As Artificial Intelligence continues to reshape global industries, there are growing concerns that we are sleepwalking into a skills gap. In the article, AI for Engineering: Why Control and Systems Thinking Matter, it is suggested that while modern practitioners are adept at deploying open-source pre-coded libraries, many lack a deep understanding of what is happening under the hood.
The Engineering Grand Challenge
The piece highlights a fundamental divide between two philosophies: the inductive, coming from Machine Learning, and the deductive, coming from the physical models of Control Theory.
While Machine Learning has proven highly effective at automating systems without needing to understand how they work, the article notes that this data-driven strength is also its Achilles' heel. For high-stakes engineering, the lack of safety guarantees remains a significant hurdle:
"While a hallucination in a chatbot is a manageable nuisance, a similar error in a smart grid or an autonomous vehicle is a physical hazard."
Control Theory, by contrast, uses physical laws to design controllers with guarantees that the system will behave acceptably. However, because these methods can be slow to iterate and deploy and require a demanding mathematical toolkit, they are often overlooked in favour of faster, data-only approaches.
Advocating for the ‘Bilingual’ Engineer
The article identifies an engineering grand challenge: fusing these two fields to enjoy the advantages of both. To address this, the piece advocates for university programmes that merge both disciplines to provide a comprehensive and well-rounded skillset.
At the Centre for Machine Intelligence, we value this integrated approach to AI education. By championing a curriculum where students become bilingual in both disciplines, the University of Sheffield is preparing graduates for a market where demand for a skillset in AI for Engineering is set to skyrocket.
The future, the piece concludes, belongs to engineers who are bilingual in both disciplines.
Read the full article: AI for Engineering: Why Control and Systems Thinking Matter – The Statesman