Accelerating AI ‘space race’ — what it means for jobs

why AI is moving up the agenda.

“Potential international rivals in the AI market are creating pressure for the US to compete for innovative military AI applications. China is a leading competitor in this regard, releasing a plan in 2017 to capture the global lead in AI development by 2030,” the report noted. Russia is also active in military AI development, with a primary focus on robotics.”

Ideological rivalries between Russia and the US propelled man to the moon in the 60s. It was a space race between communists and capitalists, as each side tried to demonstrate the superiority of their systems of governance. But being a leader in AI is arguably much more significant than the — largely symbolic — race to the moon.

Any country that becomes the global leader in AI will have real advantages here on Earth. The infrastructure of the future is being constructed on the technological developments that are being made today. Owning that infrastructure will bring great power and influence.

When the military gets involved in prioritising a technology, it is usually a sign that its development will accelerate before spilling over into everyday life. World War I gave us blood transfusions, World War II the rocket jet. GPS, which runs your car satnav, was a US Cold War military project. They all owe their existence to military research caused by rivalries between countries.

Outside the military, a recent study by the World Economic Forum (WEF) concluded that the workforce was already automating faster than it had previously expected. The WEF now expects machines and lines of computer coding will displace 85 million jobs over the next five years.

A two-year study from McKinsey claimed that by 2030 AI and robots could replace up to 30 per cent of the world’s current workforce. The consultancy concluded that — in terms of scale — job losses caused by the automation revolution could rival the “green revolution” in agriculture and the automation of manufacturing in Western nations in the 20th century. Of course, peddling doom always grabs attention. Humans have been telling each other stories of looming disasters and potential Armageddons for centuries. But human ingenuity found the solutions that solved these problems.

Predictions of mass starvation because of overpopulation — as first popularised by Reverend Thomas Malthus in his 1798 pamphlet: An Essay on the Principle of Population — have never come to pass. Food production managed to keep up with the rising global population because human intelligence solved the problem in the agricultural green revolution. We developed intensive farming and irrigation techniques and focused on high-yielding crops.

These are less visible and spread across different sectors, and are likely to be numerous. Clearly, the lower skilled a job is, the higher the risk of automation — but one reassuring thing we have been taught by the Covid-19 pandemic is that governments worldwide will not allow such mass unemployment to materialise because of the civil and economic strife that it would cause.

Even the US, the world’s torch carrier for free-market capitalism, passed the Coronavirus Aid, Relief and Economic Security Act earlier this year to provide government assistance to people who lost their jobs because of the crisis. So, most people shouldn’t be too worried about the threat of unemployment caused by robots taking their job away.

There are many other examples of humans heading off doomsday-like scenarios. Peak Oil proponents claim that global crude oil production was about to hit its maximum rate, after which production would plunge and the price of energy would soar.

Today the world is awash with oil as new extraction techniques help keep fields alive — and the development of “green” alternative energy supplies means the transition away from oil-produced energy is well under way. Once again, human ingenuity solved a problem that doom peddlers argued was unsolvable. Fears over AI causing mass global unemployment are all a bit overcooked.

It’s very easy to identify sectors where jobs will be lost. The most susceptible to automation include physical activities in predictable environments, such as operating machinery or flipping burgers at a fast-food outlet. Data processing is another area where machines could do work better and faster. However, it is almost impossible to get a handle on how many jobs these new technologies will create.