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Experts from Yale and Oxford University recently released their research on how AI will transform modern life by reshaping transportation, finance, health, science, and the military. Key findings pointed toward a 50 percent chance that AI will outperform humans in every job in 45 years’ time.
How can we anticipate and manage trends in AI, and will creative and analytical skills really be the key to job success in an AI world?
Recounting a personal scenario, my boys had a “future day” at school. One dressed up as a chief robot maker and the other as a soccer player — which left me wondering, which career would be right in a world of artificial intelligence?
When the internet came of age, I would tell anyone who asked, “Don’t do a job that can be put down a wire” — meaning, don’t train to do a job that someone on the other side of the world can do for half the price. But with AI, it’s no longer that simple, according to the survey.
This shift is worrying for two reasons: It’s going to happen relatively quickly, and most schools are ill equipped to handle it. But before exploring the future of work, let’s dispel some myths and look at what won’t happen.
Over- and underestimating the effects of AI
During a recent panel discussion at the Financial Conduct Authority, time and resistance were both flagged as key challenges to the effective deployment and adoption of AI technologies.
Resistance — or “AI friction” — is a particular challenge within the older demographic, where people may play with the tech but find ways not to use it because deep down they prefer human interaction.
Driverless cars and deliveries are another example of AI friction. That’s a job threat for three million people in the U.S. alone, as indicated in a report published in December 2016 by the White House that looked at the ways AI will transform the U.S. economy. The industry has scrutinized this and broken down the evolution of autonomous cars into phases. The initial phase is what we see now on the roads, which is essentially an advanced cruise control, and the final phase is a completely autonomous car.
The friction in this case occurs around phase three or four, where a human and a computer both drive the car. In this phase, when the computer does not know what to do, it hands control over to the human. On the surface this sounds logical; however, when simulated, it is revealed to be intensely dangerous. Imagine being in a driverless car and you have “switched off” from the task of driving — then a car pulls out and the AI hands over control. Few drivers will snap to attention quickly enough to avoid a collision.
The progression and extensive testing of these vehicles presents a problem that cannot be easily fixed, meaning there’ll be a gap between the smart cruise control phase and the introduction of a truly autonomous vehicle.
The AI friction in this scenario also relates to the three million people in the supply chain who could be replaced by AI. To understand if this impact is realistic, we need to consider the logistics. Most logistics models start with the inbound goods arriving on a train or ship. This is called a multi-modal shipment because it’s full of standardized containers that can be lifted directly from the ship onto the back of a truck, thereby changing the mode of shipment. Autonomous vehicles are not really going to affect this first leg.
The shipment is then typically long-hauled from the port to a warehouse or distribution center. These…
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