And engineering is not a set of internal management controls. It governs the controls an organization runs for itself, and for the engineering it points outward — Those are properties built into a system through engineering. When AI carries real hazard, the law is naming what engineering has always required — engineered systems Engineer the AI you build. One is internal management.

Perhaps, walking the physical Gemba will be replaced by walking digital threads that provide transparency "Digital Threads: The Future of Compliance: https://www.leancompliance.ca/post/digital-threads-the-future-of-compliance

Engineering applies it. The engineer applies it, and answers for whether the bridge stands. Applying it to your business follows the engineering method. This engineering cannot be left to the AGI provider. It is true that they engineer, and heavily.

I am a professional engineer who studied electrical / computer engineering back in the 80’s. As it turns out, compliance is not so different from engineering at least the way it is now. Compliance added a new benchmark – a new design objective for engineering. This requires thinking in engineering terms such as: Design Thinking, Systems Engineering, Model Based Engineering, Digital Twins and Threads, Risk-based Thinking, and so on.

There are many ways in which choice architecture manifests itself in the digital environment. Further reading: Digital Nudges, Fabio Pereira, Presentation at GOTO Conference, https://gotober.com/ 2017/sessions/303 The Persuasive Power of the Digital Nudge, Julia Fetherston, https://www.bcg.com/ en-ca/publications/2017/people-organization-operations-persuasive-power-digital-nudge.aspx Digital ://link.springer.com/article/10.1007/s12599-016-0453-1 Digital Nudging: Altering User Behavior in Digital

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.

On earlier flights, engineers found that they had. In engineered systems, safety is the intended state we define and work to maintain. Whether or not they are built with general-purpose AI, they are engineered systems, and much of the current

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.