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By Raimund Laqua, Lean Compliance Engineer Mistakes aren't failures—they’re lessons. Because when compliance engineers make mistakes, people die. The connection is engineered to work every time. Now apply this to compliance. Engineering Reliable Delivery Build obligation fulfillment into the process.   Engineer commitment keeping.  Your car won't start without a seatbelt.

all the talk about artificial intelligence it’s easy to get caught up in a world of machine models, digital

Multiplicity: Designing What This Is and What This Is Not With the essentials established, the engineer The Rub Here is where engineering demands expertise. The engineer's expertise lives in this tension: defining identity tightly enough that the thing remains This is the bridge between engineering and compliance. First Principles Engineering is about building things.

The following diagram is a slightly modified version of her model outlining engineering activities across At this level of analysis we are talking about AI Systems (i.e. engineered systems) not about systems A key takeaway is that AI engineering must incorporate and ensure responsible and safe design & practice This is where professional AI engineers are most helpful and needed.

From an engineering perspective, I propose three principles that organizations should consider when designing The engineering discipline here is straightforward but often overlooked: Map your existing safety controls This integrated view reflects how safety is actually achieved in mature engineering disciplines. Aircraft aren't safe just because engines are reliable. This is the work of engineering: not making perfect systems, but making systems that fail safely, that

System controls — engineered into the work, instrumented, outcome-bearing. Engineered into how work is done. 🧡 C2 / C1 — Process and functional safety.

Unlike traditional engineered systems with predictable inputs and outputs, AI systems exhibit emergent Ray Laqua, P.Eng., PMP, is Chair of the AI Committee for Engineers for the Profession (E4P), Co-founder

responsible for the “responsible” use of AI, and when does the science experiment stop, and responsible engineering A step we can take is to reinsert the engineering method into the development of AI. This will require more engineers, along with other professionals, in the loop, advocating for and practising Instead of deploying science experiments to the public at scale we need to build responsible engineered

As an engineer, I have always had to comply with rules (i.e. requirements) of all kinds such as: laws Professional engineers in Canada (and other parts of the world) are also constrained by law to protect All of these are a form of constraint, and to an engineer these are seen as challenges and not problems The essence of engineering lies in designing solutions that work within given constraints while planning Compliance with regulations in many ways is no different than an engineer designing a system to meet

Companies need to build AI literacy across all departments, from engineering to legal, HR, and marketing Engineers need technical understanding, while legal teams require compliance and risk perspectives. Many professionals are moving into AI governance roles, but fewer are pursuing AI engineering due to This could create imbalances, with potentially too many governance specialists and too few engineers Bringing Teams Together One clear message from the conference: AI governance and engineering must work

created by Engineers Canada in 2016. in sustainable engineering efforts. Sustainable engineering defines an approach to engineering to meet the challenges of sustainable development In many ways, in Canada, we have not done as much engineering as we used to. outlines 10 guidelines for engineers: Engineers: Should maintain and continuously improve awareness

governance policy means creating an operational, regulation framework that links  legal ,  ethical ,  engineering system behavior visible Compliance streams : Flows of promises from legal/ethical commitments through engineering Roles & Accountability Assign decision rights: executive sponsor, AI/Model Compliance lead, Engineering