United States automaker, Ford Motor Company has reversed to human employees by hiring more than 300 veteran quality inspectors. The decision came after the auto giant’s artificial intelligence systems failed to match the skills and experience of human engineers.
The company, which had massively deployed AI-powered cameras and automated systems across its plants to detect quality issues, acknowledged that automated tools lacked the training and expertise of seasoned technicians. Executives of the firm revealed that Ford had reintroduced the experienced workers to train its AI systems and mentor younger employees.
The latest move marked a significant setback for the automaker’s AI-driven quality assurance strategy, after it had embraced AI across its operations in a bid to cut costs and boost productivity, discovered that automated tools were no substitute for the hard-earned wisdom of decades of design experience.
According to the chief operating officer, Kumar Galhotra, in a bid to reap the benefits of AI technology, Ford deployed 900 AI-powered cameras in its plants “to detect quality issues at the source and help us mitigate supply disruptions.”
The company also adopted automated systems for quality checks across its operations. However, executives admitted that the AI-driven checks had failed to live up to expectations.
The company also adopted automated systems for quality checks across its operations. “Mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a highquality product,” Charles, vice president of vehicle hardware engineering, told BBC.
Charles pointed to automated tools lacking the training and expertise of veteran technicians, many of whom he said had left the company before their knowledge could be used to improve its tech. “Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it,” he said.
Bloomberg reported that the company’s response was to bring back the experienced workers who had left. “We recognised that for us to enhance some of our automation and machine learning and artificial intelligence tools we needed to ensure that they were trained by the most experienced individuals,” Charles said, according to Bloomberg. The veteran engineers were reintroduced to train the company’s systems, as well as mentor younger workers.
