In a machine age can professions who rely predominately on facts and data for judgement or decision making remain immune from artificial intelligence (AI)? How will AI alter recruitment, talent development and tomorrow’s workplace? What skillsets and toolkits will the next generation of doctors, lawyers and financial advisors require to compete with the automation of data. The age of advancing artificial intelligence and machine learning is here and shaping tomorrow’s workplace.
We’ve grown accustomed to decaying factories and abandoned warehouses. We’ve studied what industrialisation and the printing press did to craft workers during the turn of the 19th century. Currently, oil and gas manufacturing yards are seeing less activity due to changing technological and political landscapes. It is now commonplace to see automation in place for some services, which were once recent steadfast employment providers. Fast food kiosks, store check-outs, travel agents and baggage check-ins are all now predominately self-service, faster and more cost effective as a result of automation. It is also accepted that manufacturing jobs may soon become a thing of the past. In 2016, Apple’s supplier Foxconn replaced 60,000 employees with robots, and China’s Everwin Precision Technology replaced 90% of its factory workforce with robots resulting in fewer defects and a higher rate of production. More companies are likely to follow suit. But blue collar jobs aren’t the only ones at risk.
We’ve already begun to see the professional office, traditionally unchallenged, being disrupted. For professions such as law, medicine and finance, it is tempting to believe humans will remain untouched being tradition-bound and labour intensive. However, when you break down any given role it is difficult to see where a machine cannot replace many of the mundane routine daily tasks. Diagnoses, data mining of facts, analysing balance sheets, researching, collating, selecting and sourcing of information is routine and at the backbone of these professions. Today, these tasks are typically carried out by junior trainees, paralegals, young associates, interns or recent graduates. Yet these are the tasks where AI and machine learning excel. We are on the cusp of a transformation according to the Susskind’s, co-authors of “The Future of the Professions” Where they outline a thesis for the approaching end of professional institutions in their current state.
The finance sector, given its heavy reliance on data, is a prime candidate for the automation offered by intelligent deep learning. Online self-service systems have been eroding billable hours and tax preparations may soon be entirely automated. KPMG has been using a system called MAT since 2015 in helping them automate the audit process. It allows for the automation of evidence gathering and the production of complex data reports, saving both time and money.
Increasing automation of the legal sector promises to increase efficiency and save clients’ time and money. The LawGeex platform can automate contracts. It can take a new contract, read it and then compare it to a database of every similar contract that it’s seen in the past. It learns from each review it performs just as every young lawyer does. Law firms are incorporating AI to remain competitive and cost effective. A Deloitte Insight report released in 2016 stated that «profound reforms» will occur in the legal sector over the next decade, estimating nearly 40% of jobs in the legal sector could end up being automated in the long term. Lower-level employees at law firms are more likely to feel the effects of downsizing because of AI. Where will graduates find their place in this new hierarchy?
In medicine, AI is providing faster and more accurate diagnoses. It reduces errors related to human fatigue where doctors may suffer from exhaustion due to the high levels of concentration required. Unlike a human doctor, AI isn’t concerned by the high number of patients it diagnoses or the hours it works. The Da Vinci Surgical System is currently being used as a robot in basic surgical procedures. Such surgical robots already deliver smaller incisions, reduce patient pain, minimise the need for medication, and shorten hospital stays, all of which reduce medical costs.
As many of these tasks are necessary stepping stones in a graduate’s development and career path to becoming medical professionals, technical advisors, investors or consultants, how will they gain their experience in the future? How will their education and internships develop and adapt to make space for both man and machine? Even if human interaction is something we all need, there is no reason we should seek it from our lawyer, financial advisor or doctor. Tasks such as advising clients, writing legal briefs, negotiating and appearing in court all seem beyond the reach of automation but these are for the more seasoned professionals. How are graduates going to be able to gain enough basic experience if their data crunching and labour intensive jobs are replaced? There is no point in trying to beat machines at their own game. Computers may not think, but they do an excellent job at number-crunching to emulate us.
Technological advancements will follow the historical trend: initial disruption, lower production costs, eventual job reallocation and, we hope, an overall benefit to society. Today, an understanding of IT, science, technology and analytical thinking are all highly desirable skills. Yet these are the very skills machines excel at. Being even more analytical may well be the wrong approach. As many before have concluded, from Orwell to Susskind, having empathy is what sets us apart. Gaining trust, individualism, independent and innovative thinking, being able to negotiate and influence others are all part of an empathic toolkit. Professional education and training may need to adjust its focus. Enabling graduates to become better negotiators and influencers straight from college and to begin improving these skills at an earlier than expected stage in the workplace. Employees will require a level of critical thinking and decision-making not easily programmable to compete. Having more empathy may well be what sets us apart from AI. Ironically, the advance of the machine may force humans to become more human to compete. If we have learnt from history a positive disruption will occur.