Renew's Brogan Meaney asks: do advancements in AI look set to further worsen pre-existing economic inequalities?
We’re no strangers to the chilling cries of robots stealing our jobs. We’re in the midst of a technological revolution, and like during other industry-transforming revolutions that came before, we’re on the brink of a dramatic transition within the workforce -automation.
The fast-paced technological advances within the field of AI have already brought automation to the workplace, with 1.5 million jobs in the UK currently at risk of it. The most commonplace example of automation can be seen inside supermarkets across the country: automated self-checkout tills. As these have already demonstrated, advances within the field of AI will have a dramatic impact on many industries. Although these can mean a more streamlined and efficient workforce, there are other consequences.
For example, the economists Anton Korinek and Joseph E. Stiglitz have argued that economic inequality is one of the main challenges we face in the advancement of workforce technology innovation.
We live in a world where the richest one percent own half of the world's wealth. This results in disparities in life expectancies, seen not only globally, but also at home: in England, the gap in life expectancy between the wealthiest and the most deprived areas can reach up to 9.4 years.
The issue of job automation is a complex, multifaceted problem. We don’t know exactly how technology will advance, or how it will affect wealth inequalities within the UK. However, based on current technologies, the risk of losing your job to automation for those lower-skilled workers far outweighs the risk for higher-skilled workers. The three jobs most at risk are waiters and waitresses, shelf-fillers, and elementary sales occupations; the three least at risk are medical practitioners, higher education teaching professionals and senior professionals of educational establishments.
Although AI will make some jobs obsolete, it will, of course, create new ones. However, these are jobs that will require specialisation. For example, when human supermarket cashiers are fully automated, the ex-cashier would be faced with having to learn new skills or adapt to an unstable reality where they are very much replaceable.
Those most at risk of automation are the ones already economically marginalised within the workforce. The ONS reports that 70.2% of the roles at high risk of automation are currently held by women, and, in addition, the age group most affected by automation are those aged between 20 and 24.
The risk of automation also varies on region. This is due to the jobs available, meaning areas with a greater volume of roles, in particular higher-skilled roles, are safer from the threat of automation. This increases the risks for those who are already both economically marginalised and economically disadvantaged within society.
Current AI research focuses on the importance of policy regulation to prevent exacerbating pre-existing equalities. Democratising access to technology is crucial, as is creating equal opportunities within technological advancement. Some other suggestions have included a universal basic income (which Finland trialled last year), a ‘robot tax’, a focus on lifelong learning and training, especially within the fields of computer science and STEM education. There is also the discussion of privilege within AI advantages, with Korinek and Stiglitz commenting that it is conceivable that the wealthiest of humans will be able to finance, dictate, or sway certain advancements.
These are all attempts to offset inequalities that this workplace revolution will cause. But will they be enough? The automation of certain job roles, or particular aspects of roles, will soon be unavoidable. To prevent worsening economic inequalities, we need a government who takes these issues seriously.
The robots aren't coming - they're already here, says Renew's James Bryan.
“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” - John Maynard Keynes
Based on the decline of manual labour in industries ranging from automotive manufacturing to agriculture, the vast media coverage regarding the rise of automation technology, along with information on the Bank of England site, which gives a probability of losing one's job to automation, it seems Keynes had a point.
Much of the modern drive towards automation is based on advances in the field of artificial intelligence and the creation of more powerful microprocessors. Jobs which were once considered to be the exclusive domain of humanity are now regularly performed by machines. The benefits of automation technology are applicable to virtually any field that one would care to name, it is no understatement to say that data science and better technology saves lives and nowhere is this truer than in medicine. However, this also raises an important question that seems almost philosophical in nature: do jobs exist to employ or to create the output of that work?
As the field of automatable work expands, this question becomes ever more urgent and important. It is clear that the products of automation have lead to greater prosperity and efficiency on a global scale, but research and development of these technologies is an area which requires more investment and greater attention. While the question of technological unemployment does not have a clear answer yet, it is clear that the creation of new policies to deal with the fallout of job-loss on a perhaps unprecedented scale is a vital part of the equation. If this is to be done with minimal negative consequences, those with the technical expertise to understand these issues in their true depth will need to be heavily involved in this process.
If there is a lesson to be learned from how evolving technologies have shaped our political and social landscape, it is that those currently in power have failed time and again to address the implications of the misapplication of data science and artificial intelligence by actors seeking to manipulate public perception and promote their own agenda. Deepfakes, extremely realistic faked footage created using machine learning techniques, aren’t coming; they’re already here. Cambridge Analytica existed and we may never know the true scale of how effective their large-scale social engineering campaigns were.
The reality is, the robots aren’t coming. They’ve come, and these are issues which aren’t going away.
We are currently caught up in one of the largest and most momentous revolutions in human history – whether we know it yet or not. We’re living through perhaps the most fundamental transformation of our environment mankind has ever seen.
The war is not being fought with rifles, bayonets or nuclear force – this time around, the weapons of choice are big data and smart technology. Quieter maybe, but more insidious that its predecessors; the information revolution is changing the way we shop, vote, govern and even think.
We’re quickly waking up to the fact that pivotal changes are underway. But, as tends to be the case with such periods of upheaval, it’s almost impossible to say where they’re headed until they get there. With the conclusion of the digital revolution still a very long way off, we won’t be granted the luxury of hindsight as a means of understanding this change. It’s not for want of trying either – academia across disciplines is riddled with attempts to explain our new and interconnected world.
In the face of such uncertainty, we have a tendency to revert to what we know - ideas that have helped to explain the past but are no longer helpful in trying to understand the future. We see this all the time in our politics, but it often leaves us staunchly on the back foot and ill-prepared for challenges to come.
In her new book, The Age of Surveillance Capitalism, Shoshana Zuboff puts forward a welcome new attempt to describe the effects of digitisation. The focus is not necessarily the workings of the Facebook/Google/Amazon clan themselves, but rather, on the ways in which they are shaping the wider context of global capitalism as we know it. Zuboff describes the new evolution of capitalism that has emerged from big tech as ‘Surveillance Capitalism’ – a system that both relies upon and utilises big data to achieve its ends.
So-called surveillance capitalists – online service providers in their myriad forms – are able to monitor the behaviour of their user bases with a remarkable degree of detail and accuracy. While many of us feel comfortably veiled in algorithmic obscurity, in reality, tech giants are covertly collecting hundreds of thousands of bytes of data each day; data which can be fed back into improving algorithms and making predictions on the behaviour of their users. Much of this happens without explicit or obvious consent.
At best, these processes contribute to service improvement, creating more user friendly interfaces and intuitive design. At worst, the acquisition of behavioural data is used to develop highly sophisticated machine intelligence capable of predicting what you will do now, soon and later. As these techniques improve, usership grows – a feedback loop which, without regulation, could continue indefinitely. Prediction techniques and their ability to influence human behaviour are already having huge implications for the political and economic landscape, creating and shaping new markets and voting behaviours at the whim of the corporations that control them.
Digital hegemony is already well-established and will become yet more deeply entrenched as data is used to facilitate its own growth. It’s becoming increasingly important to re-examine the way we look at the wider system as the power dynamics within it begin to shift.
Traditionally, economic theory has relied on the assumption that market forces are dynamic, unpredictable and ultimately unknowable. The State should refrain from attempting to regulate or constrain markets on this basis, just as agents in a market-place are free to compete with each other in mutual ignorance. But with the rise of big tech, these fundamental principles have changed. It is essential that our assumptions about markets change with them.
Global tech firms now know too much to be granted the same licence as other free market actors - after all, under their influence, markets are no longer truly free. There’s no easy fix, either - the acquisition of user data is so deeply inherent in the operations of online service providers that self-regulation would be almost impossible.
Rather, it may be time to rethink our unquestioning faith in free-market economics - if for no other reason than the fact that markets are demonstratively becoming less and less free. The governing principles of the 20th century are becoming increasingly less relevant as time progresses, and less able to cope with this rapid, systemic change.
The absence of state regulation risks the rise of insurmountable monopolies that wield too great an influence over our markets, our behaviour and our democracy. Legislation against this will no doubt be hugely challenging, but the consequences of shying away from the problem will be more challenging still.