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’.
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.
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.
- The Macroeconomics of Artificial Intelligence
IMF publications, Erik Brynjolfsson and Gabriel Unger (December 2023)
- Economic impacts of artificial intelligence (AI)
European Parliamentary Research Service, Marcin Szczepański (July 2019)
- Artificial intelligence: A real game changer
Chief Investment Office, Merrill/Bank of America (July 2023)
- Generative AI could raise global GDP by 7%
Goldman Sachs, Joseph Briggs (5/4/23)
- The macroeconomic impact of artificial intelligence
PwC, Jonathan Gillham, Lucy Rimmington, Hugh Dance, Gerard Verweij, Anand Rao, Kate Barnard Roberts and Mark Paich (February 2018)
- How genAI is revolutionizing the field of economics
CNN, Bryan Mena and Samantha Delouya (12/10/23)
- AI-powered digital colleagues are here. Some ‘safe’ jobs could be vulnerable.
BBC Worklife, Sam Becker (30/11/23)
- Generative AI and Its Economic Impact: What You Need to Know
Investopedia, Jim Probasco (1/12/23)
- AI is coming for our jobs! Could universal basic income be the solution?
The Guardian Philippa Kelly (16/11/23)
- CFPB chief’s warning: AI is a ‘natural oligopoly’ in the making
Politico, Sam Sutton (21/11/23)
- Which industries are most likely to benefit from the development of AI?
- Distinguish between labour-replacing and labour-augmenting technological progress in the context of AI.
- How could AI reduce the amount of labour per unit of output and yet result in an increase in employment?
- What people are most likely to (a) gain, (b) lose from the increasing use of AI?
- Is the distribution of income likely to become more equal or less equal with the development and adoption of AI? Explain.
- What policies could governments adopt to spread the gains from AI more equally?
The emergence of the digital economy has brought about increased competition across a wide range of products and services. The digital economy has provided businesses with the opportunity to produce new categories of goods and services with the aid of artificial intelligence. This new digital era has also been beneficial for consumers who now have greater choice and access to often higher-quality products at lower prices.
But while the digital revolution has facilitated greater competition, it also presents some challenges for competition law enforcement. Competition agencies continue to intensify their scrutiny of the digital economy as they try to get to grips with both the opportunities and challenges.
The role of regulation
Many agencies are aware that regulatory overreach could have negative effects on the development of digital markets. Therefore, any competition enforcement in this area needs to be evidenced-based.
A number of agencies have commissioned market studies or appointed experts in the digital field to prepare industry reports. While many of these reports and studies have found that existing competition rules generally continue to provide a solid basis for protecting competition in the digital age, there is growing demand for various changes to regulation. The reports have generally noted that the traditional tools for competition analysis may require some adaptation or refinement to address better the specificities of online markets, such as the multisided nature of platforms, network effects, zero-price markets, ‘big data’ and the increased use of algorithms.
Tech giants and online platforms, in particular, have been a focus of recent intervention by competition authorities. Investigations and intervention have related to a range of practices, including self-preferencing in the ranking of search results, the bundling of apps (and other alleged anti-competitive leveraging strategies), the collection, usage and sharing of data, and the setting of access conditions to mobile ecosystems and app stores.
The duration and complexity of these investigations have been met with concerns that competition authorities are not sufficiently equipped to protect competition in fast-moving digital markets. These concerns have been amplified by the growth in size and importance of online platforms, their significant economies of scale and network effects, and the risk that market power in digital markets can become quickly entrenched.
In addition to the commissioned reports, some agencies have established or appointed specialist digital markets units or officers. The aim of such units is to develop expertise and regulation to deal with fast-paced digital markets. In Europe, The Digital Markets Act (DMA) was adopted by the EU in response to these concerns to establish a uniform ex-ante regulatory regime to make digital markets fairer and more competitive, and to prevent a fragmentation of the EU’s internal market.
A recent case concerns Apple. Because of the Digital Markets Act, Apple has been required to allow app store competitors onto its products. This will come into effect in 2024.
In the UK, the government has been concerned that ‘the unprecedented concentration of power amongst a small number of digital firms is holding back innovation and growth’. UK competition rules are thus set to change significantly, with the government setting out the framework for an entirely new ‘pro-competition regime’ for digital markets. As it states in the Executive Summary to its proposals for such a regime (see linked UK official publication below):
The size and presence of ‘big’ digital firms is not inherently bad. Nonetheless, there is growing evidence that the particular features of some digital markets can cause them to ‘tip’ in favour of one or two incumbents… This market power can become entrenched, leading to higher prices, barriers to entry for entrepreneurs, less innovation, and less choice and control for consumers.
It has established a new Digital Markets Unit (DMU) within the Competition and Markets Authority (CMA). It was launched in ‘shadow form’ in April 2021, pending the introduction of the UK’s new digital regulatory regime. Under the proposals, the new regime will focus on companies that the DMU designates as having ‘strategic market status’.
The government is expected to publish its much-awaited Digital Markets, Competition and Consumer Bill, which, according to legal experts, will represent the most significant reform of UK competition and consumer protection laws in years.
It is expected that the Bill will result in important reforms for competition law, but it is also expected to give the DMU powers to enforce a new regulatory regime. This new regime will apply to UK digital firms that have ‘strategic market status’ (SMS). This will be similar to the EU’s Digital Markets Act in how it applies to certain ‘gatekeeper’ digital firms. However, the UK regulations are intended to be more nuanced than the EU regime in terms of how SMS firms are designated and the specific obligations they will have to comply with.
A report by MPs on the influential Business, Energy and Industrial Strategy Committee published in October, urged the Government to publish a draft Digital Markets Bill that would help deter predatory practices by big tech firms ‘without delay’.
On 17th November 2022, the UK Government announced in its Autumn Statement 2022 that it will bring forward the Bill in the third Parliamentary session. There has been no specific date announced yet for the first reading of the Bill, but it will probably be in Spring 2023. Current expectations are that the new DMU regime and reforms to competition and consumer protection laws could be effective as early as October 2023.
Proposals for the Bill were trailed by the Government in the Queen’s Speech. It announced measures that would empower the Competition and Markets Authority’s (CMA) Digital Markets Unit (DMU) to rein in abusive tech giants by dropping the turnover threshold for immunity from financial penalties from £50 million to £20 million and hiking potential maximum fines to 10% of global annual income. Jeremy Hunt, the Chancellor of the Exchequer, said that the Bill, once enacted, would ‘tackle anti-competitive practice in digital markets’ and provide consumers with higher quality products and greater choice. The strategy includes tailored codes of conduct for certain digital companies and a bespoke merger control regime for designated firms.
The Bill is also expected to include a wide range of reforms to the competition and consumer law regimes in the UK, in particular:
- wide-ranging changes to the CMA’s Competition Act 1998 and market study/investigation powers, including significant penalties for non-compliance with market investigation orders;
- significant strengthening of the consumer law enforcement regime by enabling the CMA directly to enforce consumer law through the imposition of fines;
- changes to UK consumer laws to tackle subscription traps and fake reviews and to enhance protections for savings schemes.
Competition law expert Alan Davis of Pinsent Masons said:
Importantly, the Bill will bring about major reforms to consumer protection law, substantially strengthening the CMA’s enforcement powers to mirror those it already uses in antitrust cases, as well as important changes to merger control and competition rules.
It is anticipated that the Bill will announce the most significant reforms of UK competition and consumer protection laws in years and is expected to have an impact on all business in the UK to varying degrees. It is advised, therefore, that businesses need to review their approach to sales and marketing given the expected new powers of the CMA to impose significant fines in relation to consumer law breaches.
Technological innovation is largely pro-competitive. However, competition rules must be flexible and robust enough to deal with the challenges of the online world. A globally co-ordinated approach to the challenges raised in competition law by the digital age remains important wherever possible. Under the EU’s Digital Markets Act, firms that are designated as gatekeepers, and those defined as having strategic market status under the UK regime, will be required to undertake significant work to ensure compliance with the new rules.
UK official publications
- For what reasons may digital markets be more competitive than traditional ones?
- What types of anti-competitive behaviour are likely in digital markets?
- Explain what are meant by ‘network economies’? What are their implications for competition and market power?
- Explain what is meant by ‘bundling’? How is this likely to occur in digital markets?
- Give some examples where traditional markets are combined with online ones. Does this make it difficult to pursue an effective competition policy?
- Give some examples of ways in which firms can mislead or otherwise take advantage of consumers in an e-commerce environment.
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.
- “The effect of automation on wages and employment is likely to be positive overall”. Discuss.
- Using examples and anecdotal evidence, do you agree with these findings?
- 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.
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.
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!
- What do you think is going to be the effect of automation on labour market participation in the future? Why?
- Using the Solow growth model, explain how automation is likely to affect economic growth and capital returns.
- 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.
 Daron Acemoglu and Pascual Restrepo, Robots and Jobs: Evidence from US Labor Markets, NBER Working Paper No. 23285 (March 2017)
What will production look like in 20 years time? Will familiar jobs in both manufacturing and the services be taken over by robots? And if so, which ones? What will be the effect on wages and on unemployment? Will most people be better off, or will just a few gain while others get by with minimum-wage jobs or no jobs at all?
The BBC has been running a series looking at new uses for robots and whether they will take people’s jobs? This complements three reports: one by Boston Consulting one by Deloitte and an earlier one by Deloitte and Michael Osborne and Carl Frey from Oxford University’s Martin School. As Jane Wakefield, the BBC’s technology reporter states:
Boston Consulting Group predicts that by 2025, up to a quarter of jobs will be replaced by either smart software or robots, while a study from Oxford University has suggested that 35% of existing UK jobs are at risk of automation in the next 20 years.
Jobs at threat from machines include factory work, office work, work in the leisure sector, work in medicine, law, education and other professions, train drivers and even taxi and lorry drivers. At present, in many of these jobs machines work alongside humans. For example, robots on production lines are common, and robots help doctors perform surgery and provide other back-up services in medicine.
A robot may not yet have a good bedside manner but it is pretty good at wading through huge reams of data to find possible treatments for diseases.
Even if robots don’t take over all jobs in these fields, they are likely to replace an increasing proportion of many of these jobs, leaving humans to concentrate on the areas that require judgement, creativity, human empathy and finesse.
These developments raise a number of questions. If robots have a higher marginal revenue product/marginal cost ratio than humans, will employers choose to replace humans by robots, wholly or in part? How are investment costs factored into the decision? And what about industrial relations? Will employers risk disputes with employees? Will they simply be concerned with maximising profit or will they take wider social concerns into account?
Then there is the question of what new jobs would be created for those who lose their jobs to machines. According to the earlier Deloitte study, which focused on London, over 80% of companies in London say that over the next 10 years they will be most likely to take on people with skills in ‘digital know-how’, ‘management’ and ‘creativity’.
But even if new jobs are created through the extra spending power generated by the extra production – and this has been the pattern since the start of the industrial revolution some 250 years ago – will these new jobs be open largely to those with high levels of transferable skills? Will the result be an ever widening of the income gap between rich and poor? Or will there be plenty of new jobs throughout the economy in a wide variety of areas where humans are valued for the special qualities they bring? As the authors of the later Deloitte paper state:
The dominant trend is of contracting employment in agriculture and manufacturing being more than offset by rapid growth in the caring, creative, technology and business services sectors.
The issues of job replacement and job creation, and of the effects on income distribution and the balance between work and leisure, are considered in the following videos and articles, and in the three reports.
What is artificial intelligence? BBC News, Valery Eremenko (13/9/15)
What jobs will robots take over? BBC News, David Botti (15/8/14)
Could a robot do your job? BBC News, Rory Cellan-Jones (14/9/15)
Intelligent machines: The robots that work alongside humans BBC News, Rory Cellan-Jones (14/9/15)
Intelligent machines: Will you be replaced by a robot? BBC News, John Maguire (14/9/15)
Will our emotions change the way adverts work? BBC News, Dan Simmons (24/7/15)
Could A Robot Do My Job? BBC Panorama, Rohan Silva (14/9/15)
Technology has created more jobs in the last 144 years than it has destroyed, Deloitte study finds Independent, Doug Bolton (18/8/15)
Technology has created more jobs than it has destroyed, says 140 years of data The Guardian, Katie Allen (18/8/15)
Will a robot take your job? BBC News (11/9/15)
Intelligent Machines: The jobs robots will steal first BBC News, Jane Wakefield (14/9/15)
Robots Could Take 35 Per Cent Of UK Jobs In The Next 20 Years Says New Study Huffington Post, Thomas Tamblyn (14/9/15)
The new white-collar fear: will robots take your job? The Telegraph, Rohan Silva (12/9/15)
Does technology destroy jobs? Data from 140 years says no Catch news, Sourjya Bhowmick (11/9/15)
Takeoff in Robotics Will Power the Next Productivity Surge in Manufacturing Boston Consulting Group (10/2/15)
Agiletown: the relentless march of technology and London’s response Deloitte (November 2014)
Technology and people: The great job-creating machine Deloitte, Ian Stewart, Debapratim De and Alex Cole (August 2015)
- Which are the fastest growing and fastest declining occupations? To what extent can these changes be explained by changes in technology?
- What type of unemployment is caused by rapid technological change?
- Why, if automation replaces jobs, have jobs increased over the past 250 years?
- In what occupations is artificial intelligence (AI) most likely to replace humans?
- To what extent are robots and humans complementary rather than substitute inputs into production?
- “Our analysis of more recent employment data also reveals a clear pattern to the way in which technology has affected work.” What is this pattern? Explain.
- Why might AI make work more interesting for workers?
- Using a diagram, show how an increase in workers’ marginal productivity from working alongside robots can result in an increase in employment. Is this necessarily the case? Explain.