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Archive for January 2018

The compelling case for technological optimism

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PortableComputers

In September last year, I visited the Computer History Museum in Mountain View, California. The museum is dedicated to preserving and presenting all aspects of the computer revolution, from its roots in the twentieth century to self-driving cars today. What is remarkable is to observe, while walking through the more than 90000 objects on display, the profound change in technology over the last three decades. The mobile computing display, I thought, summarised this change best, showing the first laptop computers of the 1980s (see image above) to a modern-day iPhone. But what also became clear from the exhibitions was that those ‘in the know’ at the start of the revolution were right about the transformational impact of computers, but almost certainly wrong about the way it would affect us.

We are now at the cusp of another revolution. Artificial intelligence, led by remarkable innovations in machine learning technology, is making rapid progress. It is already all around us. The image-recognition software of Facebook, the voice recognition of Apple’s Siri and, probably most ambitiously, the self-driving ability of Tesla’s electric cars all rely on machine learning. And computer scientists are finding more applications every day, from financial markets – Michael Jordaan recently announced a machine learning unit trust – to court judgements – a team of economists and computer scientists have shown that the quality of New York verdicts can be significantly improved with machine learning technology.  Ask any technology optimist, and they will tell you the next few years will see the release of new applications that we currently cannot even imagine.

But there is a paradox. Just as machine learning technology is taking off, a new NBER Working Paper by three economists, Erik Brynjolfsson, Chad Syverson and Daniel Rock affiliated to MIT and Chicago, show something peculiar: a decline in labour productivity over the last decade. Across both the developed and developing world, growth in labour productivity, meaning the amount of output per worker, is falling. Whereas one would expect that rapid improvements in technology would boost total factor productivity, boosting investment and raising the ability of workers to build more stuff faster, we observe slower growth, and in some countries even stagnation.

TrendGrowthRates

This has led some to be more pessimistic about the prospects of artificial intelligence, and in technological innovation more generally. Robert Gordon, in his ‘The Rise and Fall of American Growth’, argue that, despite an upward shift in productivity between 1995 and 2004, American productivity is on a long-run decline. Other notable economists, including Nicholas Bloom and William Nordhaus, are somewhat pessimistic about the ability of long-run productivity growth to return to earlier levels. Even the Congressional Budget Office in the US has reduced its 110-year labour productivity forecast, from 1.8 to 1.5%. On 10 years, that is equivalent to a decline of $600 billion in 2017.

How is it possible, to paraphrase Robert Solow in 1987, that we see machine learning applications everywhere but in the productivity statistics? The simplest explanation, of course, is that our optimism is misplaced. Has Siri or Facebook’s image recognition software really made us that more productive? Some technologies never live up to the hype. Peter Thiel famously quipped: ‘We wanted flying cars, instead we got 140 characters’.

Brynjolfsson and co-authors, though, make a compelling case for technological optimism, offering three reasons for why ‘even a modest number of currently existing technologies could combine to substantially raise productivity growth and societal welfare’. One reason for the apparent paradox, the authors argue, is the mismeasurement of output and productivity. The slowdown in productivity of productivity in the last decade may simply be an illusion, as most new technologies – think of Google Maps’ accuracy in estimating our arrival time – involve no monetary cost. Even though these ‘free’ technologies significantly improve our living standards, they are not picked up by traditional estimates of GDP and productivity. A second reason is that the benefits of the AI revolution are concentrated, with little improvement in productivity for the median worker. Google (now Alphabet), Apple, and Facebook have seen their market share increase rapidly in comparison to other large industries. Where AI was adopted outside ICT, these were often in zero-sum industries, like finance or advertising. A third, and perhaps most likely, reason is that it takes a considerable time to be able to sufficiently harness new technologies. This is especially true, the authors argue, ‘for those major new technologies that ultimately have an important effect on aggregate statistics and welfare’, also known as general purpose technologies (GPT).

There are two reasons why it takes long for GPTs to be seen in the statistics. It takes time to build up the stock necessary to have an impact on the aggregate statistics. While mobile phones are everywhere, the applications that benefit from machine learning are still only a small part of our daily lives. Second, it takes time to identify the complementary technologies and make these investments. ‘While the fundamental importance of the core invention and its potential for society might be clearly recognizable at the outset, the myriad necessary co-inventions, obstacles and adjustments needed along the way await discovery over time, and the required path may be lengthy and arduous. Never mistake a clear view for a short distance.’

As Brynjolfsson and friends argue, even if we do not see AI technology in the productivity statistics yet, it is too early to be pessimistic. The high valuations of AI companies suggest that investors believe there is real value in those companies, and it is likely that the effects on living standards may be even larger than the benefits that investors hope to capture.

Machine learning technology, in particular, will shape our lives in many ways. But much like those looking towards the future in the early 1990s and wondering how computers may affect our lives, we have little idea of the applications and complementary innovations that will determine the Googles and Facebooks of the next decade. Let the Machine (Learning) Age begin!

An edited version of this article originally appeared in the 30 November 2017 edition of finweek.

How religion shapes an economy

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Harare billboard

Source: Her Zimbabwe

Drive around Harare and you will notice something very peculiar. Billboards across the city do not advertise the latest car model or data bundle or washing powder. In Harare, by contrast, almost every billboard advertises church services. They all follow a precise formula: next to the photo of the charismatic spiritual leader is the date of the event and a promise, best summarised in this example: ‘Freedom from poverty/freedom from disease/freedom from barrenness.’ The implication: join us to improve your material welfare.

On my visit last year, I spoke to several university students who attend these services. One told the incredible story of a pastor who arrived one Sunday morning at his church with a truck full of bricks. These were ‘blessed bricks’, he proclaimed; one of them built into your house would, according to the good pastor, alleviate you from material want. According to the student, he sold each of the 10 000 bricks on the truck for $10. The last few ones even fetched as high as $50. Do the math. It would seem that at least one person’s material welfare did improve significantly.

This and similar stories by the students reminded me of something that had happened five centuries ago. By the 16th century, the abuse of indulgences – a payment to reduce the punishment for sins – had become a serious problem that the Catholic Church in Europe recognized but was unable to restrain effectively. A young German professor of theology, Martin Luther, rejected the belief that freedom from God’s punishment for sin could be purchased with money, and penned his Ninety-Five Theses to the door of All Saints’ Church in Wittenberg on 31 October 1517, a date now considered the start of the Protestant Reformation.

Luther’s movement, and the ones it would kindle elsewhere, heralded an era of prosperity across Northern Europe. The Catholic city-states of Southern Europe – think Venice – were some of the wealthiest in 14th and 15th century Europe. But by the 17th and 18th centuries, these had been supplanted by cities in the Protestant North, notably in Holland and then England.

Many scholars have linked the Protestant Reformation – at least indirectly – to this reversal of fortunes. German sociologist Max Weber, for example, argued that the Reformation encouraged the ethics of hard work, thrift and efficiency, and that this resulted in a change in savings behaviour by the followers of the new religion, with consequences for investment and growth. Others highlighted the impact the new religion had on literacy and education, as it emphasized adherent’s ability to read and write, and that this channel of causation was what propelled the North forward. But proving these theories empirically was difficult.

A new NBER Working Paper by Davide Cantoni, Jeremiah Dittmar and Noam Yuchtman posit another channel and finds empirical support for it. The authors assemble a new, highly disaggregated dataset on the degrees received by German university graduates for more than 2000 German towns in the period following the Reformation. They then split the sample in two: those students that qualify with religious degrees, and those with secular degrees. The authors are also able to identify the occupations of these German graduates, and split the occupational sample in two: those who find work as monks and priests, and those who find work in administration and the private sector.

The results are remarkable. In those areas that experienced the Reformation, two things happen. First, the Protestant university students increasingly studied secular subjects, especially degrees that prepared students for public sector jobs, rather than church sector-specific theology. Graduates of Protestant universities, in contrast to universities that remained Catholic, also increasingly took secular, especially administrative, occupations.

Second, the Reformation affected the sectoral composition of fixed investment. In Protestant regions, new construction shifted from religious toward secular purposes, especially the building of palaces and administrative buildings, which reflected the increased wealth and power of secular lords.

In short, the Protestant Reformation changed the preference for physical and human capital investment from unproductive to more productive activities. Importantly, this reallocation was not caused by preexisting economic or cultural differences. The interpretation is therefore that it was the Reformation, and not some other underlying factor, that resulted in this shift to the secularization of graduate degrees and the workforce.

This had profound long-run consequences. With more students studying secular subjects and more of them finding jobs in the public or private sector (instead of the religious sector), a process of cultural and intellectual change was set in motion that culminated, ultimately, in the enlightenment, the scientific revolution and modern economic growth.

Which brings us back to the pastors of Zimbabwe. In a country devoid of private sector opportunities, religious entrepreneurship is a popular calling for charismatic individuals. But if the brightest young minds choose professions in the religious sector – and the little surplus capital that there is, are used to fund mega-church buildings (as you will find when you drive around Harare) – then Zimbabwe is experiencing exactly the opposite of the Protestant Reformation. Selling ‘blessed bricks’ is the modern equivalent of the sixteenth-century indulgences sold for salvation.

The result? Productive investments in human and physical capital becomes investments in unproductive activities. The circle of poverty is strengthened, exploited by religious entrepreneurs who themselves profit from others’ hardship. Are we returning to the Middle Ages, or will our generation’s Martin Luther rise up?

*An edited version of this first appeared in Finweek magazine on 16 November 2017.

Written by Johan Fourie

January 4, 2018 at 10:57