Our View: AI inching its way into tire technology, but future remains unclear

Mention the term "artificial intelligence," and there's a good chance you'll start a debate.

Will AI become the technology to make all other technologies obsolete? Or will it be a "buzz word" of today that's shoved to the background in the coming years?

At NAHAD's recent annual convention, attendees got to hear from one of the world's top proponents of AI, Zack Kass, who worked as head of Go-to-Market for OpenAI. He was a key player in channeling the firm's innovative research into tangible business solutions.

And in his keynote speech, he said he believes at some point that AI will be intellectually equal to humans.

"I think it will be the last technology humans will have to invent," Kass said. "It will be more important than fire, the wheel and the internet combined."

The OpenAI alum predicts that AI will accomplish unimaginable things, including curing cancer and bringing the costs of goods and services to new lows.

With the pressures facing a technology-driven industry like tire manufacturing, it's no surprise that the use of AI is beginning to enter the conversation.

For tire production equipment manufacturer VMI Group, automation—and by extension, AI—is one of the pillars driving the tire making of the future, especially as it relates to the more complex, heavier tires required for EVs.

VMI CEO Harm Voortman said recently that introducing flexibility into tire-making systems can be extremely valuable.

"What you want are systems that are automated—and can handle all kinds of different things in an automatic way," he said. "What we think is the way forward is to make use of very smart solutions and software that can help."

For example, VMI uses AI in foreign object detection and in retreading operations, often the most complex, highly engineered portion of a tire.

Giti's upgrades in South Carolina also include co-location and integration of AI.

The machine-learning technology builds on itself, allowing for greater consistency in processing and fewer mistakes by fallible, human operators.

In addition, Rockwell Automation experts note that a newer, less permanent and more selective work force dominates in North America, making legacy knowledge in a legacy industry much more difficult to pass down.

And therein lies the need for autonomy and automation in production, according to Rockwell.

But just how far AI will go in tire and other industries may depend as much on public opinion and perception rather than how well AI performs.

With the future unfolding much faster than most realize, Kass said there are a number of monumental decisions that must be made. One will be deciding the difference between the "Technological Threshold"—or what can the machine do—and the "Societal Threshold"—or what do we want that machine to be able to do.

He said developers "can science their way out" of such things as computing and energy deficits. But bad policy and politics could be what holds back AI in the future.