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AI takes the driver’s seat

Speed of light: A train speeds past a Tokyo station, reflective of how mobility is fast improving — and evolving — amid ‘enabling technology.’ — PHOTO BY KAP MACEDA AGUILA

New technologies are speeding up the future of mobility in ways that go beyond letting car writers use ChatGPT

By Brian M. Afuang

AS THE WAY by which people move around evolves with the transport industry’s transition to voltage-propelled forms of conveyances and to cars that can drive themselves, artificial intelligence (AI) is emerging as the dominant enabling technology speeding up these developments.

In a recent report, the McKinsey Center for Future Mobility analyzes its own research data identifying which technology trends are potentially shaping mobility. The most relevant ones range from cloud and edge computing, to industrialized machine learning, and even Web3, a new form of decentralized internet seen to offer individuals significant practical benefits. All of these, the report notes, are gaining momentum and making the transition to more inclusive and sustainable forms of transportation easier.

But more companies are focusing on the development of AI than on any of the other technologies. McKinsey asserts AI is most “poised to disrupt multiple aspects of the mobility ecosystem” because of the tech’s influence on R&D, manufacturing, marketing, and to driving itself.

For example, AI can let production-line robots do more than merely weld or paint sheetmetal, as these have been doing for decades. Using cameras and advanced radar systems, AI-controlled robots are now proving useful in ensuring quality during manufacturing. They can identify variances in fitment and consistency of finishes, alerting their human counterparts to correct these. And the role AI plays on the factory floor will only get bigger.

Other AI systems can snitch on OEM suppliers. By monitoring mainstream and social media, these gather and process information to red-flag companies that may not have conformed to certain standards — committing a recent emissions-related violation, for instance. Also, AI is able to mark out suppliers with higher environmental, social and governance risks, factors relevant to car makers’ carbon-reduction goals.

Such a capability is doubly significant in global car makers’ transition to EVs. Responsible manufacturers are taking extra steps to make sure their EVs are emissions-free not only when these are driven, but also throughout the models’ entire life cycle. This requires building a supply chain that is as eco-conscientious as the car makers are.

AI can more comprehensively “train” algorithms controlling autonomous driving cars as well. It can repeatedly simulate millions of scenarios and the appropriate responses to these — then add even more to aid in making such cars as safe and functional in the real world as these possibly can. AI allows sensors and systems to better understand the environment and condition where the car is relative to other cars, infrastructure, and pedestrians. It makes the car’s propulsion system manage energy use smartly so that hybrids and full-electrics operate more efficiently. It allows the car to interact with its passengers by understanding natural voice commands for infotainment and navigation functions, or even respond to their current state of health. As development of AI technology progresses, autonomous driving is seen to become seamless and more prevalent.

All this means AI offers vast benefits to mobility in general, going far beyond enabling motoring scribes to churn out work through ChatGPT.

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