Tag Archives: Richard Murnane

Hiding from the Computers Part 6: What Is to Be Done?

In my last post, I argued that technology-driven productivity gains had to go somewhere, and the data suggested that the recipients were cognitive workers undertaking non-routine tasks (and thus safe from computers) and the holders of technology-based capital—generally the same set of people.

At this stage, it is worth stressing that the workplace is a little more complex than a simple grid of non-routine cognitive workers, routine cognitive workers, routine manual workers and non-routine manual workers as in the simplified models that underpin the job polarisation economic literature (click for larger image).

Job Polarization Autor jpeg

As the chart above shows (from a 2003 paper by Autor, Levy and Murnane), we are really talking about tasks as opposed to jobs. Every type of job will contain elements of the non-routine cognitive and the routine manual, even the most specialist, such as the non-routine cognitive profession of brain surgery, or the most routine, such as production-line work in a meat-packing factory.

What technology is doing is disassembling and then reassembling categories of jobs through extracting and then automating the routine elements. The semi-attended customer activated terminals (SACATs) that I covered in my third post in the series are not replacing any individual employee; what they are doing is taking a group of, say, 10 employees and stripping out a subset of their routine tasks until perhaps eight employees’ worth of non-routine cognitive and manual tasks are left.

Articles such as Farhad Manjoo’s “Humans 1, Robots 0: Cashiers Trump Self-Checkout Machines at the Grocery Store” in The Wall Street Journal completely miss the point. This is not a straight fight of human against machine over all aspects of a cashier’s work. It is a tussle between human and machine over individual tasks. And the very fact that self-checkouts exist and are proliferating means that the machines are winning individual task battles. Indeed, that is why U.S. Bureau of Labor Statistics show declining cashier numbers as I referenced in Part 3. So Manjoo’s article should really have been titled “Humans 5, Robots 1: Self-Checkout Machines Start Winning Battles Against Cashiers at the Grocery Store”.

Once we realise that we are really talking about aggregations of tasks when we are looking at the job market, it is easier to understand the chart below with which I began the series (click for larger image). Take ‘Office and Administrative Support’, for example. The workers who have some defence against technology are those who have concentrated on the non-routine cognitive aspects. But their jobs wills also change as technology keeps looking for ways to reformulate as routine processes bits of their work that currently appear non-routine. When enough of such tasks can be aggregated at the right technological price, a job will be eliminated and the remaining workers will have a different task set than that which existed before.

Probability of Computerisation jpeg

Faced with such a threat to the job market, I ended my last post with two possible policy prescriptions: 1) educate and train routine manual workers to become non-routine cognitive workers or 2) redistribute income from the cognitive workers to the non-routine manual workers. Actually, there are a couple more alternatives: 1) do nothing or 2) carve out more of human life that is not encompassed by the market economy.

So what will happen if governments do nothing? Continue reading

Hiding from the Computers Part 5: Follow the Money

In my last post, I explained how the academics behind the job polarisation literature (declining middle class) have given us a framework for understanding the emergence of very clear winners and losers in the modern workplace. Yet most of these scholars have refused to extend their analysis to justify any fear of technology-led mass unemployment.

According to these economists, the disappearing middle class —due to the death of white collar routine cognitive work carried out by office employees and blue collar routine manual work performed by factory employees—will reappear in cognitive non-routine or manual non-routine jobs. In so doing, these academics have generally wasted few opportunities to bash lump-of-labour advocates; that is, those people who believe that there exists a fixed pool of jobs that computers are draining away.

Nonetheless, there are cracks in the facade. For example, back in 2003 Paul Krugman (who has acted as a commentator on the job polarisation literature rather than an originator) was rock solid behind the consensus economic profession position as can be seen here. But by December 2012 we see a significant U-turn in a piece called Rise of the Robots in the New York Times.

However, I would say that the consensus, while shaky, is still in place. Moreover, for a high-voltage polemic against the lump of labour theory, I recommend you read “Are Robots Taking Our Jobs, or Making Them?” by Ben Miller and Robert Atkinson of the Information Technology and Innovation Foundation. Like all good polemics, the essay assembles all the evidence that supports their thesis of ‘don’t worry, be happy’ and omits any evidence that contradicts it.

Nonetheless, it is a good, comprehensive exposition of the consensus position of the economics profession that has dominated thinking for decades. Further, we can actually take their analysis, but subvert it somewhat to fit the facts of what is actually happening in the job market, and from there think about solutions.

Miller and Atkinson sum up their position thus:

Both history and scholarly analysis have clearly and consistently refuted the notion that increased productivity leads in the moderate to long term to higher unemployment. This is because rising productivity increases overall wealth, and in a competitive economy that increased wealth gets reallocated to create additional demand that requires new workers.

This is a bold statement that I would agree used to be true, but may no longer be valid. But before we look at any data, let’s focus on the mechanism that they claim supports their assertion. The next sentence is key: Continue reading