AI, ML and the Ripple Effect
Automation is at the center of current innovations. Cashierless checkouts, Amazon’s delivery robot Scout, and Boeing’s automated flying cars are all recent examples of how automation is being integrated into the real world. While these automated technologies are applied in various areas, the driver behind these technologies is all the same: the implementation of artificial intelligence (AI) and machine learning (ML). Cashiers, robots, and cars must be intelligent to some degree in order to be automated.
What is AI and ML and why does it matter?
Artificial intelligence refers to the ability of a computer to perform complex, intellectual tasks such as driving or performing deliveries. Machine learning is a subset of artificial intelligence that deals with computers recognizing and solving problems as well as identifying patterns. As computers and machines act more and more like people, people run the risk of losing their jobs to AI and machine learning-driven technologies. According to a report by a think tank called Centre for Cities, nearly one in five jobs could be replaced by AI and machine learning driven technologies by 2030.
While this has yet to happen on a wide scale, the trajectory of the taxi industry serves as a possible case study. Uber, Lyft and other ridesharing companies have put immense downward pressure on the taxi industry’s market share in ground transportation services. According to Certify, taxis market share in ground transportation services has dropped from 37% to less than 6%, displacing thousands of taxi drivers from work. While these old taxi jobs are being replaced by gig economy driving opportunities, most ridesharing companies are invested in AI and machine learning through the research and development of automated cars. With the implementation of self-driving cars, the ground transportation services could potentially be entirely automated, eradicating all these drivers’ jobs thanks to AI and machine learning.
The implementation of AI and machine learning technologies have the potential to be widespread and to penetrate multiple industries. In finance, algorithmic trading, market analysis, and portfolio management could all be done by a computer. Education has the potential to be revolutionized by AI-driven tutors, student assistants, or even teachers. AI and machine learning could even displace healthcare workers through automated diagnostic and surgical processes. The total amount of jobs displaced by AI and machine learning could certainly be enormous and no industry is safe.
Possible Benefits
According to the Centre for Cities report, though, AI and machine learning will create as many, if not more, jobs than they displace. However, there are less concrete examples of the new jobs these technological changes will facilitate. There will definitely need to be more computer scientists, programmers, and robotic experts, but definitely not in the same magnitude as the number of professionals potentially displaced by AI and machine learning.
While these technological changes may facilitate job growth in an unexpected, yet to be determined way, there will likely be an adjustment phase. Surely, new types of education and skill sets will be more valued with the implementation of automated technologies. It will take time for the workforce to react and adjust to these newly demanded skills. Furthermore, the implementation of such technologies may promote economic inequality; those who own the technology, machines, and automated processes will have a greater control over the economy and potentially over the job market.
While AI and machine learning may promote technological growth and innovation, the implementation of these technologies may have significant economic repercussions.
We should undoubtedly continue to innovate, but we should continue to be cognizant and aware of the repercussions of these new, innovative technologies.
