Artificial intelligence: The ethical dilemma created by labour market disruption

Richard Goold, partner and head of tech law at EY, and his colleague Lauren Anderson explore how artificial intelligence will disrupt the labour market both here in the UK and overseas.
Artificial intelligence (AI) is not a new concept. Technologies that mimic the cognitive functions associated with human intelligence such as learning and problem solving have been around for decades and in many cases have become such routine technologies that we no longer perceive them as being examples of AI.
AI technologies are only now making significant headway at the top of the bill due to the proliferation of the Big Data universe and the massive investments being made in storage, tracking and analytical technologies.
AI systems increase processing speed, reduce mistakes usually caused by human error and minimise labour demand and costs, all while improving customer satisfaction rates.
However, one major ethical dilemma is that while AI will radically increase efficiency in industry and boost national GDP, for many in low-skilled service jobs like call centres, administration and manufacturing – and increasingly in skilled jobs like financial and even legal advisory – this will translate into unemployment and uncertainty. As human jobs are replaced by machines, this could in turn accelerate the already widening economic inequality gap around the world.
Prof. Stephen Hawking recently wrote: “The automation of factories has already decimated jobs in traditional manufacturing, and the rise of artificial intelligence is likely to extend this job destruction deep into the middle classes, with only the most caring, creative or supervisory roles remaining.”
A report put out in February 2016 by Citibank in partnership with the University of Oxford predicted 47% of US jobs and 35% of UK jobs are at risk of automation. In China, it’s a mind-blowing 77%, while across the OECD it’s an average of 57%.
Job creation
There is no doubt AI will significantly disrupt the labour market by automating a significant number of existing jobs. However, this will not necessarily translate to mass unemployment as feared by many. In the past, while technology has made a vast many jobs redundant, it has always ended up creating more jobs than it destroys and will typically reallocate and enable rather than displace jobs. Automating tasks, so that they can be done more quickly and/or cheaply, will typically accelerate business expansion and increase demand for human workers to do other manual tasks that support new technology.
Although it is difficult to predict where new jobs might be created, companies and governments will need to consider investing in education systems to make it easier for workers to acquire new skills so they can switch jobs as needed. One ethical challenge that businesses pursuing a “triple bottom line” will face is whether to take the cost-saving of automation and initiate mass redundancies or whether to take the cost-saving and work to create new jobs and retrain existing employees.
While we are unlikely to see mass unemployment, there is a plausible concern that retraining and job reallocation will not keep pace with the unprecedented levels of automation promised by AI development over the coming decades. This may inevitably result in higher levels of unemployment and greater economic inequality. One widely touted solution for tackling such issues is the concept of a universal basic income, where legal citizens or legal residents are paid a basic unconditional income out of taxation, which may be topped up with work. Such a proposition has been considered by the European Parliament and pilots are currently either underway or anticipated in Finland, Canada, California, Catalonia as well as a number of other jurisdictions.
The development and implementation of AI and its impact on the labour force will create a diverse myriad of issues for government, businesses and individuals alike. Whether the issues are related to legal, regulatory, tax or operational efficiency matters, organisations will need to be prepared for and highly responsive to imminent changes in both social and commercial landscapes.
Stay tuned for the next episode of Tech World, where Richard Goold will discuss this topic further.