Newark survey shows most engineering designers trust AI to help pick components

Eighty-six percent of respondents trust artificial intelligence (AI) to play at least some role in their component selection for designs, and more than a fifth (22%) said they’d “completely” trust AI to select components, according to survey results reported Aug. 31 by Newark.

More specifically, 49% of the 528 total respondents said they’d accept specific input from AI on choosing components for their designs, while 16% would accept very limited input in selections that remain subject to their reviews and checks, and 11% would not accept any input from AI on components for designs.

Overall, the results indicated, while engineers believe AI will have an increasing role in assisting with component selection in the future, there’s lingering concern about intentional or unintentional bias in AI systems. Though most respondents welcomed complementary AI, they also felt that human beings will always be required as part of the selection process, especially for safety-critical systems and innovative designs.

"AI is no substitute for good engineering calculations,” stated one retired engineer in a text opinion. “I’ve been following AI for more than 40 years and it’s more overhyped now than ever. I’m more willing to tolerate human error than rely on an AI solution where I can’t control the data used to train the AI model." Newark adds this sentiment reflects a concern that engineers won’t be able to fully understand why an AI module selects particular products.

A second respondent highlighted a common view that AI could be more useful as an assistant rather than a replacement. He said, "That comes with the caveat that I'd reserve the right to vet everything the AI selected. In this capacity, AI would be used as an enhanced search engine of sorts."

A respondent keen to use AI added, "I don't see why AI couldn’t be fully integrated into the component selection process. Hardware design is fundamentally composed of patterns. It's just a matter of time until people discover ways to get online netlists and schematic PDFs and use them as good AI training data. In fact, AI will even be able to improve on them once there are better digital representations of devices and what's inside them, coupled with telemetry from all of the subsystems. AI has a deep and rich well of sources to draw from that will enable it to learn even more. There are already completely generic AI systems that can do impressive, if limited selection, even building up simple VHDL for example. It's specifying what logic to use and how to assemble it. AI is already writing code for me. All I need to do is vet it."

Meanwhile, another regular user of AI for selecting components nevertheless voiced misgivings about AI’s ability, stating that AI modules still have a lot to learn about reliably and how to consistently make the best and most appropriate choices.

“Our survey results clearly show that engineers are beginning to see a path for AI’s place in terms of component selection in their designs, especially where safety or innovation are considerations,” says Cliff Ortmeyer, global head of technical marketing and solutions development at Newark. “As AI models get more sophisticated, it seems clear they’ll become more useful for modelling designs, selecting components, shortening design cycles and reducing time to market of new products.”