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Human development in recent decades has been accompanied by rapid changes in technology and an increasing proliferation of digitized devices and services.

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These technologies can be used to boost productivity and improve livelihoods. AI, for example, combined with robotics can transform production and business processes. 3D printing allows faster and cheaper low-volume production and rapid, iterative prototyping of new products.


Humans and Machines at work


Innovation with equity


Market and profit concentration


Technological change is thus interlinked with structural changes and international trade

Technologies affecting inequality through jobs, wages and profits

Technologies can change how people work and produce goods and services, thus changing how wealth is created and distributed. In long chain reactions through an economy, technological change creates, destroys and transforms jobs producing winners and losers. Technological change also affects wages and profits, which in turn widens gaps within and between wage earners and the owners of capital


Risks of unemployment and increasing income divides

How do frontier technologies make the processes described above different from the past? In principle, there is no difference. Similar disparities have occurred before. Each technological revolution had its winners and losers requiring societies to create new institutions to spread wealth more evenly and re-establish social cohesion.


The gig economy and an erosion of labour rights

It is less clear what impact the gig economy will have on income inequality. Much will depend on whether the gig workers are poor people who would otherwise be unemployed, or middle class people looking for a small additional income. Inequality will also rise if these jobs replace better paid ones or full-time jobs with part-time ones, or if profits grow faster than salaries.


AI and global economic Inequalities

Although competing for global dominance in AI, both countries now have digital platforms that gather massive amounts of data from global user bases. Of the total, China would take $7 trillion and North America $3.7 trillion. On this scenario, these countries would leave the rest of the advanced industrialized economies behind.


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