May 4, 2017    8 minute read

What Lawmakers Need to Keep in Mind about Automation

Ex Machina    May 4, 2017    8 minute read

What Lawmakers Need to Keep in Mind about Automation

If one subscribes to the idea of technological unemployment, which is the loss of employment caused by the increasing use of, and development of, technology in the workplace, then the advancing tide of technology is a frightful sight. From the relief of labour workers through ‘machine muscle’ to the reduced need for human input in analysing large data, more automation is reducing the demand for human workers.

Whether one believes that technology only creates short-term unemployment with no long-standing effects (optimist) or whether one believes technologies can create a lasting decline in human employment (pessimist), it is inescapable that more and more companies are seeking to use technology to augment their business processes.

Currently, the oncoming tide of unemployment through automation is yet to make a significant splash. Mckinsey & Company, in their 2015 quarterly report – Four fundamentals of workplace automation – noted that in most cases of automation and computerisation, the worker was not entirely displaced, but rather experienced certain elements of their work being performed through automation. One can see such a highlight with the legal Industry, with more firms and practitioners relying on techniques and systems, such as ROSS Intelligence, to facilitate greater legal work, rather than being entirely replaced.

Furthermore, the current US unemployment rate fell to 4.5% in March 2017,  from 4.7% in the previous month. This was the lowest jobless rate since May 2007, as the number of unemployed persons declined by 326,000, to 7.2 million. Furthermore, The International Bar Association’s (IBA) 120 report April 2017, titled Artificial Intelligence and Robotics and Their Impact on the Workplace, found that of 1,000 manufacturing professionals, two-thirds stated they had not witnessed job losses as a result of automation, with a further 37% commenting that automation had increased job creation.

However, if there were to be a shift in the power of automation, how would employment be impacted? How would the law cope?

Setting the Scene

PricewaterhouseCoopers found, in their March 24th, 2017 report that up to 30% of existing UK jobs could fall victim to automation in the next 15 years, as compared to the US (38%), Germany (35%) and Japan (21%). These impact figures ring truer in more manual and physical labour sectors such as transport and manufacturing and lower in education, health and social work. Upon this, John Hawksworth, chief economist at PwC, commented that manual and routine tasks are “more susceptible to automation, while social skills are relatively less automatable. That said, no industry is entirely immune from future advances in robotics and AI.”

Additionally, The IBA report pointed to the example of a German car worker costing more than €40 (£34) an hour, whereas a robot was priced at between only €5 and €8 per hour.

“A production robot is thus cheaper than a worker in China,” the report notes. Nor does a robot “become ill, have children or go on strike and [it] is not entitled to annual leave”. The poignant example is the erosion of the competitive advantage of poorer, emerging economies which utilise cheaper workforces, as automated manufacturing and computer systems undercut the cost of human labour.

If these statements are held to be true, one could see a rise in technological unemployment in the coming years. Employment is more than simply a source of income, however – it is a status symbol, a source of social interaction, a place to develop technical skills and abilities. Employment can provide fulfilment through to structure and security in one’s life.

On the other hand, unemployment can cause mental health issues, with “on average, those who are involuntarily out of work have higher levels of psychological distress than those who have work,” with such illnesses becoming a barrier to re-employment.

Employment Issues

Firstly, business restructuring, brought on by the introduction of automated work processes, will ultimately reduce the demand for a particular kind of work and could thus lead to redundancies and unemployment. This would also create new opportunities in the workforce, from the relocation of employees to retraining.

For example, an AI research programme would free up legal time, allowing junior lawyers to conduct higher-level work, and so on, thus promoting the value of work along the progression chain.

Currently, it is legally acceptable for an employer to dismiss an employee (by reason of redundancy) if the human can be replaced by a robot. Simply put, the employer need only show they have a reduced demand for employees to carry out work of a particular kind. Yet, robots lack legal personality (and thus the ability to carry liability) and thus cannot be classified as employees. Therefore, it could arise that there is both a situation of redundancy and the employer still requires that employee’s work to be carried out.

In this regard, it can be argued that the law should step in to either offer further protections, through the narrowing of the redundancy definition or regulating the legal status of robots. This is also relevant to issues of health and safety, particularly occupational safety hazards through working with automated machinery. This includes wearable technology such as exoskeletons, designed to enhance worker performance as these technologies could impact general health, from altering posture to straining the body.

Not (Yet) Liable

In addition, the principle of vicarious liability and its interaction with robots creates a further legal question. This is the principle that an employer can be held liable for the wrongdoings or negligence of an employee, yet because robots cannot create primary liability nor do they hold a duty of care under the law, triggering vicarious liability would be difficult for any claimant. Thus, it is suggested that the law requires a significant review in this area, especially considering automated cars and logistics, such as unmanned drones for delivery.

This would also necessitate new skills being tutored to employees, to integrate them into the new processes. An element which the law could protect would be requiring the company to first offer retraining to displaced employees rather than simply firing them and hiring a new worker. Automation will instate the mandatory upskilling the workforce in order to efficiently and effectively utilise the systems, and thus the law could facilitate this. However, one could also argue that this is the law complicating what is essentially a business decision.

A New Type of “HR”

One issue that is brought to the forefront is workplace privacy. A key issue is that of behavioural analysis which can be used in the recruitment process. Employment laws in Western countries commonly protect classes of applicants, aiming to eliminate biased hiring practices. Using behavioural analysis in the recruitment process could have the unintended consequence of ‘automating prejudice,’ unintentionally.

Data on behaviour and other indications of a candidate’s skill collected by the robotic system would be compared to similar data of successful workers already at the company or in the industry. Algorithms in these HR systems sift through resumes to find the top candidates and should the system produced biased results as against age, sex or race, then it would contravene the law.

Yet, this could easily occur if the system prioritises a certain experience or role, inadvertently discriminating against candidates if a class was more likely or less likely to exhibit those experiences. What’s more, if AI and automated systems are used to analyse candidate interviews, it could construe biological responses incorrectly.

A further consideration is the effect on working time regulations. Take for example the EU Working Time Directive, which requires EU member states to guarantee that all employees have a minimum set of rights, from the limitation of weekly working hours to an average of 48, including overtime to paid annual leave of at least four weeks per year.

The immediate consideration is in the reduction of hours that would be created by the introduction of automation, rather than being limited by the hours of work, an employee utilising automation would be limited by the amount of work available. As before, they could only work 48 hours (unless a legally-compliant waiver is signed), whereas the question is now whether there is enough work to fill those 48 hours. Consequently, this could lead to greater reliance on flexible working hours, with employers moving to contract employees in such a way as to respond to short-term fluctuations in demand for work, disrupting the traditional working week. Certainly, this can have its advantages, from enabling more time to be given to travelling workers to facilitating more familial time for those with children.

Automation also impacts collective rights and bargaining power. As aforementioned, there is currently very little protection against redundancy as a result of automation. Consequently, this also impacts collective rights as employers can, cheaply and effectively, replace swathes of workers with little ramifications, undermining social protections and job security. Whether greater security is achieved through extending individual protections or strengthening group rights, the current challenges submitted against Uber can be instructive in this regard.

Conclusion

Automation has raised several important questions, of both economic and political significance. Does automation lead to a rapid relocation and concentration of wealth? Is a universal minimum wage required? Should the government impose ‘human’ quotas?

However, whilst these questions are certainly important, the underlying tool that can be used to facilitate the safe implementation of automation is the law. What is for certain is that laws, as they currently stand, are not adequate to address the incoming tide of automation, AI and Big Data usage.

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