Tag: automation

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The AI revolution

Artificial intelligence is having a profound effect on economies and society. From production, to services, to healthcare, to pharmaceuticals; to education, to research, to data analysis; to software, to search engines; to planning, to communication, to legal services, to social media – to our everyday lives, AI is transforming the way humans interact. And that transformation is likely to accelerate. But what will be the effects on GDP, on consumption, on jobs, on the distribution of income, and human welfare in general? These are profound questions and ones that economists and other social scientists are pondering. Here we look at some of the issues and possible scenarios.

According to the Merrill/Bank of America article linked below, when asked about the potential for AI, ChatGPT replied:

AI holds immense potential to drive innovation, improve decision-making processes and tackle complex problems across various fields, positively impacting society.

But the magnitude and distribution of the effects on society and economic activity are hard to predict. Perhaps the easiest is the effect on GDP. AI can analyse and interpret data to meet economic goals. It can do this much more extensively and much quicker than using pre-AI software. This will enable higher productivity across a range of manufacturing and service industries. According to the Merrill/Bank of America article, ‘global revenue associated with AI software, hardware, service and sales will likely grow at 19% per year’. With productivity languishing in many countries as they struggle to recover from the pandemic, high inflation and high debt, this massive boost to productivity will be welcome.

But whilst AI may lead to productivity growth, its magnitude is very hard to predict. Both the ‘low-productivity future’ and the ‘high-productivity future’ described in the IMF article linked below are plausible. Productivity growth from AI may be confined to a few sectors, with many workers displaced into jobs where they are less productive. Or, the growth in productivity may affect many sectors, with ‘AI applied to a substantial share of the tasks done by most workers’.

Growing inequality?

Even if AI does massively boost the growth in world GDP, the distribution is likely to be highly uneven, both between countries and within countries. This could widen the gap between rich and poor and create a range of social tensions.

In terms of countries, the main beneficiaries will be developed countries in North America, Europe and Asia and rapidly developing countries, largely in Asia, such as China and India. Poorer developing countries’ access to the fruits of AI will be more limited and they could lose competitive advantage in a number of labour-intensive industries.

Then there is growing inequality between the companies controlling AI systems and other economic actors. Just as companies such as Microsoft, Apple, Google and Meta grew rich as computing, the Internet and social media grew and developed, so these and other companies at the forefront of AI development and supply will grow rich, along with their senior executives. The question then is how much will other companies and individuals benefit. Partly, it will depend on how much production can be adapted and developed in light of the possibilities that AI presents. Partly, it will depend on competition within the AI software market. There is, and will continue to be, a rush to develop and patent software so as to deliver and maintain monopoly profits. It is likely that only a few companies will emerge dominant – a natural oligopoly.

Then there is the likely growth of inequality between individuals. The reason is that AI will have different effects in different parts of the labour market.

The labour market

In some industries, AI will enhance labour productivity. It will be a tool that will be used by workers to improve the service they offer or the items they produce. In other cases, it will replace labour. It will not simply be a tool used by labour, but will do the job itself. Workers will be displaced and structural unemployment is likely to rise. The quicker the displacement process, the more will such unemployment rise. People may be forced to take more menial jobs in the service sector. This, in turn, will drive down the wages in such jobs and employers may find it more convenient to use gig workers than employ workers on full- or part-time contracts with holidays and other rights and benefits.

But the development of AI may also lead to the creation of other high-productivity jobs. As the Goldman Sachs article linked below states:

Jobs displaced by automation have historically been offset by the creation of new jobs, and the emergence of new occupations following technological innovations accounts for the vast majority of long-run employment growth… For example, information-technology innovations introduced new occupations such as webpage designers, software developers and digital marketing professionals. There were also follow-on effects of that job creation, as the boost to aggregate income indirectly drove demand for service sector workers in industries like healthcare, education and food services.

Nevertheless, people could still lose their jobs before being re-employed elsewhere.

The possible rise in structural unemployment raises the question of retraining provision and its funding and whether workers would be required to undertake such retraining. It also raises the question of whether there should be a universal basic income so that the additional income from AI can be spread more widely. This income would be paid in addition to any wages that people earn. But a universal basic income would require finance. How could AI be taxed? What would be the effects on incentives and investment in the AI industry? The Guardian article, linked below, explores some of these issues.

The increased GDP from AI will lead to higher levels of consumption. The resulting increase in demand for labour will go some way to offsetting the effects of workers being displaced by AI. There may be new employment opportunities in the service sector in areas such as sport and recreation, where there is an emphasis on human interaction and where, therefore, humans have an advantage over AI.

Another issue raised is whether people need to work so many hours. Is there an argument for a four-day or even three-day week? We explored these issues in a recent blog in the context of low productivity growth. The arguments become more compelling when productivity growth is high.

Other issues

AI users are not all benign. As we are beginning to see, AI opens the possibility for sophisticated crime, including cyberattacks, fraud and extortion as the technology makes the acquisition and misuse of data, and the development of malware and phishing much easier.

Another set of issues arises in education. What knowledge should students be expected to acquire? Should the focus of education continue to shift towards analytical skills and understanding away from the simple acquisition of knowledge and techniques. This has been a development in recent years and could accelerate. Then there is the question of assessment. Generative AI creates a range of possibilities for plagiarism and other forms of cheating. How should modes of assessment change to reflect this problem? Should there be a greater shift towards exams or towards project work that encourages the use of AI?

Finally, there is the issue of the sort of society we want to achieve. Work is not just about producing goods and services for us as consumers – work is an important part of life. To the extent that AI can enhance working life and take away a lot of routine and boring tasks, then society gains. To the extent, however, that it replaces work that involved judgement and human interaction, then society might lose. More might be produced, but we might be less fulfilled.

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Questions

  1. Which industries are most likely to benefit from the development of AI?
  2. Distinguish between labour-replacing and labour-augmenting technological progress in the context of AI.
  3. How could AI reduce the amount of labour per unit of output and yet result in an increase in employment?
  4. What people are most likely to (a) gain, (b) lose from the increasing use of AI?
  5. Is the distribution of income likely to become more equal or less equal with the development and adoption of AI? Explain.
  6. What policies could governments adopt to spread the gains from AI more equally?
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Automation revisited

It’s been a while since I last blogged about labour markets and, in particular, about the effect of automation on wages and employment. My most recent post on this topic was on the 14th of April 2018 and it was mostly a reflection on some interesting findings that had been reported by Acemoglu et al (2017). More specifically, Acemoglu and Restrepo (2017) developed a theoretical framework to evaluate the effect of AI on employment and wages. They concluded that the effect was negative and potentially sizeable (for a more detailed discussion see my blog).

Using a model in which robots compete against human labor in the production of different tasks, we show that robots may reduce employment and wages … According to our estimates, one more robot per thousand workers reduces the employment to population ratio by about 0.18–0.34 percentage points and wages by 0.25–0.5 percent.

Since then, I have seen a constant stream of news on my news feed about the development of ever more advanced industrial robots and artificial intelligence. And this was not because of some spooky coincidence (or worse). It has been merely a reflection of the speed at which technology has been progressing in this field.

There are now robots that can run, jump, hold conversations with humans, do gymnastics (and even sweat for it!) and more. It is really impressive how fast change has been happening recently in this field – and, unsurprisingly, it has stimulated the interest of labour economists!

A paper that has recently come to my attention on this subject is by Graetz and Michaels (2018). The authors put together a panel dataset on robot adoption within seventeen countries from 1993 to 2007 and use advanced econometric techniques to evaluate the effect of these technologies on employment and productivity growth. Their analysis focuses exclusively on developed economies (due to data limitations, as they explain) – but their results are nevertheless intriguing:

We study here for the first time the relationship between industrial robots and economic outcomes across much of the developed world. Using a panel of industries in seventeen countries from 1993 to 2007, we find that increased use of industrial robots is associated with increases in labor productivity. We find that the contribution of increased use of robots to productivity growth is substantial and calculate using conservative estimates that it comes to 0.36 percentage points, accounting for 15% of the aggregate economy-wide productivity growth.
 
The pattern that we document is robust to including various controls for country trends and changes in the composition of labor and other capital inputs. We also find that robot densification is associated with increases in both total factor productivity and wages, and reductions in output prices. We find no significant relationship between the increased use of industrial robots and overall employment, although we find that robots may be reducing the employment of low-skilled workers.

This is very positive news for most – except, of course, for low-skilled workers. Indeed, like Acemoglu and Restrepo (2017) and many others, this study shows that the effect of automation on employment and labour market outcomes is unlikely to be uniform across all types of workers. Low-skilled workers are found again to be likely to lose out and be significantly displaced by these technologies.

And if you are wondering which sectors are likely to be disrupted most/first by automation, the rankings developed by McKinsey and Company (see chart below) would give you an idea of where the disruption is likely to start. Unsurprisingly, the sectors that seem to be the most vulnerable, are the ones that use the highest share of low-skilled labour.

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Questions

  1. “The effect of automation on wages and employment is likely to be positive overall”. Discuss.
  2. Using examples and anecdotal evidence, do you agree with these findings?
  3. Using Google Scholar, put together a list of 5 recent (i.e. 2015 or later) articles and working papers on labour markets and automation. Compare and discuss their findings.
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Rage against the machine (or should we)?

I recently found myself talking about my favourite TV shows from my childhood. Smurfs aside, the most popular one for me (and I suppose for many other people from my generation) had to be Knight Rider. It was a story about a crime fighter (David Hasselhoff) and his a heavily modified, artificially intelligent Pontiac Firebird. ‘Kitt’ was a car that could drive itself, engage in thoughtful and articulate conversations, carry out missions and (of course) come up with solutions to complex problems! A car that was very far from what was technologically possible in the 80s – and this was part of its charm.

Today this technology is becoming reality. Google, Tesla and most major automakers are testing self-driving cars with many advanced features like Kitt’s – if not better. They may not fire rockets, but they can drive themselves; they can search the internet; they can answer questions in a language of your choice; and they can be potentially integrated with a number of other technologies (such as car sharing apps) to revolutionise the way we own and use our cars. It will take years until we are able to purchase and use a self-driving car – but it appears very likely that this technology is going to become roadworthy within our lifetime.

Artificial intelligence (AI) is already becoming part of our life. You can buy a robotic vacuum cleaner online for less than a £1000. You can get gadgets like Amazon’s Alexa, that can help you automate your supermarket shopping, for instance. If you are Saudi, you can boast that you are compatriots with a humanoid: Saudi Arabia was the first country to grant citizenship to Sophia, an impressive humanoid and apparently a notorious conversationalist who does not miss an opportunity to address a large audience – and it has done so numerous times already in technology fairs, national congresses – even the UN Assembly! Sophia is the first robot to be honoured with a UN title!

What will be the impact of such technologies on labour markets? If cars can drive themselves, what is going to happen to the taxi drivers? Or the domestic housekeepers – who may find themselves increasingly displaced by cleaning robots. Or warehouse workers who may find themselves displaced by delivery bots (did you know that Alibaba, the Chinese equivalent of eBay, owns a warehouse where most of the work is carried out by robots?). There is no doubt that labour markets are bound to change. But should we (the human labour force) be worried about it? Acemoglu et al (2017) think that we should:

Using a model in which robots compete against human labor in the production of different tasks, we show that robots may reduce employment and wages […] According to our estimates, one more robot per thousand workers reduces the employment to population ratio by about 0.18–0.34 percentage points and wages by 0.25–0.5 per cent.[1]

Automation is likely to affect unskilled workers more than skilled ones, as unskilled jobs are the easiest ones to automate. This could have widespread social implications, as it might widen the divide between the poor (who are more likely to have unskilled jobs) and the affluent (who are more likely to own AI technologies). As mentioned in a recent Boston Consulting Group report (see below):

The future of work is likely to involve large structural changes to the labour market and potentially a net loss of jobs, mostly in routine occupations. An estimated 15 million UK jobs could be at risk of automation, with 63 per cent of all jobs impacted to a medium or large extent.

On the other hand, the adoption of automation is likely to result in higher efficiency, huge productivity gains and less waste. Automation will enable us to use the resources that we have in the most efficient way – and this is bound to result in wealth creation. It will also push human workers away from manual, routine jobs – and it will force them to acquire skills and engage in creative thinking. One thing is for certain: labour markets are changing and they are changing fast!

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Questions

  1. What do you think is going to be the effect of automation on labour market participation in the future? Why?
  2. Using the Solow growth model, explain how automation is likely to affect economic growth and capital returns.
  3. In the context of the answer you gave to question 2, explain how human capital accumulation may affect the ability of workers to benefit from automation.

[1] Daron Acemoglu and Pascual Restrepo, Robots and Jobs: Evidence from US Labor Markets, NBER Working Paper No. 23285 (March 2017)