The day that artificial intelligence takes your job may be further off than most people think.
Speaking at the Coins2Day Brainstorm AI London conference on Monday, Marc Warner, the chief executive of AI consultancy Faculty dismissed fears that adopting the technology at scale would automatically lead to a mass culling of employees.
“That will be much further away than those people anticipate,” Warner told conference participants, adding it was often all too easy amid the ongoing hype to overestimate AI’s true capabilities.
“Look at when we were promised fully autonomous cars—it’s taken a bit longer than we expected,” Warner continued.
Ever since ChatGPT launched in November 2022, experts have predicted generative AI, and AI more broadly, would eventually revolutionize every facet of our daily lives just as the internet did a generation ago. Economists at Goldman Sachs even predicted last April that no less than 300 million full-time–equivalent jobs were at risk of redundancy as a result.
Warner believes such predictions will prove as unrealistic as robo-taxis.
Executives in both the tech and auto industries have repeatedly argued this technology was just around the corner. For example, Elon Musk falsely forecast five years ago to the month that Tesla would have 1 million cars on the road by 2020—each earning the equivalent of $30,000 in annual fares for their lucky owners. Instead, it has taken considerably longer to ensure the technology’s safe deployment. Just a few weeks before ChatGPT arrived, Bloomberg had already concluded that “self-driving cars are going nowhere.”
“Nowhere” is perhaps too skeptical, but progress has indeed been painfully slow. The few AI-driven cars in operation are largely confined to a handful of select cities that boast the most favorable overall road conditions, such as San Francisco and Phoenix, and even then they have not been without the occasional scandal.
AI should be designed to support people, not supplant them
The idea that AI would swiftly automate people’s jobs out of existence in the process would likewise prove premature, Warner believes.
“Clearly, it’s both true and good that it would be further away,” he said.
A former Harvard University fellow in physics, Warner cofounded Faculty in 2014 to help organizations using AI better reap the technology’s benefits while managing its potential risks.
He believes AI should first and foremost be developed and built around humans to serve as a tool that supports them rather than supplants them.
Not only could that approach ultimately be more effective, as opposed to scaring people with predictions of layoffs in the hundreds of millions, it could go a long way in gaining social acceptance for AI as well.