Ever since HAL refused to open the pod bay door in “2001: A Space Odyssey,” we’ve been both fascinated by and a bit frightened of the potential for artificial intelligence. The idea that we can create something that’s “smarter” than we are both challenges our intellectual curiosity and bruises our fragile human egos.
But here we are at the genesis of AI, and we’re just learning to appreciate improved computational speed and rapid evaluation of design scenarios. It is changing the timeframe in which we can make better design decisions. The real value of AI is in the speed we gain in reaching those design choices.
That concept is at crux of Wojciech Matusik's article now on MachineDesign.com. Matusik is uniquely qualified to look at this issue: He’s an MIT professor of electrical engineering and computer science, two disciplines at the intersection of AI. “Although AI and [machine learning] do not eliminate the need for experimentation, they can help researchers efficiently plan and even conduct experiments,” Matusik writes in this month’s issue. “In the near future, we will see completely automated workflows in which designers set parameters for desired outcomes, and then robots conduct experiments and assess the results.”
Will those be the right results, or just the “smartest” results? This is a place where design and operation teams will rightfully retain control over the final process decisions. It is possible to optimize both performance and profitability and still not have the optimal system. As the world desires a more personalized choice of products and as business strives to deliver on that desire, there are aspects that still require the human touch. For as much as we have been buoyed by the door-to-door deliveries of almost everything we needed during the pandemic, there continues to be logistical and human barriers we cannot yet scale.
We continue to need more people in new roles doing new jobs to support this new approach, and we still are reckoning with the sheer economics of that change. There is nothing artificial in how we regrow our operations in a post-COVID age. The most recent data from the Institute for Supply Management shows that while manufacturing is surging, the two drags on that surge is difficulty hiring workers and supply chain disruption.
Artificial intelligence may point the way to the best idea, but only after humans have created the first idea. And there are still a few things we have yet to automate—and probably never should. Intelligence may be artificial; the search for more of it is very real.