The Age of Automation

Introducing the RSA’s new report on artificial intelligence, robotics and the future of low-skilled work

By Benedict Dellot and Fabian Wallace-Stephens

Follow Benedict and Fabian on Twitter @BenedictDel @Fabian_ws

This article is an extract from the RSA report The Age of Automation: Artificial intelligence, robotics and the future of low-skilled work

A new machine age beckons

Public interest in artificial intelligence and robotics is gathering steam — and for good reason. Recent years have seen the emergence of machines that can diagnose cancers as accurately as pathologists, detect fraudulent financial transactions in a matter of milliseconds, produce coherent news stories for media outlets, shuttle goods and pallets within complex distribution warehouses, trade stocks and shares in financial markets, and perform case research for the legal industry. The breadth and depth of accomplishments expands by the day.

It is therefore unsurprising that fears have grown in tandem about what AI and robotics might mean for workers. It is four years since the University of Oxford published its landmark study predicting 35 percent of UK jobs could be made obsolete by new technology. But since then, anxiety about automation has only become more acute. Alarming newspaper headlines such as ‘Robots will destroy our jobs — and we’re not ready for it’ and ‘Robots will take a third of British jobs by 2030’ are now common. So too are the warnings from esteemed technologists and economists, such as Elon Musk, Mark Carney and Bill Gates.

But are we right to be worried? Are humans destined for the scrapheap as some suggest, or will we find new jobs and niches in a world saturated by machines? These are the questions we sought to answer in our study on AI and robotics. In doing so, we have tried to broaden the conversation out from an almost exclusive focus on the number of jobs that might be lost, to look at how the nature and substance of jobs are likely to change. This means examining the potential impact of technology on recruitment, pay, progression and productivity, as well as whether it will make jobs more or less fulfilling and purposeful.

Our research has paid particular attention to low-skilled workers, who have naturally faced greater economic challenges than most.

Nearly a third of elementary workers (which includes waitresses and cleaners) have household incomes below the poverty line, as do 22 percent of process, plant and machine operatives. Prospects for progression are also minimal. Barely 1 in 10 workers who were low paid at the beginning of the last decade had escaped low pay by the end. Added to this is the growth of non-standard forms of employment such as temporary work, agency arrangements and zero hour contracts, which afford fewer rights and protections.

Job availability: reasons to be hopeful

Will AI and robotics make matters worse? They will undoubtedly cause the loss of some jobs, whether it is picking and packing robots that usurp warehouse workers, or algorithms that take the place of professionals in financial services firms. But there are several reasons to question claims of mass automation (at least in the short-medium term):

• Technical limitations — Despite impressive advances in the capability of machines, there are still many things they cannot do. As entrepreneur and technologist Gary Marcus recently put it: ‘Robots fall over while opening doors, prototype driverless cars frequently need human intervention, and nobody has yet designed a machine that can read reliably at the level of a sixth grader, let alone a college student.’
• Task vs. job automation — In most cases, AI and robotics will automate individual tasks rather than whole jobs. And because jobs usually encompass a range of functions, the automation of one task means workers will be able to pivot into new roles. No machine can wholly substitute for retail assistants, care workers, hotel receptionists, warehouse workers or building labourers. These occupations are more likely to evolve than be made obsolete.
• Technology complements and creates — AI and robotics will not just substitute for workers. They will also complement them and create new tasks not previously done by humans. Examples include robotic systems used by overburdened care workers to help lift patients, algorithms that enable doctors to recommend more appropriate treatments, and chatbots that provide call centre workers with partially automated responses to speed up customer support.
• New jobs will emerge — Some of the fastest growing occupations in the UK are in the technology industry. The number of programmers has grown by 40 percent since 2011, while the ranks of IT directors have doubled over the same period. Tech jobs alone are unlikely to replace those lost to machines, but they will spur job creation in ancillary sectors. The Berkeley economist Enrico Moretti estimates that every new job in the tech sector has the potential to generate 5 complementary jobs elsewhere.
• Demand will be recycled — Automation must also be looked at through a macro lens that accounts for feedback loops. One of these is the phenomena of shifting or ‘recycled’ demand. Rising productivity caused by new machines may lead to a lowering of prices, thereby freeing consumers to spend money in the same sector or another part of the economy. In cases where demand is elastic (i.e. goes up and down with prices), automation may not lead to aggregate job losses.

While we do not wish to dwell on automation estimates, which are often misleading and superficial, our RSA/YouGov poll of business leaders indicates that 15 percent of private sector jobs in Britain have the potential to be fully automated in the next decade. However, we found wide variation among our respondents, with a fifth (22 percent) saying they see zero prospect for job automation in the business they work for. Thirty-eight percent predict a low impact (between 1–15 percent of jobs automatable), 27 percent a medium impact (between 16–30 percent of jobs automatable), and just 13 percent a high impact (more than 31 percent of jobs automatable).

Regardless of their estimates, most studies reveal a technological bias against low-skilled and low-paid workers. Yet some sectors will be more affected than others.

While retail and logistics stand out as highly automatable industries, the picture is markedly different for sectors that are bound up in person-to-person interaction. Just 4 percent of business leaders in hospitality and leisure, 2 percent in medical and health services, and 3 percent education see the scope for high automation among their workforce (although these last two figures should be interpreted with caution given low sample sizes). This finding is reflected in current job growth rates, with primary and nursery teaching professionals up by 40 percent since 2011, and educational support assistants up 50 percent.

Job quality: a matter of choices

We conclude that jobs are more likely to evolve than be eliminated, and that new occupations will emerge in the long-run, often of a more valuable and ‘human-centric’ nature. What is less clear is how AI and robotics will change the quality of work:

• Recruitment — Just as new machines will affect the number of jobs available in the future, so too will they alter the way people access that work. Software is coming on stream that can help recruiters by screening CVs and analysing gestures and expressions during interviews. Some believe these algorithms will entrench existing biases in workforce recruitment, yet others think they could eliminate prejudice. AI is also being used to power on-demand platforms, which have been simultaneously praised for creating jobs and condemned for diminishing worker rights.
• Pay — New machines may de-skill occupations, thereby lowering barriers to entry and reducing the bargaining power of workers in existing positions. Deep learning algorithms capable of detecting cancers may enable lower skilled nurse practitioners to complete diagnoses that usually take radiologists a decade to train for, with the latter losing out as a result. On the other hand, there is evidence that AI and robotics could boost wages due to sizeable productivity gains, which will generate more absolute wealth that can be shared with workers.
• Experience — AI and robotics may pave the way for a ‘digital Taylorism’, with employers using new tools to control the minutiae of workers’ day to day activities. Or technology could humanise jobs and phase out dull, dirty and dangerous work. The LSE’s Leslie Willcocks, who has examined the take up of technology in companies such as Associated Press, reports that in most cases “we found staff not feeling threatened by automation but instead appreciating having fewer repetitive tasks”.
• Consumer power — AI and robotics will not only affect people at work but also in the home — as customers, patients, learners and political citizens. The experience of history tells us that technological advances more often than not supercharge living standards, and AI and robotics are almost certain to sustain this trend. Robo-advisory services in finance will open up financial advice to more people, AI in healthcare will improve the detection and treatment of diseases, and algorithms used in education will enable personalised learning.

Quick to criticise, slow to adopt

The message here is that technology is not predetermined to result in a particular outcome. As a society we have a choice in how to apply AI and robotics and manage their effects. There are choices to be made by developers and engineers in terms of the functionality they imbue in machines, there are choices to be made by employers as to which technologies they purchase, there are choices to be made by HR teams as to whether and how they help staff evolve into new roles, and there are choices to be made by policymakers about the kind of regulatory, welfare and tax system that can maximise the upsides of disruption and minimise the downsides.

As a society we have a choice in how to apply AI and robotics and manage their effects

These choices, however, are only relevant so long as the technology is being deployed. Indeed, just because a machine can do something, does not mean that it will be bought, integrated and licensed to do so. And herein lies the rub for the UK: while as a society we have been quick to lament the rise of AI and robotics, as an economy we have been slow to adopt these technologies.

Sales of industrial robots to the UK fell in the period between 2014 and 2015, with the UK purchasing fewer robots than France, the US, Germany, Spain and Italy. Today the UK has just 33 robot units for every 10,000 employees, compared with 93 in the US and 213 in Japan.

These figures must be seen in the context of our smaller manufacturing base — still the biggest outlet for robotics. But in many sectors the UK has a poor record of investment. Data from the World Bank shows the proportion of UK GDP accounted for by gross fixed capital formation — a measure of investment that includes private and public sector spending — has fallen by 7 percentage points since 1990.

Our RSA/YouGov poll finds that just 14 percent of business leaders are currently investing in AI and/or robotics, or plan to in the near future (the figure is just 4 percent for small businesses). Many think the technology is too costly or not yet proven. For others, concepts such as machine learning, deep learning and cloud robotics appear to be completely new.

Some may view the slow diffusion of technology as the ideal outcome. It will give society time to adjust. Workers can keep hold of their jobs for longer. There will be less need to retrain and shift careers. Business can carry on as usual. Yet it is worth reminding ourselves what business as usual means. The status quo is a largely low-skilled, low-paid, low productivity labour market that offers too few people the chance to flourish at work. Real median wages are still below their pre-crisis levels — an outcome reflected in our abysmal productivity rates. On average, UK workers are 30 percent less productive than their counterparts in the US.

Our problem is not with the number of jobs available today but rather with their quality.

Accelerating automation on our own terms

The central argument of this report is that the deployment of AI and robotics could help the UK forge a path towards a better world of work. New technologies could phase out mundane jobs, raise productivity levels, open up the door to higher wages, and allow workers to concentrate on more human-centric roles that are beyond the technical reach of machines. This is just as true for low-skilled workers as it is for high-skilled ones. But we cannot be complacent. AI and robotics if deployed on a large scale would result in both losers and winners. Some geographic areas, demographic groups, occupations and sectors will be hit harder than others. Economic inequality could rise, geographic disparities could deepen, and demographic biases could become further entrenched.

The deployment of AI and robotics could help the UK forge a path towards a better world of work

The challenge, then, is to accelerate the adoption of AI and robotics but in a way that delivers automation on our own terms. Our existing policy framework appears ill-prepared for this task. Our tax system leans too heavily on labour over capital, our welfare structure lacks a sufficient safety net to protect those who lose out to machines, our educational institutions do not do enough to support lifelong learning that would aid career shifts, our inflated housing market prevents people from moving in search of better work, and our investment communities seldom distinguish between supporting benign and malign technologies.

But an alternative path exists. While it is beyond the scope of this study to lay out fine-tuned recommendations, we suggest several interventions that would help bring about inclusive automation.

Among our ideas are to:

• Develop an ethical framework to guide the behaviour of AI and robotics engineers,
• Encourage VCs and non-profits to invest in benevolent technology that enriches the worker experience,
• Establish a Centre for AI and Robotics that encourages greater take-up of innovations among industry,
• Create personal training accounts that aid lifelong learning and help workers as they jump from job to job,
• Shift the burden of taxation away from labour and towards capital, and
• Draft a blueprint for a UK sovereign wealth fund that would give every citizen a ‘technological inheritance’.

In the frenzy of commentary on automation, it is easy to lose sight of a simple but profound truth: that technology does not arrive out of nowhere, but is humanity’s creation to be wielded as we see fit. It would be a tragedy if we were to let a failure of imagination and a dearth of leadership deny us its gifts.

AI and robotics promise to extend lifespans, eradicate famine, tackle climate change, and help us manage an ageing population. If there were a question we should be asking, it is not how can we live with these technologies, but rather how can we live without them?

Key findings from our RSA/YouGov survey of UK business leaders

• Business leaders on average believe 15% of jobs in their organisation have the potential to be automated
• 22% see zero prospect for automation in their business
• 38% predict a low impact (between 1–15% of jobs automatable)
• 27% a medium impact (between 16–30% of jobs automatable)
• 13% a high impact (more than 30% of jobs automatable)
• Estimates of high impact automation vary widely by sector:
• 15% of business leaders in retail
• 21% in transport and distribution
• 4% for hospitality and leisure

The adoption rate of AI and/or robotics is low among UK business leaders:

• Just 14% have already invested in AI and/or robotics, or plan to in the near future
• 20% say they want to invest but that it will take several years before they will ‘seriously’ do so
• 14% are aware of the technology but believe it is too costly
• 15% are aware of the technology but do not believe it has been properly tested
• Most business leaders take a positive stance towards the arrival of new technologies in their sector (including but not limited to AI and robotics):
• 46% think new technologies are more likely to alter jobs than to eliminate them, and lead to greater prosperity in the long run
• 15% think new technologies will lead to the significant automation of jobs, harming livelihoods in the process

There is lukewarm enthusiasm among business leaders for radical policy solutions to technological disruption, although surprising backing for some ideas:

• 44% back more priority to vocational education and lifelong learning
• 34% back employee ownership models
• 31% back a Universal Basic Income

This an abridged account of the full survey results.

Automation anxiety

Of all the innovations set to impact the labour market in the 21st century, few have received more attention than robotics and artificial intelligence. Recent books including Rise of the Robots (Ford), Only Humans Need Apply (Kirby and Davenport) and Race Against the Machine (McAfee and Brynjolfsson) predict these technologies will change the face of modern employment, possibly beyond recognition. Whether it is driverless cars or surgical robot assistants, banking ‘chatbots’ or self-service checkouts, it is now common to hear of how new machines are stepping in for humans at work (a process known simply as ‘automation’).

The public reaction has so far been a combination of marvel and trepidation — feelings that are reflected in popular culture. TV shows and films such as Humans, Ex Machina and Automata are both feeding off and fuelling interest in the power and possibilities of AI and robotics. Nor have developments escaped the attention of policymakers.

Both the UK and US governments have investigated the potential impact of these technologies on the workforce, and earlier this year a new All Party Parliamentary Group was launched to consider the ramifications of AI. Added to these are independent reviews, such as The Future of Work Commission, led by Tom Watson MP, and the Royal Society’s Machine Learning inquiry.

Such interest is understandable given the huge sums of money now flowing into these technologies, the definitions of which we unpack in another article. The amount of venture capital funding going into robotics doubled between 2011 and 2015 to $587 million, while the number of mergers and acquisitions of AI start-ups went from 11 in 2012 to 78 in 2016. Several of these deals involved UK companies, including DeepMind (bought by Google), SwiftKey (Microsoft) and Magic Pony (Twitter). The global market for robotics and AI-based systems is expected to grow from $58bn in 2014 to $153bn by 2020.

Four voices on automation

Not everyone is in agreement about the consequences for workers. Internet law and policy expert Robert Cannon believes that “everything that can be automated will be automated”, while Amazon CEO Jeff Bezos claims “It’s hard to overstate how big of an impact [AI is] going to have on society over the next 20 years”.

In stark contrast, the new US Treasury Secretary Steve Mnuchin has said the prospect of significant job automation is “not even on my radar screen”. Likewise, the economist Robert Solow has mocked that “the fear of automation is rather like the fear of collision with an enormous asteroid.”

Division in opinion is not limited to a handful of public figures. A Pew poll of technology and business experts found a 52:48 split between those who believe AI and robotics will create more jobs than they destroy, and those who think the opposite. There are also widely different estimations of how many jobs are likely to be displaced by new machines. Carl Benedikt Frey and Michael Osborne from the University of Oxford predicted in 2013 that 35 percent of UK jobs had the potential to be automated, whereas more recent studies put the figure at 10 percent (OECD), 5 percent (McKinsey), and 30 percent (PwC).

Yet whether jobs are likely to be rendered obsolete or not is only one dividing line in the complex debate about technological disruption. At least four different camps of opinion on technological change can be discerned, including those who deny it is even happening on the scale widely presumed:

• Alarmists — Alarmists believe in an irresistible march of AI and robotics that will lead to the mass automation of jobs, rising inequality and economic strife — unless imminent action is taken. Writers like Martin Ford acknowledge that technology has historically led to new and better jobs in the long-run, but argue that the pace of recent improvements in AI and robotics will mean that ‘this time is different’: more destruction, less creation. Many, including Ford and the journalist Ryan Avent, are doubtful that upskilling the workforce will help, pointing as proof to a dwindling number of high-skilled jobs. A Universal Basic Income is presented as one solution, possibly paid for by a ‘tax on robots’, as was recently suggested by Bill Gates to much controversy.
• Dreamers — Dreamers believe, just as Alarmists do, that new technology will lead to the mass automation of jobs. However, their stance is that this could usher in a utopia of a leisure society where workers are emancipated from the drudgery and dullness of modern work (a ‘digital Athens’). Instead of railing against the machines, Dreamers call for greater investment in technology and for the productivity gains to be used in pursuit of reducing worker hours (or ‘full unemployment’). Alex Williams and Nick Srnicek, two leading leftwing proponents of automation, have, like the Alarmists, called for a Universal Basic Income, as well as for the use of public funds to ‘democratically control’ how technology develops.
• Incrementalists — Incrementalists believe AI and robotics are sophisticated technologies, but with a long way to go before they make humans obsolete at work. They see the force of technology as a gradual rising tide rather than a fast approaching tidal wave, and believe that new machines are more likely to evolve jobs than eliminate them. For the writers Julia Kirby and Thomas Davenport, AI and robotics will augment the human workforce, giving the mundane to the machines and the purposeful to the people. It is up to employers and educators to help workers respond by ‘stepping up’ or ‘stepping aside’, meaning respectively to find jobs overseeing machines or to find a human-centric pursuit that is resistant to automation, such as in healthcare or education.
• Sceptics — Unlike the other three camps, Sceptics claim that recent innovations — including in the realms of AI and robotics — are mediocre compared with past inventions. In their view, the low hanging and richest fruits of technology have mostly been harvested, and only modest innovations remain to be discovered. Among the Sceptics’ founding fathers are Tyler Cowen and Robert Gordon, the latter of which has argued that the invention of indoor plumbing was more consequential for mankind than the advent of the internet. As proof of their claims, Sceptics point to the plateauing of productivity levels around the world, a phenomenon Cowen has labelled ‘The Great Stagnation’.

Focusing in on the low-skilled

Each of these camps has been tussling for position for at least a decade. Yet the debate has been squarely focused on assessing automation’s impact on one group: middle-skilled workers. There is now a broad consensus among all but the most ardent Sceptics that the labour market underwent a form of ‘hollowing out’ during the 1990s and early 2000s, albeit with a subsequent filling in of middle-skilled jobs as other professions plugged the gap.

According to the Resolution Foundation’s analysis, jobs in the middle of the pay distribution, such as secretarial and manufacturing work, fell markedly as a share of total UK employment between 1993 and 2014. In contrast, there was a large growth in the number of customer service roles and health and social care professionals (e.g. housing officers and paramedics) — jobs that are known to be less routine.

But what about low-skilled work? Less attention has been paid to jobs like caring, cleaning, driving and waitressing, largely because they embody tasks that demand manual dexterity and complex manoeuvring, which were once thought too difficult for machines to mirror. The technology that is coming on stream today is now challenging those assumptions.

Advances in modelling ‘belief space’, for example, has led to breakthroughs in situational awareness and the ability of robots to grasp objects and replicate hand-to-eye coordination. Meanwhile, developments in materials science and the use of air muscles and ‘ferrofluids’ have made robots more life-like and dexterous. Equally significant has been the emergence of cloud robotics, allowing machines to share data and continually learn from the experiences of others (see What’s the difference between AI and robotics? for a full introduction to AI and robotics).

It is important to understand how AI and robotics might affect low-skilled workers for two key reasons.

The first is that they make up a considerable chunk of the UK labour market. While the ONS does not offer a strict definition of ‘low-skilled’ employment, it does classify occupations by their skill level. This suggests there are 13.9 million low-skilled workers (levels 1 and 2) in the UK, accounting for 45 percent of the workforce. This includes 1.1 million retail assistants, 769,000 care workers, 325,000 teaching assistants, 281,000 waiting staff, 541,000 cleaners and 232,000 taxi and cab drivers. Moreover, the number of low-skilled workers is expected to expand rapidly in the years to come, with as many as 400,000 caring personal service roles set to be created between 2014 and 2024.

The second reason is that low-skilled workers already face pressing challenges in the workplace, having been at the sharp end of a slow economic recovery. 30 percent of elementary workers (which includes waitresses and cleaners) have household incomes that push them below the poverty line, as do 22 percent of process, plant and machine operatives, and 20 percent of workers in care and leisure occupations. Low pay is in turn reflected in a dearth of assets and savings. More than half of all workers in elementary, machine operative, and sales and customer service roles have £1,000 or less in gross financial wealth, leaving them vulnerable to the slightest of setbacks such as an illness or bereavement.

Who are you calling low-skilled?

The degree to which work is deemed high-skilled, middle-skilled or low-skilled tends to be based on an assessment of its technical intensity, and the degree to which formal training and qualifications are required to fulfil the role. However, this overlooks the empathetic intensity or emotional intensity associated with many forms of work, including caring, teaching and some forms of retail.

It is not within the remit of this article to offer fresh definitions or frameworks for understanding worker skill level, and indeed we are somewhat constrained by the reams of literature and data that use traditional notions of low-skilled work. But we have endeavoured to be mindful of this limitation and will seek to address more extensively in future research.

This is just the static picture. Equally troubling is the lack of dynamism at the bottom end of the labour market, with too few workers seeing any progression in pay or skill level. According to the Social Mobility Commission, barely 1 in 10 workers who were low paid at the beginning of the last decade had escaped low pay by the end.

Added to this is the growth of non-standard forms of employment such as temporary work, agency arrangements and zero hour contracts, which afford fewer rights and protections. According to the OECD, almost all the aggregate increase in employment in the UK between 2007 and 2013 was owed to contingent work of this kind. As many as 1 in 7 care workers and 1 in 4 waiting staff is on a zero hour contract.

Neither are the problems that beset low-skilled workers solely of a financial kind. Just as many jobs are low paid and characterised by volatility, so too do many lack meaning and purpose. Others still constrain the autonomy of workers and leave them with little space to use their initiative and talents.

The recent exposés of worker mistreatment in retail and ecommerce warehouses may be at the extreme end of bad practice, but they are indicative of a broader disregard for agency and dignity in low skilled jobs. Only 21 percent of process and plant operatives are satisfied with their involvement in decision making at work, while an underwhelming 59 percent of elementary workers (e.g. warehouse workers) are satisfied with their sense of achievement.

The low-skilled are not one homogenous group. The experiences of teaching assistants and childcare minders will vary considerably from those of warehouse operatives and kitchen staff, as will the satisfaction of workers within these occupations. We should also be mindful not to exaggerate the levels of insecurity facing these workers.

The rise of gig work– where people find small jobs through online platforms or apps — has been rapid but still only 3 percent of UK adults have engaged in this work. Most of the workforce including low-skilled workers continue to be employed in conventional jobs that pay a predictable wage. What we can say with some certainty, however, is that for too many people in today’s labour market, work is far from a labour of love.

Friend or foe?

The question this report asks is whether AI and robotic technologies will add further pressure to an already ailing workforce, or whether they will be a welcome reprieve by boosting the quality of work and raising levels of pay and productivity.

On the surface, the answer is obvious: machines are becoming more sophisticated and this can only mean the displacement of workers and the driving down of wages. It is easy to imagine driverless cars pushing the UK’s 232,000 taxi drivers out of business, just as it is easy to picture self-service checkouts diminishing the need for many of the country’s 1.1 million retail workers. A glance at media headlines also foreshadow a gloomy future. ‘Millions of UK workers at risk of being replaced by robots’ and ‘Robots to steal 15 million jobs in the next 15 years’ are typical of the pessimistic captions that regularly appear in national newspapers.

Positive employment gains have been made in the UK in more than three quarters of the years since 1971, in spite of technological advances

There are several reasons to doubt these sweeping claims, however. Number one is that the UK enjoys the lowest unemployment rate in a generation. More people want to cut their hours than want to work more hours, suggesting that work is plentiful in many occupations and sectors.

Moreover, history is littered with claims that new machines would make humans obsolete in the workplace, only for these to be dashed as new jobs and occupation types emerged. Positive employment gains have been made in the UK in more than three quarters of the years since 1971, in spite of technological advances. One need only look at day-to-day technologies — self-service checkouts, ATMs, automated customer helplines — to see their limitations and the interdependency of human and machine.

As with every topical issue, there is more to the sensational headlines and snappy statistics than first appears. Through this report we hope to clear up inaccuracies and enrich people’s understanding of the impact of AI and robotics — both the opportunities and the threats. What is the technology capable of and how has it evolved in recent years? How are low-skilled workers in different occupations and sectors likely to be affected? Will AI and robotics even be adopted at the rate some suspect? And what can the government, employers, educators and regulators do to prepare the workforce of today and tomorrow for any disruption?

We hope to add particular value by:

• Capturing the views of employers, whose voices are often missing from debates on technology, yet who are ultimately the ones who buy and deploy it
• Looking at how technology affects the quality of work as well as its quantity, such as what it means for pay, productivity, progression and agency
• Discussing the value of technology as it relates to broader societal challenges, including an ageing society, climate change and rising pressures on public services
• Setting out policy and practice prescriptions that extend across the technology lifecycle, from the point at which machines are conceived to the time they are deployed in workplaces.

Our starting point is to state clearly that the trajectory of AI and robotics is not predetermined, but rather can be moulded to suit our own ends. A common theme we will return to in this report is that we do have choices as a society over how we marshal technology for the benefit of workers. Developers can choose what features they code into software. Employers can choose which types of robots or AI systems they purchase. Regulators can choose what constraints to put on industries and employers. Educators can choose which skills and qualities they want to develop in the workforce of the future. And the government can choose how it sets its tax and welfare regime to ensure those who gain the most from technological disruption support those who stand to lose the most.

We firmly believe there is such a thing as automation on our own terms, and we hope the rest of this report spells out a positive vision for how this can be achieved.

You can read further articles from our report on the ‘Age of Automation’ here:

How will automation change the nature of work?

How AI & robotics are transforming social care, retail and the logistics industry

What’s stopping UK businesses from adopting AI & robotics?

Automation on our own terms

What is the difference between AI & robotics?

To find out more about our research, please contact Benedict Dellot

For full references and bibliography please visit the RSA website to download the full report