AI and its Impact on Jobs

The world, at the moment, is awash with speculations, opinions, and fears about artificial intelligence and its perceived `threat’ to human held jobs. Many researchers and scientists are still of the conviction that AI cannot, in actuality, replace human intelligence. They still maintain that AI can assist and augment but never take the place of humans at the workplace.

AI has been an area of passion and pursuit for a long time. However, it is in the recent years that it has come to stay, moving from the research desk to active field. AI is now dominant, taking on an exponential role, influencing particularly the fields of gaming, natural language processing, speech and handwriting recognition and robotics.

Since artificial intelligence is poised to take on many tasks that the human has so far been performing, is there a threat of unemployment across the globe? How is AI going to impact the job scene world over?

Leading research and advisory firm, Gartner comforts job holders in its statement: Robots are not here to take away our jobs; they’re here to give us a promotion. Instead of replacing the human at work, artificial intelligence may increase the number of job opportunities, especially in healthcare, public sector, education, to name a few. As the gig economy is gaining popularity, retail, manufacturing and transportation could possibly be the first to adopt AI for work. Industry heads are not as optimistic as Gartner. Leading personalities Elon Musk and Stephen Hawking feel AI may go beyond taking away people’s jobs. AI could eventually become a real threat to human beings. For now, it is helpful and comforting to go with Gartner’s report which states by 2020, AI will generate 2.3 million jobs, exceeding the 1.8 million that it will remove.

When one of the Big Four consulting firms, Deloitte delved into UK census data for the last 140 plus years only to discover that technology has very steadily taken over many jobs that were being handled by humans. Deloitte also quickly pointed out that jobs in the professional sector have increased multifold.

This pattern of generating new jobs as and when a machine takes over current jobs will continue in this era of AI. Emerging technologies will allow for emerging new jobs, not only for people working with new technologies but also for the enablers who need to manage the increasing requirements of content development and training to bring people up to speed.

The fact is, AI is contributing in a major way to the evolving landscape of work. Going back to the gig economy, the concept is gaining prominent space as it provides scope for professional work within a time-bound period.  The big gig companies differ from traditional firms not only in conducting business online but also in allowing and encouraging individuals to freelance and engage `just in time’. As TED CEO Richard Saul Wurman sums up the online marketplace platform: For the first time in human history, individuals can design a life around the pursuit of interesting work.

AI is going definitely going to define the way work happens. How much humans will be involved in `working’ is a subject of speculation for anyone who is familiar with AI. But if we have to think about the next decade, we need to remember though AI is enabling a machine to be independent of man, it is dependent on data. The more data AI consumes the smarter it gets. But to sift data and feed AI and obtain output is a process as laborious as the creation of AI.

Google AI chief John Giannandrea explained this concept of AI’s need to be fed data by using an example involving his 4-year-old daughter. She was able to identify a 19th-century “penny-farthing” bicycle anywhere once he had told her what it was. But computers, need to be shown 100,000 penny-farthings before identifying one. Once they’d seen 100,000, they’d probably be better at identifying them than humans are.

Companies may talk at length about AI and secretly look forward to right-sizing their employee base by bringing in machines. However, they would need to clean up messy databases, work on file management and in overall make their data algorithm-friendly, before any machine can really take over a man’s job. How long will this take? Well, time will tell.