I have no reason to believe that a GPT model would not undergo the same criteria as any other software tool. The process is outlined in DO-330, but the essence

I have no reason to believe that a GPT model would not undergo the same criteria as any other software tool. The process is outlined in DO-330, but the essence of it is that, if a software tool is performing a function that (a) replaces a human who would otherwise be doing some particular task, and (b) either could introduce errors into a software system (for code generation), or could fail to detect them (for code verification), then the tool must be qualified. Qualifying a tool includes preparing a requirements document that describes the tool's behavior and limitations, and a set of tests that demonstrate that the tool performs as described within those limitations. (No tool is infinite, nor could any tool be tested infinitely. For an easy example, does it handle integers? What's the range of integers it handles?) Trivial in concept, but the more complex the tool, the more arduous the process of putting together materials that convince the FAA that the tool is acceptable. The DO-330 guidance for tool qualification is only about a decade old; prior to that, tool qualification guidelines were baked in to the more general avionics development guidelines document of DO-178B, which insisted that any software development tool be completely deterministic. DO-330 relaxes that somewhat, but in every case you must still demonstrate that, even if the tool output can vary, it varies within known expectations, and any variance does not change the effective meaning of the tool output. (It is my understanding that such variance is also only permitted for the least-critical category of software tools; the more safety-critical job the tool does, the less flexibility there is.) So preferably, for any given prompt, the AI tool will always produce the same output of code. In the most possible relaxed scenario, for any given prompt, the AI tool must at least always produce code that functions the same. For context, I've worked nearly 20 years in the aerospace industry, including a lot of work with tool qualification and product certification. I am not claiming that using AI tools is impossible. I am claiming that, compared to many other technological industries, there is a huge amount of red tape and bureaucracy here. Including AI/ML techniques in this work is slow-moving research effort, rather than the fast pace of many other places. Given that we are literally talking about software systems that are depended upon to keep people safe and alive, we must be more certain than usual.