AI's curse is that once it becomes mundane people call it "automation".
I think that having a focused degree in AI makes sense. I think that AI has reached the level of maturity that a separate curriculum should be made for it.
Just as we had no distinction between computer scientists and software engineers we now face a world where AI and or Data Science require a different focus on education.
My only thought on that idea is that it feels like an undergrad in AI is less useful in the sense that most AI positions prefer PHD over masters, let alone undergrad.
On the other hand, I've got a friend with a film degree pulling in decent money in Houston as a solo consultant (hiring contractors as needed (like me)), going from oldschool oil EPC to oldschool healthcare data analysis firms pitching "Big Data analysis" and "AI trained data modeling."
Mostly it's plugging .CSVs into google's cloud platform tools, but sometimes I get to peek at some homebrew R or python modeling stuff.
He (nor any of us that he pulls in for big projects) will never do research for MIT or OpenAI, but money is already being made in "AI." If his business ever explodes into a full blown company, these undergrads are exactly the kind of people he'd hire.
Training an analysis model and then using it for further analysis is automation? Well then so is telling a programmer "find ways to add value to this company." Boom. Automation.
Mate no offense but I find semantics arguments super boring. The kind of work my friend does is exactly the sort of stuff they teach in AI courses. You wanna call it "bananabananafruitypoopoo" that's fine by me, "automation," sure, whatever.
I probably wouldn't call it automation, but you could regroup all these under the term machine learning or data science and IMHO it would be valid. I think OP refers to AI as the autonomous agent type of AI. Conversation, understanding the world, moving & acting, planning & decision making, multi-agent collaboration, this type of stuff. Some of these might fall under machine learning, but I would say most are outside of the scope of machine learning -- and do not seem to be targeted by the so-called AI degrees. However, I think it's fine to call those degrees AI, because they are AI -- machine learning is AI.
The question is should we name this after the smallest denominator (machine learning) or the biggest one (AI). Also, in the short term future, more and more real AI (i.e., not machine learning) will probably be integrated in those classes, so why not skip one painful rebranding step.
To me "AI" means it learns by itself. Including the decision what to learn, and how. Having done quite a bit of statistics courses over the last few years (albeit with a focus on medicine/biology) and some of free the basic machine learning courses, AFAICS that is not the case, what and how something is learned is all decided and done by the human(s) in front of the computer, no? So, I don't see much "intelligence" - in the machine. Lots of it in those humans, of course.
But with the application of those diciplines you can build machines that "learn." The "by themselves" bit is agi which is a specific subset of ai and would be more on the research side of things, not a bs.
I think the real issue appears that the media has confused people as to what "ai" practically means from a compsci perspective.
Your definition doesn't match the real definition. Technically, a hard coded rule-based decision algorithm is a form of very basic AI. You seem to be confusing ML and AI- ML is a subset of AI that focuses on training a complex model.
No I'm not confused, as I said, I took the courses. I know what is. I'm just saying that I don't see this as "AI" at all and why. I don't really care that someone decided to define what is possible now as "AI" for whatever reason because I don't agree and don't see that as reasonable. It's not like those "definitions" are laws either, ask around, even among professionals, and you get as many different definitions as you want. Therefore I prefer to use a "common sense expectation/interpretation" approach, and "common sense" here to me means coming from above (where we want to go), not from below (what we have thus far achieved).
I dunno what it should be called (including the possibility that "AI" is exactly right).
I do know that I focused on AI in my electives for UMich's CS degree circa 1990, and from the sounds of it the AI I studied will have literally nothing in common with what is described as AI for CMU's new degree.
I dont call this AI, I call this automation.
I know AI is a buzzword, but unless something is trying to think, its not AI to me.
What they are talking about seems to be automation through lots of code.
But hey, I havent been keeping up with this field, not sure what people are calling this.