Ford Had to Rehire Veteran Engineers After Its AI Flopped. Other Employers Should Take Notice

Source Domain: www.cnet.com

At a conference last year, Ford CEO Jim Farley said that artificial intelligence is “going to replace literally half of all white-collar workers in the US.” Just last week, Ford executives said that the automaker had quietly rehired more than 350 of what it internally calls “gray beard” engineers over the past three years to help fix the AI quality-control systems that weren’t getting the job done.

Over the last decade, US automakers have cut more than 20,000 jobs, nearly a 20% reduction in workforce between Ford, General Motors and Stellantis combined. While Ford hasn’t said for sure how many of these gray beard rehires were originally fired to make way for AI and how many are simply returning retirees, Farley’s recent statements on automation-fueled worker replacement certainly paint an awkward picture.

Representatives for Ford and the United Auto Workers union did not immediately respond to requests for comment.

Not getting the desired results

“Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it,” Charles Poon, Ford’s vice-president of vehicle hardware engineering, told reporters last week. “Mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a high-quality product.”

Kumar Galhotra, Ford chief operating officer, was even more blunt about the realities of AI in manufacturing, saying that Ford had been “relying more and more on automated quality systems and not getting the desired results.”

More than a simple oopsie, automation issues have been costing Ford billions in warranty costs and recalls. A study from iSeeCars, an automotive marketplace and research company, ranked recent Ford models among the most recalled vehicles in the industry. Ford’s statements and the rehiring of experienced workers are essentially an admission that moving too quickly into AI was a big mistake.

Many major corporations in almost every aspect of…

Source