With Trust in AI, Manufacturers Can Build Better

Some people might not associate the word “trust” with artificial intelligence (AI). Stefan Jockusch is not one of them. Vice president of strategy at Siemens Digital Industries Software, Jockusch says trusting an algorithm powering an AI application is a matter of statistics. This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not produced by MIT Technology Review’s editorial staff. “If it works right, and if you have enough compute power, then the AI application will give you the right answer in an overwhelming percentage of cases,” says Jockusch, whose business is building “digital twin” software of physical products. He gives the example of Apple’s iPhones and its facial recognition software—technology that has been tested “millions and millions of times” and produced just a few failures. “That’s where the trust comes from,” says Jockusch. In this episode of Business Lab, Jockusch discusses how AI can be used in manufacturing to build better products: by doing the tedious work engineers have traditionally done themselves. AI can help engineers manage multiple design variations for semiconductors, for example, or sift through routine bug reports that software developers would have had to manually review to figure out what is causing a glitch. “AI is playing a bigger role to allow engineers to focus more on the real, creative part of their job and less on detail work,” says Jockusch. Also in the episode, Jockush explains how AI embedded in products themselves have already won over millions of people—think voice assistants like Siri and Alexa—and will someday become such a common component that people will barely talk about the value or the future of AI. “I mean, how many discussions do you have nowadays about the value of Excel, of cellular calculation, although we use it every day?” says Jockusch. “Everybody uses it every day in something, and it’s so universal that we hardly ever think about it.”