Technological advances related to the fourth industrial revolution – including artificial intelligence – allow the automation of an increasingly big range of processes in increasingly interactive and complicated ways. These advances will likely give rise to many opportunities for economic and social development in developing countries, for example by increasing food production.

But the brand new technologies also involve necessary risks, which have special significance in developing countries. They may construct upon and exacerbate existing inequalities – each inside developing countries in addition to between developing and more developed regions.

Three of those inter-related risks are worsening unemployment, increasing concentration of economic power and wealth, and the spread of biases in influential algorithms. They will manifest in alternative ways and require different responses in diverse contexts. A cross-cutting problem is that too few developing country governments are giving these risks serious attention.

Risk 1: Worsening unemployment

The concern that latest technologies – especially artificial intelligence – will result in widespread job losses has been widely discussed. Of course, the fear that latest technologies replace employees is an old one. But it’s been identified that historically latest technologies have often given rise to more latest jobs than those which were automated away.

What’s perhaps different now could be that the brand new, interconnected digital technologies will likely have a broader and more far-reaching array of abilities. And so the prospect of recent sorts of jobs may be diminished or limited to increasingly sophisticated domains, similar to machine learning.

In addition, latest technologies are actually not only replacing jobs, but also they are enabling the disruption and restructuring of entire industries. For instance, Uber has already pulled the rug from underneath the traditional taxi industry in lots of places. Imagine the possible consequences of Uber’s shift to driver-less cars.

Lower labour costs in lots of developing countries mean that investments in job replacing technologies shall be lower. But other features of developing countries’ contexts increase the possible severity of this risk.

First, the dearth of effective education systems and skills in countries like South Africa will make it tougher for people to be retrained for the technology intensive latest jobs that can grow to be available. Secondly, all governments are struggling to grapple with the implications of recent technologies and associated latest business models. This struggle is especially strong in developing country governments. The case of Uber in South Africa reflects this.

Risk 2: Increasing concentration of wealth

Many developing countries are characterised by high levels of inequality inside their populations. Elites inside these countries shall be more more likely to make use of AI and other latest technologies. This will further increase returns to capital widening the gap between elites’ productive capability and that of everyone else.

An analogous effect is probably going at a world level. It’s no coincidence that Russia’s President Vladimir Putin has identified AI as the brand new terrain for global competition between nations.

New technologies’ benefits for capital usually are not just attributable to increasing productivity, but in addition because they permit latest business models which will control and even dominate entire sub-sectors and stifle competition. For instance, it could grow to be possible for a single company to control large fleets of automated vehicles in a number of large areas.

Again, much will depend upon whether states can sustain with these developments and respond effectively. Particular attention will have to be paid to mental property and competition law. For instance, the strict enforcement of mental property rights for AI algorithms may support increasing economic concentration. It’s also likely that national governments can have less and fewer influence over such decisions and trends. Even so, many developing country governments usually are not giving these developments their due attention.

Risk 3: Bias baked into algorithms

Finally, the AI algorithms which can be on the centre of the fourth industrial revolution will reflect and perpetuate the contexts and biases of those who create them. Difficulties faced by voice recognition software in recognising particular accents are a comparatively innocuous example. Of course, the promise is that AI will enable such systems to learn to deal with such issues. But the training process itself is likely to be influenced by racial, gender, or other prejudices.

AI algorithms are developed almost entirely in developed regions. Thus they could not sufficiently reflect the contexts and priorities of developing countries. Ensuring that AI algorithms are appropriately trained and adapted in several contexts is an element of the required response. It could be even higher if developing countries grow to be more engaged in the event of recent technological systems from the get-go.

Governments must act

These three risks require that academics, businesses, and civil society actors attend to the role of recent technologies in developing countries. But a special responsibility lies with governments. For probably the most part, they appear to be distracted.

Governments should fastidiously assess the above risks of their national context after which establish corresponding policies and programs. This includes national skills development and work placement platforms, mental property and competition policies, and native technology adaptation and development.

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