I come from a research background, and transitioned to software later. There is an interesting tendency of software engineers to believe they have skills outside of their skillset.
Relevant here: the would we trust a Software engineer, which in general don’t always obtain the mathematical foundation to understand deep learning in the first place, on the trajectory of AI?
Part of my software engineering skillset is "going native" with subject matter experts to be able to get more out out of them and even work around the lack of sufficient SME on a project.
I see software development as part of a broader science, technology and even ideology of simulation. But I came from a research background too.
Sounds like a similar track, and I agree that its a useful skill and talent.
What I mainly noticed was, after really understanding my domain, the confidence of the SWEs I was working with despite being incorrect. Now I am a SWE and I try to stay humble.
This is correct behavior. There must be a name for this effect of having some more or less shallow understanding and feeling like an actual expert with decades of experience from various sides of the topic.
SWEs I think are more susceptible to this since as you say we often dip in many areas and industries. No, we are not actual SMEs and proper experts (barring exceptions of course, but in any case we usually have a specific view on domain, while proper experts understand many/all views).
> would we trust a Software engineer, which in general don’t always obtain the mathematical foundation to understand deep learning in the first place, on the trajectory of AI?
Valid point, but it suggests a mathematician who understands the math behind AI is more capable of grasping its trajectory, which is probably not the case.
People who are deep in the inner workings of this stuff day in and day out are the only ones who have a chance at having any real insight.
I think more broadly that grabbing attention with predictions and hot takes has become lucrative, and we definitely don’t celebrate prediction accuracy.
Relevant here: the would we trust a Software engineer, which in general don’t always obtain the mathematical foundation to understand deep learning in the first place, on the trajectory of AI?