By Sandip Sen
In 2009, Martin Ford, the author of The New York Times best seller, ‘The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future’ predicted the loss of millions of jobs held by assembly line workers, cab drivers and retail store employees to automation driven by AI. In 2015 he wrote the award winning book ‘Rise of the Robots: Technology and the Threat of a Jobless Future’. At a conference in 2016, he said, “I wrote that self-driving cars might happen one day, and within six months of that book being published, we already had such a vehicle on the road,” he said. “It’s possible that taxi drivers and truck drivers will soon be out of work.’’
The acceleration of change
Martin Ford, may be one of the early voices warning us of the advent of thinking machines that will not only replace humans in repeat jobs but also in places where some intelligence is needed. But he is not the only one. For years, futurists are trying to warn us of the jobless days ahead, and everyone knew that change was inevitable. What nobody had expected was that the machine learning advancements would come so soon. While Ford penned down his writings, scientists were actually perfecting the prototypes of the driverless cars.
A lot of the fears of the early thinkers is actually happening today. Several technology companies are using AI for coding jobs and reducing staff, and Indian IT companies have shed more than 50,000 jobs this year due to automation in-house as well as at the client end. Even big retailers like Walmart have announced that they will be replacing 6000 jobs using automation. Automobile major Toyota will be replacing welders, brazers, machinists and automotive diagnostic personnel by the hundreds in their plants due to the advent of AI. Whereas a welder’s job can be called a repeat job, the diagnosis work is a highly skilled work of multifunction specialists being performed previously by an army of highly trained and high paid quality control inspectors. They were highly sought people responsible for vehicle safety. Today, a large number of them have been replaced by intelligent machines.
From 2020, it will not be the change or the speed of change, but the acceleration of change that will be disruptive and threatening. Each year, more and more frontiers will fall to AI. They will not only threaten low end jobs, but also very high end ones. Those needing extensive analytic skills that will be either supplemented by machine learning or totally done by AI. For example, the work of a radiologist is one that will increasingly be done by machines to ensure better results. But, it will not be losses all the way.
A September 2018 study by Professor Ken Goldberg of UC Berkeley with Vinod Kumar, CEO and Managing Director at Tata Communications, released at London identifies how AI can help diversify human thinking, instead of replacing it. The study identifies opportunities for humans and businesses based on discussion and insights from 15 in-depth interviews with 120 global leaders. Among them were thought leaders, CXOs and entrepreneurs, including Tony Blair, the former UK Prime Minister, who is the Executive Chair at the Institute of Global Change.
Tata Communications confirms that the key findings of the study show that nine out of ten leaders agree that cognitive intelligence is important to management decision-making. Broadly speaking, leaders thought that ‘multiplicity can enhance cognitive diversity, combining categories of intelligence in new ways to benefit all workers and businesses’. That, nine out of ten leaders believe that AI will enhance decision making. That, three out of four leaders expect AI to create new roles for their employees.
This is a new school of thought that favours the accelerated growth of AI hoping that it will help humans explore fresh vistas that are too complex for humans to solve today. That may be true for challenges such as climate change or volatility of markets or rapid spreading of new viruses are increasingly possessing challenges that governments and businesses across the world are failing to tackle. AI will definitely help in finding solutions to such complex problems.
But whether it will help create more jobs than it will take away is something which we may not put our money now, at least for a decade. This largely because the humans with skills to partner robots using AI will be difficult to find. Though the Tata Communication research presents a credible contra view to the currently prevalent theory, it still cannot be considered as an authentic hypothesis unless a detailed roadmap of identifying such jobs is taken up by the industry groups that employ AI. In short, it would take detailed studies by an automobile industry group to identify which jobs will get created in the industry through AI. Similarly for other industry areas, where respective business process experts must identify and quantify specific job opportunities that AI will bring to those businesses.
AI and machine learning is at the early stage today. It is very difficult to accurately predict its impact, because it is still not a continuous effort from pre-identified sources. If AI cuts jobs, businesses will be quick to adopt it because it will reduce recurring costs. Job losses will be initially intermittent and thereafter sporadic in the next few years till the pipeline of AI churns out solutions on a regular basis. Once that happens, job losses will be disruptive and people will relook at skill sets anew and retrain themselves to fit the scenario. Till today, machines were looking to adopt to human needs to be productive. But AI will turn the tables. Humans will have to retrain themselves to be uniquely productive amidst working robots to justify their job. But eventually they will learn. And that is when more jobs will be created than lost due to AI.