ATMs and Asilomar
The ATM automation meme
[image error]
In an engaging TED talk recorded in September 2016, economist David Autor points out that in the 45 years since the introduction of Automated Teller Machines (ATMs), the number of human bank tellers doubled from a quarter of a million to half a million. He argues that this demonstrates that automation does not cause unemployment – rather, it increases employment.
He says ATMs achieved this counter-intuitive feat by making it cheaper for banks to open new branches. The number of tellers per branch dropped by a third, but the number of branches increased by 40%. The ATMs replaced a big part of the previous function of the tellers (handing out cash) but the tellers were liberated to do more value-adding tasks, like selling insurance and credit cards.
[image error]
This story about ATMs has become something of a meme, popular with people who want to believe that technological unemployment is not going to be a thing.
There are three problems with this account. One is that the numbers don’t seem to add up: if you increase the number of branches by 40% and reduce the number of tellers per branch by a third, you don’t get double the number of tellers
It was deregulation, not ATMs
The second problem is that it is not true. The increase in bank tellers was not due to the productivity gains afforded by the ATMs. According to an analysis by finance author Erik Sherman, the increase was mostly due instead to a piece of financial deregulation, the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994, which removed many of the restrictions on opening bank branches across state lines. Most of the growth in the branch network occurred after this Act was passed in 1994, not before it.
[image error]
This explains why teller numbers did not rise in the same way in other countries during the period. In the UK, for instance, retail bank employment just about held steady at around 350,000 between 1997 and 2013, despite significant growth in the country’s population, its wealth, and its demand for sophisticated financial services.
The third problem with Autor’s ATM story is that it is unnecessary. No-one is arguing that previous rounds of automation caused lasting unemployment. In 1800, US farms employed 80% of all American workers. In 1900 it was down to 40%, and by 2000 it was below 2%. This was due to automation – or to be more precise, to mechanisation. No doubt the shift was painful for many of the farm workers involved, but in the medium and long term they ended up doing better-paid, safer and more interesting work in towns and cities. And they – or their children – got an education to make sure they could do the new jobs.
It really could be different this time
The present worry about technological automation is that a new wave is coming, and it could be different this time. Previous rounds of automation have involved machines substituting for human and animal muscle power. Horses were put out of a job permanently because they had nothing to offer beyond muscle power – their population in the US went from 25m in 1900 to 2 million today.
[image error]
We humans, by contrast, did have something else to offer: our cognitive skills. This is what the machines, powered by AI, are coming for this time. This time we will see a wave of cognitive automation.
We have had cognitive automation in the past: the role of secretaries has largely been automated by desktop computers. But it hasn’t really got started yet: after all, AI wasn’t very effective until machine learning was successfully applied to it, starting around 2012. Now machines can recognise images better than you can (including faces, which is one of humanity’s special talents), they are overtaking you in speech recognition, and they are catching up fast in natural language processing. And unlike you, they are improving at an exponential rate.
No-one knows for sure what the impact of this will be. But to declare at this early stage that widespread and lasting unemployment will not happen – just because it hasn’t happened in the past – is complacent and dangerous.
[image error]
