The Impact of Digital Technology on Wealth and Income Inequality

April, 2025 - I wrote this research report when I was 16, just under 10 years ago, and rediscovered it after the topic arose in a recent conversation. I remember it being core driver for me later studying Computer Science at university. At the time, the issues discussed felt like a looming reality in the distant future. The threat is now at our doorstep. We've all experienced the technology developments firsthand - the most surreal one so far being the fully autonomous car journey (courtesy of Waymo). And while I used 'GPTs' in this report to mean General Purpose Technology, today the acronym is synonymous with Generative Pre-trained Transformers, now writing 60%+ of our startup's codebase. My views on how to address these issues have developed, though I haven't given it as much thought as of yet, maybe I will in a future post. At a high level, I would now probably lean more towards allowing free markets to function and not restricting technology development, while emphasizing the need for governments to 'keep up' to ensure people generally are not left behind.

Abstract

The growth of digital technology is occurring at a staggering rate and one that cannot be controlled or regulated. However, its negative social impacts can both be measured and minimised. The wonders of increasing efficiency and productivity to levels never imagined before are driving the economy into a new age, but too many are being left behind. But why are we now concerned about this? Levels of inequality are returning to as they were in the 1800s, and the social problems that arise as a result of this are much more damaging than the financial problem itself. It has the power to destroy nations. Hence why it is essential to work with the machines to grow as nations in such a way that everybody benefits.

The overall effects of technology on inequality are what I set out to find, with solutions to how the negative impacts can be minimised. The mechanisms through which inequality is affected became less important as my research progressed, since it became clear that lack of government intervention was to blame. I found that the lack of labour mobility among the population, particularly median income households, leads to displaced workers who cannot grasp the high-skilled jobs generated through the growth of digital technology. The demand for labour is there, the willingness to work is there, the only thing missing are the necessary skills. The research collaboratively pointed towards a common solution. Governments should focus on financially encouraging firms to increase training schemes for those who are at the highest risk of being displaced by automation. The reason for having the firms develop and run the schemes is because they have the best knowledge on what is needed from the workforce.

Introduction

Over the past century, we have seen, particularly in the developed world, an exponential rise in the uses and applications of modern technologies in all aspects of our lives. We live in an age where we cannot escape technology and so its influence on the economy is direct. Inequality is a key issue in our society as the wage gap widens and inequality is rising faster than ever.

What is first required is to define what is meant by income inequality and wealth inequality and the distinction between the two. Income inequality refers to the widening gap between annual incomes, whereas wealth inequality refers to the unequal distribution of assets among residents of a country. Wealth includes the values of homes, cars, personal valuables, businesses, savings, and investments.

The next very important definition is that of technology. In today's society, the word is thrown around and means a variety of things to people. For some, it means advances in science that make way for new products and machines. Others would say it is anything that simplifies/aids life in general.

For the purposes of this dissertation, Technology is the collection of techniques, skills, methods, and processes used in the production of goods or services or in the achievement of objectives.

Although technology as a whole will be considered, the importance of computer systems, digital technologies, will be analysed and evaluated in greater depth. The more recent development over the last few decades is often taken for granted and its value is underestimated.

The focus will be placed on the last three decades, from 1985-2015, as well as the decade the follow (2015-2025) and the future of technology's impact on inequality. The transition to the digital era has taken place in the time period chosen, and is where the effects can be analysed. Although technology affects all economies, regardless of size, the research will be based on the UK & USA. These are two of the most advanced economies in the world and so the effects of digital technology are easiest to measure and data is most available, developing countries are likely to exhibit similar trends in the future. The extent to which technology affects each economy will vary, and the time taken will also vary, but the overall effects and trends within the two countries are likely to be similar.

Whatever the extent of the effect is, it is clear that there must be a link, and it is also clear from the past that advances in technology have lead to changes in employment and inequality in economies. The ultimate aim of this dissertation is to put emphasis on the role of governments in controlling the economy effectively, and the steps they can take through implementing policy to ensure that everybody has the opportunity to benefit economically from advances in technology. The primary factor here is education. The skills are lacking, and money needs to be invested into the training and retraining of individuals in order to suit the requirements of the ever-changing job market.

I intend to study Computer Science at university, and find it important to understand the mechanisms of economies. What interests me most is how inequality may change in light of new and upcoming technological advancements. I would like to explore the ways in which inequality can be affected by technology, and how it affects the income and wealth of nations. The world should be concerned and aware of how technology affects economies on an individual level and government intervention along with policies should be used in order tackle the problems that may arise because of it.

Research Review

"We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come---namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour."

--- John Maynard Keynes, 1930 (Keynes, 1930)

French academic economist Thomas Piketty identifies in critically acclaimed Capital in the Twenty-First Century that one of the main causes for global convergence of incomes and wealth, from 19th century to present, is the diffusion of knowledge. The poor catch up to the rich to the extent that they achieve the same level of technological know-how, skill, and education, not by becoming the property of the wealthy. The diffusion of knowledge is hastened by international openness and trade, but depends upon a country's ability to mobilise financing as well as intuitions that enable large-scale investment in education and training, and hence depends on an efficient government.

Yet in a world where globalisation and international openness is at an all time high, inequality within countries is getting worse. The gap between the wealthy and everyone else is largest in the United States. In 2010, the richest 1 percent of the population had 34 percent of the accumulated wealth; the top 0.1 percent had some 15 percent. And the inequality has only gotten worse since the last recession ended: the top 1 percent have captured 95 percent of income growth from 2009 to 2012, if capital gains are included. (Piketty, 2014)

But why care, why should governments be concerned? As highlighted in the recent book by Daron Acemoglu and James Robinson, Why Nations Fail, economic inequality often results in political inequality, where: "those with great wealth and easy access to politicians and policymakers will try to increase their power at the expense of society. That sort of hijacking of politics is a sure-fire way of undermining inclusive political institutions, and it is already under way in the US." There are thus good reasons to be concerned by the rise of inequality.

As Piketty points out, it is a radical departure from how we have thought about progress. Since the 1950s, economics has been dominated by the idea---formulated by Simon Kuznets ---that inequality diminishes as countries become more technologically developed and more people are able to take advantage of the resulting opportunities. But the belief that technological progress will lead to "the triumph of human capital over financial capital and real estate, capable managers over fat cat stockholders, and skill over nepotism" is, writes Piketty, "largely illusory."

While Piketty warns against a return to a world where inherited wealth determines social and political fates, Erik Brynjolfsson worries that a growing share of the workforce could be left behind even as digital technologies increase overall income. Brynjolfsson, a professor of management at MIT's Sloan School, along with his coauthor and fellow MIT academic Andrew McAfee talks of advanced robots and the vast potential of artificial intelligence.

The distinction between Piketty's supermanagers and Brynjolfsson's superstars (as detailed later on) is critical: the latter derive their high incomes directly from the effects of technology. As machines increasingly substitute for labour and building a business becomes less capital-intensive---you don't need a printing plant to produce an online news site, or large investments to create an app---the biggest economic winners will not be those owning conventional capital but, instead, those with the ideas behind innovative new products and successful business models.

David Autor, an MIT economist, is skeptical of Brynjolfsson and McAfee's argument that the transformation of work is speeding up as technological change accelerates. Research he conducted with a fellow MIT economist, Daron Acemoglu, suggests that productivity growth is not in fact accelerating, nor is such growth concentrated in computer-intensive sectors. According to Autor, the changes brought by digital technologies are transforming the economy, but the pace of that change is not necessarily increasing. (Autor et al., 2003)

Still, as Piketty's lengthy analysis suggests, the explanation for the rise in inequality is not a simple one. Specifically, the role technology is playing is complex and contested.

Keynes, Piketty, Autor, McAfee, Brynjolfsson, Acemeoglu and Kuznets, are all academics. They have all dedicated their lives to Economic research and so it can be noted that all of the information gathered from the various research papers and books which they have written, are objective. They possess almost no bias towards anything in particular. Although they may disagree on many things, their main aim is to reduce inequality and use their research in order to pose solutions to economic problems.

Destruction of Jobs

The first and most obvious reason for technology leading to increased inequality is the destruction of jobs. For a long time, an increase in productivity would normally mean increased economic growth, which leads to the creation of new jobs. However in the last 15 years, the increase in productivity (due to improvements in technology), has been so rapid, that productivity and total number of jobs are diverging.

A recent paper by economists Daron Acemoglu and David Autor highlights the growing divergence in earnings between the most-educated and least-educated workers. Over the past 40 years, weekly wages for those with a high school degree have fallen and wages for those with a high school degree and some college have stagnated. (Acemoglu & Autor, 2011) On the other hand, college-educated workers have seen significant gains, with the biggest gains going to those who have completed graduate training. Those that are educated possess more skills and so are more valuable to employers than those with just a high school degree, and hence are more employable and better paid.

It's clear from the chart below that wage divergence accelerated in the digital era. As documented in careful studies by David Autor, Lawrence Katz, and Alan Krueger, as well as Frank Levy and Richard Murnane and many others, the increase in the relative demand for skilled labour is closely correlated with advances in technology, particularly digital technology.

"Superstars"

In many industries, a few individuals get the lion's share of the rewards, examples include pop music, professional athletics and the market for CEOs. Digital technologies increase the size and scope of these markets, allowing individuals to dominate a national or even global market, meanwhile local competitors are increasingly crowded out of their markets. And allowing the superstars in each field to earn much larger rewards than they did in earlier decades.

Why hire a local tax consultant when you can use a cheap, state-of-the-art program that is constantly being updated and refined? Likewise, why buy a second-best program or app? The ability to copy software and distribute digital products anywhere means customers will buy the top one. Why use a search engine that is almost as good as Google? Such economic logic now rules a growing share of the marketplace; it is, according to Brynjolfsson, an increasingly important reason why a few entrepreneurs, including the founders of such startups as Instagram, are growing rich at a staggering rate.

The effects are evident at the top of the income distribution. The top 10% of the wage distribution has done much better than the rest of the labour force, but even within this group there has been growing inequality. Income has grown faster for the top 1% than the rest of the top decile. In turn, the top 0.1% and top 0.01% have seen their income grow even faster. (Brynjolfsson & McAfee, 2012)

However, technology is not the only factor that affects incomes. The research on "superstars" does not evaluate the other causes of growing inequality. Political factors, globalisation, changes in asset prices, and, in the case of CEOs and financial executives, corporate governance also plays a role. In particular, the financial services sector has grown dramatically as a share of GDP and even more as a share of profits and compensation, especially at the top of the income distribution. While efficient finance is essential to a modern economy, it appears that a significant share of returns to large human and technological investments in the past decade, such as those in sophisticated computerised program trading, were from rent redistribution rather than genuine wealth creation.

But the overall changes in the United States have been substantial. According to economist Emmanuel Saez, the top 1% of U.S. households got 65% of all the growth in the economy since 2002. In fact, Saez reports that the top 0.01% of households in the United States---that is, the 14,588 families with income above \$11,477,000---saw their share of national income double from 3% to 6% between 1995 and 2007. (Saez et al., 2013)

Capital vs Labour

Production (in general) requires both machinery and human labour. The wealth they generate, according to bargaining theory, is divided according to relative bargaining power, which in turn typically reflects the contribution of each input. If technology reduces the importance of human labour, the owners of capital will be able to capture a larger share of the income from the goods. Capital owners are generally a very different and smaller group than those doing most of the labour so the income distribution is heavily affected. As Piketty writes, the main driver of inequality- the tendency of returns on capital to exceed the rate of economic growth- threatens to generate extreme inequality.

There are 2 key determinants of the return on capital:

1. Technology
2. Abundance of capital stock

However, there are flaws in this theory, especially where managers and "supermanagers" are concerned, as explained by Piketty. This is due to the marginal productivity of capital. It is impossible to put a monetary value on the pay roles of CEOs and Business managers.

Digital technologies make it easier to substitute labour for capital. Although such substitution helps productivity, it does not boost wages. This is because firms would rather invest into additional capital rather than increased wages. Instead what happens is that the capital share of income is enhanced, leading to a higher concentration of wealth. As a result, while income inequality is on the rise, the concentration of wealth is also striking. According to a recent study the wealthiest 0.01% of American families now control 11.2% of total wealth: about the same share as back in 1916, which is an all-time high. (Australian Financial Review, 2016)

General Purpose Technology

"General purpose Technology" used by economists (such as Erik Brynjolfsson and Andrew Mcafee) to describe technology that rapidly drives economic growth. Electricity is an example of a general purpose technology, like the steam engine before it. The reason for the rapid growth is because general purpose technology unleashes cascades of complementary innovations, like lightbulbs and factory redesign. The general purpose technology of our era? Computers.

Timothy Bresnahan and Manuel Trajtenberg note:

"Whole eras of technical progress and economic growth appear to be driven by ... GPTs, [which are] characterized by pervasiveness (they are used as inputs by many downstream sectors), inherent potential for technical improvements, and "innovational complementarities," meaning that the productivity of R&D in downstream sectors increases as a consequence of innovation in the GPT. Thus, as GPTs improve they spread throughout the economy, bringing about generalized productivity gains." (Bresnahan & Trajtenberg, 1995)

The idea that GPT bring about productivity gains throughout the economy means that more can be done in a shorter amount of time. This means that there is an downwards and outwards shift in the aggregate supply curve. This boost in output per worker should lead to revenues and profits rising and economies growing. The gains in productivity should in theory cause a multiplier effect, with wages rising for everyone and increased job creation.

However, the research may be relevant to electricity and the steam engine, but for computers there are other things that must be considered. The most important is that the benefits gained on an individual level varies drastically. This research links closely with the idea of Superstars. Whilst some individuals take advantage of the new tool they have available to them, others simply cannot due to the lack of opportunity. There is not yet a universal access to computers or the internet, and even in places where there is, not everybody has the skills to benefit and increase their own productivity in life as a whole. This is how inequality is heavily affected. Due to existing inequality, computers as a GPT cannot benefit everybody and so existing inequality is worsened. It remains the role of governments to ensure that people of all age and income groups can benefit through nationwide training schemes.

Moores' Law

Moore's Law, which is an expansion of an observation made by Gordon Moore, co-founder of microprocessor maker Intel. In a 1965 article in Electronics Magazine, Moore noted that the number of transistors in a minimum-cost integrated circuit had been doubling every 12 months, and predicted that this same rate of improvement would continue into the future. When this proved to be the case, Moore's Law was born. Later modifications changed the required time for the doubling to 18-24 months. The graph below shows the number of calculations per second against time, showing the power of the human brain in relation.

It also seems that software progresses at least as fast as hardware does, at least in some domains. Computer scientist Martin Grötschel analysed the speed with which a standard optimisation problem could be solved by computers over the period 1988-2003. He documented a 43 millionfold improvement, which he broke down into two factors: faster processors and better algorithms embedded in software. Processor speeds improved by a factor of 1,000, but these gains were dwarfed by the algorithms, which got 43,000 times better over the same period.

Moores' Law is very important to the effects on inequality due to computers because the rate of increase of the power of computer systems may be linked to the growth of inequality also. As computers get more powerful, they can replace and reduce the need for labour in economies. Robotics and automation are the biggest causes of job destruction, and the majority of these jobs are the median income groups, as explained later on. There is no sign of this slowing down and evidence points towards the growth possibly being exponential. It is the role of governments to plan for and be ready for such advances by offering training so that workers have job mobility.

Artificial Intelligence and Robotics: Destroying Jobs II

It would be impossible to talk about computer technology radically changing the global economy without mentioning artificial intelligence (AI) and robotics, especially when predicting what the future holds for economies due to advancements in such technologies. Although we do not know what the impact on labour markets of these developments will be, some estimates suggest that algorithms could displace around 140 million knowledge workers globally. (MGI, 2013)

As the 21st century unfolds, automation is affecting broader areas of work. Even the low wages earned by factory workers in China have not prevented them from being undercut by new machinery and the complementary organisational and institutional changes. For instance, Terry Gou, the founder and chairman of the electronics manufacturer Foxconn, announced this year a plan to purchase 1 million robots over the next three years to replace much of his workforce. The robots will take over routine jobs like spraying paint, welding, and basic assembly. A recent paper suggests that a staggering 47% of US jobs are at risk from automation, but this varies between cities. (Berger et al., 2015)

Elon Musk, CEO and founder of Tesla and SpaceX, says "the problem of self driving cars has been solved." He believes that the delay to mass market is due to regulators and expects that worldwide regulatory approval will require something on the order of 6 billion miles (10 billion km). Current fleet learning is happening at just over 3 million miles (5 million km) per day.

If this continues, and AI is used to its full potential, the rate of increases in productivity and efficiency will require a radical change in the labour market. There is no way of being sure what the future of economies will be like, but it is immediately obvious by looking at the current trends that improvements in digital technology will be the major cause of change. For a world with driverless cars and automation in all aspects of work, it is clear that lower income groups will be hit harder.

Governments are not keeping up with the advancements and this is clear as regulation is not responding fast enough to the changes in technology. Regulation on drones, driverless cars and artificial intelligence should protect the public and prevent industry from misusing the technology. At the same time, such technology should not be discouraged or slowed down, since economic growth is dependant on it. The aim for people is to use the technology and work with it, rather than work against it.

Polarisation of Jobs

Pioneering research by Autor, Katz, and Kearney (Autor, 2010) found that the share of employment in occupations in the middle of the skill distribution has declined rapidly in the US and Europe. At the same time the share of employment at the upper and lower ends of the occupational skill distribution has increased substantially. Goos and Manning termed this phenomenon "job polarisation" and it is depicted for US workers in Figure 1.

Notes: The chart depicts the percentage point change in employment in the low-, middle- and high-skilled occupations in the National Longitudinal Survey of Youth (NLSY) and the comparable years and age group in the more standard Current Population Survey (CPS). The high-skill occupations comprise managerial, professional services and technical occupations. The middle-skill occupations comprise sales, office/administrative, production, and operator and labourer occupations. The low-skill occupations include protective, food, cleaning and personal service occupations.

Middle-skilled manufacturing and clerical occupations are characterised by a high intensity of procedural, rule-based activities which Autor calls "routine tasks". As it happens, these routine tasks can relatively easily be coded into computer programs. Therefore, the rapid improvements in computer technology over the last few decades have provided employers with ever cheaper machines that can replace humans in many middle-skilled activities such as bookkeeping, clerical work and repetitive production tasks. These improvements in technology also enable employers to offshore some of the routine tasks that cannot be directly replaced by machines.

Moreover, cheaper routine tasks provided by machines complement the non-routine abstract tasks that are intensively carried out in high-skill occupations. For example, data processing computer programs strongly increased the productivity of highly-skilled professionals. Machines also do not seem to substitute for the non-routine manual tasks that are intensively carried out in low-skill occupations. For example, computers and robots are still much less capable of driving taxis and cleaning offices than humans. Thus, the relative economy-wide demand for middle-skill routine occupations has declined substantially.

This routinisation hypothesis, due to Autor, Levy, and Murnane, has been tested in many different settings and it is widely accepted as the main driving force of job polarisation. The research shows that those who are affected by job polarisation are especially those who the government training schemes should be targeted at. This is because the stagnant wages for the median income households is what is driving the growth of the income and wealth for the rich.

Discussion

What is technology doing?

Technology is increasing productivity and efficiency to levels which were thought to be unreachable. As shown by Moores' Law, the power of processors and other computer technology such as storage is increasing at a constant and high rate, leading to efficiency increasing at a similar rate. This means that production of goods and services are increasing at similar rates too and this just means that in the long-term, capacity increases.

Although many people are displaced, equally as many people become employed elsewhere. All of this must coincide with population growth. I would argue technology is, if not will be, the sole driver of modern economic growth. However, it is increasing the proportion of the role of capital, hence increasing the proportion of profit going to the owners of capital. Does this mean the labourers are worse off? Not necessarily. As trickle down economics explains, since profits are rising for those that earn capital, this should in-turn result in the creation of more jobs and increases in wages through the circular flow of income and increased investment. Additionally, this should also result in higher tax revenue that would then be redistributed to those in lower income groups. But this all depends upon one key factor; the role of governments.

The arguments posed for technology are very similar to those for immigration. Is technology a complement or substitute to labour. In some instances, economic immigrants bring financial capital to a country, and through entrepreneurship, create more jobs for citizens of the country as well as contributing significantly through taxes to the government. But on the other hand, low-skilled workers who provide cheap labour are argued to 'steal' jobs and so make it harder for citizens of a country to find employment. These low-skilled workers also contribute towards tax revenue and many of them also do not take out pensions so often contribute more, as a whole, towards tax. A third group of economic immigrants are high-skilled workers who are highly in demand where there is a lack of supply, examples include computer scientists and engineers in the UK. Although jobs are readily available, many of those who are seeking employment do not possess the skills required to do these jobs.

The link to technology is very similar to those 3 categories. In the first scenario, technology creates jobs, new technology generally obtains significant amount of funding and investment and a prime example of this is DeepMind, a UK start-up which has now been acquired by Google for £400 million. The number of jobs this creates is significant and brings money into the UK. For the second scenario, technology 'stealing' jobs could be related to the off-shoring of workers such as call-centres, which (arguably) offer the same quality of work for a significantly cheaper cost, whilst many domestic workers are displaced. As for the third scenario, and in my opinion the most important comparison, technology doing jobs which humans lack the skill/efficiency in doing. The lack of skilled workers in the UK is a growing issue, and is one that can be solved, but over an extended period of time of around 5-10 years. Over time, even jobs such as accounting will be in large replaced by comprehensive software which can do replicate the requirements of the job.

Although one of the main arguments that is often made is the new jobs are being created, do the wages of these new jobs equal/surpass that held in previous jobs, and also does this equal/surpass the increased revenue to those that own the factors of production. Many of the new jobs created are in fact require a different and more technical skill-set. What can be seen in the labour market is college graduates securing jobs which a 30-40 year old cannot compete with due to possessing 'outdated' skills. Technology is a direct cause for the change in labour markets and this has made way for much self-employment in the taxi industry and housing industry. Examples include Uber and Airbnb, both of which allow landlords and drivers to make money without a fixed employment contract. In doing so, both companies make substantial amounts of money through connecting economic agents, with each company having a net worth of \$6.3bn and \$3.3bn respectively. The problems associated with such internet companies are that they intervene in markets and increase efficiency, but in doing so, the drivers themselves each earn less than before, even though there are more drivers as a result of it.

Why is this happening?

Adoption of technology is not enough. The divergence between those from a graduate school and high school dropouts is a key illustration of the role that education plays in income, which is not surprising, but can also be used to explain why the adoption of technology is not equal for all groups. The adoption of technology has a direct correlation to growth. The more adoptable technology is, the more room there is for growth. As for the population, the educated gain more than uneducated. I believe that the cause for this is due to the lack of skills, and transferrable skills. Those who are educated enough to have basic IT skills can benefit far greater than those without, they generally find it much easier to learn and pick up these basic skills.

Median incomes have been stagnant for over 30 years. The problem isn't that technology has eliminated the need for mid-skill workers overall. New opportunities are there, but grasping them is difficult. Overcoming that obstacle will take time as well as policies that promote technical training, certify skills learned through experience, encourage employee mobility, and foster labor markets. The reason for these incomes stagnating is partly due to government policies such as progressive tax that hits middle incomes hardest as they cannot afford to pay the increased tax. Technology may be destroying jobs in one industry but it creates them in others, and the fault lies within government policy to accommodate for the evolving markets and industries.

The superstars that benefit from technology are arguably too few. According to a recent estimate, the three leading companies of Silicon Valley employed some 137,000 workers in 2014 with a combined market capitalisation of \$1.09 trillion. By contrast, in 1990 the three largest companies in Detroit had a market capitalisation of \$36 billion while collectively employing about 1.2 million workers. (Chui & Manyika, 2014) Although this estimate was made in 2013, in the last year, the companies have done nothing but grow, that too at a staggering rate. The rich are getting richer. However, these tech giants, although may seem to be keeping the lionshare of their profits, are having positive multiplier effects on employment. A document released by The Bay Area Economic Council (Bay Area Economic Council, 2012) has published some interesting statistics about silicon valley. For each job created in the high-tech sector, approximately 4.3 jobs are created (multiplier effect) in other local goods and services sectors across all income groups, including lawyers, dentists, schoolteachers, cooks and retail clerks, among many others. The jobs multiplier effect in the high-tech sector is significantly higher than for almost any other sector. By comparison, traditional manufacturing has a multiplier effect of 1.4 jobs. Demand for high tech occupations will be considerably stronger than demand for other workers at least through 2020.

Big technology companies, the 'superstars', make it very difficult for start-ups to survive grow or compete. Competition between the large firms is encouraged in order to increase efficiency, but the growth of the internet has lead to a situation wherein which competing is near impossible. Information is getting much closer to perfection due to the internet. Consumers can find the best products, at the best price, making it much harder for firms to compete. Competition is not the same as it is in traditional economies, whether this is due to technology or other factors however is not clear.

What can be done and the Role of Governments and Regulation

The adoption of technology is very high in everyday life, and this is so evident I need not go into it. But why is it when it comes to earning a living, we are not using technology to its full extent. The key is working with the technology. Innovation is important, and working with the machines is more important than blaming them for 'stealing' jobs.

In order to combat inequality and unemployment growing as a result of advances in technology, markets need to be regulated by governments in order to protect both industries and jobs. However the extent of regulation needs to be carefully planned. I believe that Research & Development is essential to to modern economic growth and so regulating developments such as Artificial Intelligence would be counter-productive, and also impossible. There is no way of effectively policing and enforcing regulation that prohibits research in topics such as AI, however, I believe regulation should be placed in the applications of such research. In industries such as military, driving, and healthcare, regulation must be put in place for the safety of humans. The rise of drones and similar technologies are on course to be very successful and improve the lives of people, but the security implications and safety concerns far outweigh the possible successes.

A step into the future

As technology continues to grow at the staggering rate that is currently is, the topic of technological unemployment and inequality will only become more important. Hence, it is important to identify and act on the effects that technology has on inequality.

The job market will rapidly reshape multiple times in the upcoming decades, with an important cause being the growth of technology. Hence why the skills learnt need to be transferrable, because a job which may seem 'secure' one day may not exist the next. Money needs to be invested into training and education for workers to be able to earn a living in the unpredictable and ever changing job market. It is important to hypothesise about what direction technology is moving in and which sectors specifically will be affected. A prime example of this are driverless cars. In the US alone, the number of taxicab drivers are 233,900. (Bureau of Labor Statistics, 2016) This doesn't include other people who drive in order to earn a living. If driverless vehicles succeed, all of those jobs will be displaced, which I expect to be a massive underestimate. Currently, there is no protection for those drivers, machines can drive better than humans and will result in roads being much safer as a whole. Another very recent example is Amazon Go, which is essentially a grocery store in which there are no checkouts or queues, and as a result, far less employees. It runs entirely through various computer systems and tracking that charges each user automatically when they leave the store. Although extremely innovative, time saving and efficient, the jobs that will displaced in the long run is dramatic!

As previously stated, up to 50% of all US jobs are prone to automation. This means that up to 50% of jobs can be done by machines, I find it frightening how much the job market and economy could change in the near future as a result of this and protection for those workers and jobs needs to begin now! As a supporter of driverless cars and other emerging technology, such as the use of drones for delivery, I think that very careful regulation needs to be put in place to protect existing workers and also safety concerns in general.

Conclusion

What do I propose?

From the four sections above, we can summarise the arguments made for and against technology. The first of these arguments is that technology is destroying jobs, and the reason for this is that technology is far more efficient and as a result of this productivity is rising in our economy, at the expense of people's jobs. This argument cannot be rejected, the figures show that jobs are being destroyed by technology, and the ones that replace them are high skilled jobs.

The second argument made is that the adoption (or lack of it) of technology is worsening the inequality. Different income groups are affected in different ways, and the main reason for this is the different levels of education among income groups. Those who are less educated find it difficult to grasp the new job opportunities (due to the lack of skills) and are the ones who are most displaced by technology. I believe this argument to be the key factor as to why income inequality is worsening due to technology, everybody cannot benefit in the same way because of the varied level of education.

The third argument is that technology is not the main cause of the problem of inequality, it is more down to the structure of firms and super managers, as outlined by Thomas Piketty. The role of technology can only be seen in a positive light, due to its various positive multiplier effects which significantly outweigh any small effects on inequality it may have. This argument has some credibility in that there are far factors that affect inequality that can be listed. Technology may not be the sole driver of inequality, but it most definitely plays a large part, and its significance will only increase and I believe we are yet to see the extent of its power. We cannot limit the growth of technology in order to control inequality, we must work with technology to reduce inequality.

However, the solution, no matter what is believed to be the current role of technology, is that governments need to be more 'involved' with technological advances. Policy-makers should ensure that improvements in tech benefit everyone, without being at the expensive of lower income groups. But how they go about doing this is a huge problem that they face. On one hand they want to encourage firms to innovate so that economies grow, yet on the other there are pressures to increase corporate tax to avoid them benefiting so highly from such ventures. It is extremely difficult reaching a middle ground wherein which both consumers and producers are both satisfied. I believe that the key is to develop new policy, much like technology firms are doing today. Instead of 'dragging' firms down, they should aim to 'push' those lower income groups up. How I propose they go about doing this is through increased training and education, as a continuous effort to keep up with advancing technology. These should be tailored for those who require additional skills to be employable, and struggle to strive in the current educational system. The kind of investment that needs to be made into education is real, technical training specifically for jobs. A university education no longer guarantees a job, unless for specific subjects that lead directly to a certain occupation, and even those jobs may be at risk. The details of these courses cannot be generalised, since the requirements vary per job, but at the very least, everybody should have basic IT skills. The government should financially encourage firms to increase training, since they are the ones that know what skills they demand from their employees.

Another suggestion is a scheme by which instead of increasing taxes, firms are encouraged to increase employment opportunities. Increased taxes should be concentrated on those who earn the most, in order to prevent super managers from exploiting their powers in senior roles. By reducing the significant tax burden on firms and targeting the individuals instead, firms are then incentivised to invest money further into the growth of the company and benefit themselves by employing more, rather than facing the increased tax on high payloads for senior employees.

Evaluation

During this extended project investigating technology's influence on inequality in the world economy, there were many difficulties faced. Technology as a term is so broad and so diverse in its nature, and measuring its effects in detail has been difficult. One of the reasons for this is that it is extremely hard to isolate technology as a variable as it is very closely linked to so many other factors. I have attempted to focus on computer technology, but even this is very broad, if it were possible to dive deeper into specific areas such as the growth of the internet, or increased communication through new hardware, and look at the effects they have had, I would have done so.

Originally, I had planned to investigate the effect on different countries in different stages of the demographic transition model. However doing this would mean that the dissertation would lack focus. Although I could've hypothesised about what is likely to be the case, focus would have been lost in the project, so I decided to refine my research to the US and UK.

I learnt much about research techniques during this process and evaluating sources and weighing each one's credibility/important against one another was key to formulating my dissertation. Throughout the process, my opinion on the topic has changed drastically, initially I was very pro-technology, and only concerned with showing it in a good light. However, as the process continued, I learnt a lot about the negative implications associated with it. It was clear that it shouldn't be overlooked and needed to be dealt with, technological advances are no good if it means that inequality takes a step back. Role of governments in this are quintessential to tackling the problems highlighted and if given the resources and time, coming up with a detailed proposal and solution would be the next thing I would do. Although I have included a section on what I propose, these are mere ideas, without well thought out mechanisms as to how they will be deployed, but that would be the next step.

The aim of this research project is not to dive deep into the mechanisms of inequality, or an in-depth analysis of recent technological advances and how these may influence the economy. The aim is to offer a broad outlook on how inequality will be affected as a whole, and to give a very brief summary on how the two topics and related, and prompt the reader to further read about and understand what the future may hold and the changes that may take place. We are in the early stages of digital technology, and it is absolutely essential to consider and be aware of the future of technology and the social implications it will have.

Bibliography