years has been the dramatic growth of mobile- specifically mobile internet penetration. The ubiquity of mobile in developing markets brings with it the opportunity to provide low-medium income jobseekers access to and visibility of job vacancies that they would otherwise never have had access to. Furthermore, mobile acts as a tool by which to capture jobseeker CVs, contact potential candidates and even schedule interviews- effectively streamlining the entire recruitment process. As such, the potential for such platforms to reduce frictional unemployment is significant. They can also help reduce the cost of recruitment for employers, and by reducing the barriers to hiring, can actually increase the number of jobs available. They do not, however, directly impact key drivers of job creation such as economic growth, labour market deregulation or education. To address these key issues, job matching platforms should be used in conjunction with other approaches.

 

Focus should be placed on upskilling workers to perform jobs that are in demand

 

Skills gaps have always existed in the developing world, thanks to poor traditional education systems and local industries dominated by low-skilled work. Developing countries are also particularly susceptible to automation because the workforce is disproportionately focused on blue collar or low-end white collar jobs. Given the looming threat of automation of jobs, on what skills and education should developing countries focus? What are the most promising models of education and upskilling? Two key answers emerged from the discussion: massive open online courses (MOOCs) and targeted upskilling based on demand. Whilst MOOCs have gained currency in developed world, their effective use remains the preserve of those who already have higher education from traditional methods. As such, they are not a panacea that will solve the educational ills of the developing world. They can, however, enable ‘train the trainer’ type models where, for example, university graduates in Ghana can use them to upskill themselves and then convey that knowledge to students. The second approach- targeted upskilling- involves using the data collected by job matching platforms to surgically identify specific demand for skills where there is a shortage of supply. In doing so, steps can be taken to upskill people with specific skills for which clear demand is known. In this way, job matching platforms can play a key role in education as well as matching.

 

Conclusions and key actions

 

Labour markets in the developing world are often informal, unregulated and vulnerable to exploitation. Whilst automation threatens to exacerbate this, the sharing economy promises to mitigate it- by empowering people to become entrepreneurs. And education technology promises to help with upskilling. Combined with the efficiency of job matching platforms, labour markets may indeed remain mobile and productive.

 

Donors, NGOs and aid agencies spend billions of dollars annually on job-creating initiatives in the developing world. However, there is limited evidence to suggest that sustainable impact is generated. What steps should be taken to enhance the impact? Some of the key takeaways from our perspective are:

 

  1. Automation is inevitable but its impact cannot be forseen; to adequately prepare, universal basic income needs to be explored, especially funding models
  2. There is a latent workforce in developing economies that should be leveraged through promoting sharing economy models
  3. There needs to be a joint effort between job matching, demand forecasting and skills development- in order to holistically address the labour challenges in the developing world
  4. MOOCS can be used to empower teachers to teach; they should be harnessed to target the specific needs of developing countries- perhaps in a joined effort with job matching platforms
  5. Large sections of the workforce that are working in dying industries will need to be retrained; governments and NGOs should identify the potential movements and work to mitigate pre-emptively by partnering with education providers
  6. Donors, NGOs and private sector need to collaborate together to address specific market failures- a silo approach is not likely to generate meaningful impact

 

The full writeup of the roundtable by The Brookings Institution, along with in depth analysis of the topics can be found here

Uncategorised Leave a comment

Leave a Reply

Your email address will not be published.