Automation Shouldn’t Always be Automatic: Making Artificial Intelligence Work for Workers and the World

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The world is currently afflicted with excessive automation. It is excessive because it is not leading to increased productivity, nor creating new tasks for humans or increasing wages. 

Automation — the substitution of machines and algorithms for tasks previously performed by human hands and minds — is nothing new. Ever since the weaving and spinning machines that fueled the first Industrial Revolution, automation has often been an engine of economic growth. However, in the past it was part of a broad technology portfolio, and its potentially negative effects on labour were counterbalanced by other technologies boosting human productivity and employment opportunities. Not today.

The last two decades have witnessed rapid advances in automation technologies, but without the corresponding investments in those that complement humans. The result has been a decline in the labour share, stagnant wages and the disappearance of good jobs in many advanced economies, and especially in the United States.

Artificial intelligence (AI) — a broad technological platform with diverse applications and great promise — can be used to boost human productivity and create new human tasks and competencies in education, healthcare, engineering, manufacturing and elsewhere. But it could exacerbate the same negative trends if we use it exclusively for automation.

The COVID-19 pandemic is also contributing to this predicament as there are now more reasons for employers to look for ways to substitute machines for workers — and recent evidence suggests that they are already doing so.

The situation is bad when we look at it from the viewpoint of workers in the United States and Western Europe, where automation has made the biggest strides. But the real danger is for workers in the developing world. The global comparative advantage of developing nations, even in this age of technology, is their abundant and comparatively cheap labour. This is all the more true since much of the richer world has started aging rapidly and will continue to do so.


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The future of work is now. Digitalisation and globalisation have sparked radical shifts in how we live and work. The coronavirus (COVID-19) crisis has accelerated these beyond anything we could have imagined.

These changes raise essential questions about the precarity of our jobs, the support available if we're unable to work or retire, the skills we need for current and future jobs, the quality of those jobs, and what voice we have in shaping these outcomes.


The situation is bad when we look at it from the viewpoint of workers in the United States and Western Europe, where automation has made the biggest strides. But the real danger is for workers in the developing world. The global comparative advantage of developing nations, even in this age of technology, is their abundant and comparatively cheap labour. This is all the more true since much of the richer world has started aging rapidly and will continue to do so.

Viewed from this perspective, automation and AI are an “inappropriate technology” for much of the world: they are developed in advanced economies to economize on expensive labour by using cheap machines and algorithms (and, as I have pointed out, arguably doing so excessively). And yet in the developing world, labour is abundant and capital is scarce. The appropriate technology for countries such as Brazil, India or Mexico would not be using the AI platform to eliminate workers. Instead, it could make them more productive in a range of tasks and reduce their informality, so that they could be incorporated into the modern segments of these economies.

Despite the bewildering array of new machines and algorithms all around us, productivity growth in the West has been significantly lower in the last 20 years than in the decades that followed World War II.

The imbalance of technology, favouring automation and ignoring other technological opportunities, may also be partly responsible for the disappointing productivity performance of the advanced economies. Despite the bewildering array of new machines and algorithms all around us, productivity growth in the West has been significantly lower in the last 20 years than in the decades that followed World War II.

Excessive automation is not an inexorable development. It has arisen because researchers have focused on automation applications at the expense of other uses of technologies, and leading companies have built their business models on automation and reducing labour costs rather than broad-based productivity increases. But we can make different choices. While there is no consensus on exactly what brought us to this perilous state, we know of a number of factors that have pushed the economy towards greater automation.

Chief among these has been the transformation in the corporate strategies of tech giants. World technology is shaped by the decisions of a handful of American, European and Chinese companies with, in almost all cases, relatively small workforces. These huge corporations are responsible for more than two out of every three dollars spent globally on AI. Their vision — centred on the substitution of algorithms for humans — influences more than their own spending. It also affects what other companies prioritise, as well as the aspirations and focus of hundreds of thousands of young students and researchers specialising in computer and data sciences. There is of course nothing wrong with successful companies pushing their vision, but when this becomes the only game in town, we get into trouble. Past technological successes have more often than not been fueled by a diversity of perspectives and approaches, and without them we also risk losing our technological edge.

Also on the Forum Network: Don't Be Evil: How Big Tech Betrayed Its Founding Principles – and All of Us by Rana Foroohar

The dominance of the paradigm of a handful of companies has been exacerbated by the dwindling support for fundamental research from many governments, especially from the United States government. The transformative technologies of the 20th century, such as antibiotics, sensors, modern engines and the internet, have the fingerprints of the government all over them. The government funded and purchased these technologies and often set the research agenda. This is no longer the case.

Last but not least, government policy is encouraging automation excessively. For example, the United States tax system subsidises firms to use machines and algorithms instead of workers by giving big tax breaks to investments and heavily taxing labour.

A first step towards a course correction would be to eliminate the differential taxation of capital and labour both in the United States and in the rest of the West. A second step is to reevaluate the role of big tech companies in our lives, including in the direction of technology. This of course goes beyond debates about automation and AI, as it relates to the issue of limiting the size and the dominance of big tech companies. These measures can be strengthened with government R&D policies specifically targeting technologies that help human productivity and increase labour demand.

Yet none of this will be enough if the future of technology remains in the hands of a handful of Western companies. The developing world needs to be at the table and have a voice in how promising new technologies will be used — not just for profits, not just for the very skilled engineers in the United States, Europe and China, but for its billions of workers around the globe.

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Daron Acemoglu

Elizabeth and James Killian Professor of Economic, Massachusetts Institute of Technology

Daron Acemoglu is Elizabeth and James Killian Professor of Economics in the Department of Economics at the Massachusetts Institute of Technology. He has received a BA in economics at the University of York, 1989, M.Sc. in mathematical economics and econometrics at the London School of Economics, 1990, and Ph.D. in economics at the London School of Economics in 1992.

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