Ford has rehired more than 300 experienced quality inspectors after discovering that its artificial intelligence (AI) systems could not match the skills, judgement, and experience of veteran human workers.
According to a recent Bloomberg report, the American automobile manufacturer had introduced AI technology across several of its manufacturing plants, including about 900 AI-powered cameras designed to detect production defects and identify supply chain disruptions.
However, Ford later realised that relying heavily on AI alone was not enough to maintain the level of quality the company expected.
Speaking to reporters, Ford's Vice President of Vehicle Hardware Engineering, Charles Poon, admitted that the company had underestimated the importance of its most experienced engineers when deploying the new technology.
Poon described artificial intelligence as a powerful tool but stressed that its performance depends entirely on the quality of the data and knowledge used to train it. He acknowledged that Ford had not given enough attention to the expertise of long-serving engineers who had worked through many vehicle development cycles.
He explained that while AI can quickly identify patterns and detect potential problems, it still lacks the practical judgement and decision-making abilities that experienced technicians develop over decades of working in the industry.
As a result, Ford has brought back more than 300 veteran inspectors, many of whom had previously left the company. Their new responsibility is to help improve the company's AI systems by training them with real-world manufacturing knowledge while also mentoring younger engineers and passing on their experience.
Poon said Ford recognised that to improve its automation, machine learning, and artificial intelligence tools, the systems needed to be trained by the company's most knowledgeable and experienced professionals.
The move highlights the growing belief among many companies that while artificial intelligence can improve efficiency and productivity, human expertise remains essential in areas that require experience, critical thinking, and sound judgement.
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