MAN V MACHINE
Is it even a contest any more?
Tech writer Timothy Lee used to be one of the most ardent techno-optimists. But he’s had a bit of a conversion, of late, and is now on the side of those who think tech progress is slowing.
Lee now broadly suggests that the inventions of tomorrow won’t be as world-changing as those of yesteryear.
The idea that tech will remake our lives, he writes, ‘‘has fallen flat in recent years, and I think it’s going to continue failing in the years to come.
‘‘There are a number of industries – with healthcare and education being the most important – where there’s an inherent limit on how much value information technology can add. Because in these industries, the main thing you’re buying is relationships to other human beings, and those can’t be automated.’’
Lee illustrates his argument with a chart of prices for various goods and services in the United States economy during the past four decades.
Continued techno-optimism
The chart shows manufactured goods have mostly fallen in price, while college and healthcare have soared. He reasons that these are difficult industries for technology to disrupt, since they rely so much on human-to-human interaction.
It’s a compelling argument, but I see a number of ways it could potentially be wrong. There’s a case to be made for continued techno-optimism.
First, Lee’s chart includes only final goods - the things that consumers buy. But there are a vast number of other goods that also use huge amounts of time and resources to create, such as backoffice services.
Technology that makes these thing cheaper will make the business world more efficient, just like cheaper steel makes manufacturing cars more efficient.
And it’s here, in the realm of white-collar work, where I believe the technologies bow under development have the potential to create huge productivity gains.
Much effort right now is being poured into machine learning and artificial intelligence, thanks in part to technical advances in the field, and also thanks to the availability of large amounts of data to train machines.
In a recent interview with Lee, venture capitalist Marc Andreessen explained why he thinks machine learning is the next transformative technology.
Essentially, machine learning allows machines to do your thinking for you. One of the earliest applications was recognising addresses on envelopes – instead of armies of humans sitting there doing the reading, the process could be accomplished with just one or two humans managing the machine readers. That’s a big productivity improvement.
Machines will dominate white-collar jobs
It isn’t hard to imagine fancier versions of that technology taking over many of the tasks we now spend our time and energy on.
Machines will evaluate business proposals for banks and other lenders. Machines will scan contractors and take bids. Machines will seek out targets for mergers and acquisitions. Machines will write most of the text of legal briefs. A machine might even write my columns someday.
In fact, many of the things that white-collar workers now spend hours on every day will be managed by machines. That will free up enormous amounts of time – machines don’t have to go to meetings or read emails.
Technology is fundamentally about saving labour, and most of the labor in the typical whitecollar work-day consists of thinking.
Just as factory tools and vehicles saved physical labour in the Industrial Revolution, smart machines will save more and more mental labour in the Information Revolution.
And since machine learning is still in its infancy, at least in terms of applications, it’s a good bet that this part of the Information Revolution isn’t over.
Humans might become redundant
Now, one might look at Lee’s graph and say ‘‘OK, fine and good, but which of the consumer goods on this graph will get cheaper as a result of all this automation? If the things we want don’t fall in price, who cares?’’
But as technology frees humans from the work necessary to produce the old things, humans will spend their time creating new things.
We just don’t yet know what most of those things will be.
Forty years ago, video games barely existed – now they’re a major consumption item. Who knows what we’ll desire four decades from now?
There’s also the possibility that many humans might become redundant.
If machine learning makes most of us obsolete, we will have to alter the structures of society to redistribute the massive abundance created, in order to make everyone’s leisure time as pleasant as possible.
This is the rise-of-the-robots scenario that lots of people are worried about, but it doesn’t have to be a scary thing, if society changes accordingly.
But whichever future occurs, it seems likely that the world of white-collar work is due for some much-needed disruption. That makes me a little more optimistic than Lee. – Bloomberg