One of the most discussed aspects of AI (artificial intelligence) of late is its potential impact on the employment market. Can AI replace humans fully, particularly when it comes to white-collar, knowledge-work jobs? One Japanese insurance company intends to find out, as Quartz reports:
Fukoku Mutual will spend $1.7 million (200 million yen) to install the AI system, and $128,000 per year for maintenance, according to Japan’s The Mainichi. The company saves roughly $1.1 million per year on employee salaries by using the IBM software, meaning it hopes to see a return on the investment in less than two years.
Watson AI is expected to improve productivity by 30%, Fukoku Mutual says. The company was encouraged by its use of similar IBM technology to analyze customer’s voices during complaints.
A number of other Japanese insurers are also testing AI systems. As the Quartz report notes, insurance is one area that could be poised for serious disruption by AI. An Israeli startup called Lemonade has raised $60 million for its AI system, which it says can replace claims processors and brokers with intelligent chatbots.
Fukoku Mutual is using IBM Watson Explorer to create a "diagnostic document assessment automatic coding system," according to a press release. The system will automatically encode and classify diseases, surgeries and other data points from forms submitted by doctors and hospitals and match them up with patients' medical histories, insurance contracts, which the company expects will speed up claims processing by 30 percent.
Currently, Fukoku Mutual's payout department has 131 workers and the Watson technology will make 34 employees redundant by March, according to the Mainchi.
It's important to note a couple of things about the insurer's project. For one, humans will continue making final decisions on payouts, not the Watson AI system.
In addition, AI systems need continuous training, notes Constellation Research VP and principal analyst Alan Lepofsky. "Specialize AI, such as medical or insurance needs to understand the intricacies of the industry," he says. "It has to be trained by the humans to know what to do with the patterns and trends it finds. The point to AI is learning—continuous learning. It’s not a one-time trained and done."
Concerns over AI replacing white-collar workers may be a bit sensationalized for now, but it's true that some employees will lose their jobs. "It's naive to claim otherwise," Lepofsky says.
Meanwhile, on a broader level, Fukoku Mutual's project and others like it should provide telling examples of AI in action in a real-world, enterprise context. If 2016 was about AI exuberance, 2017 could be more about AI reality.
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