I'm sorry but I do tend to feel like this muddies up the discussion on "what this technology really is". I think "artificial" is actually a pretty good term to describe the output of the models. That output does appear to resemble at least some definition of the word "intelligence" - there is some ability there to do cognition over information that's been provided to them in-context. What is it to understand, then? I…
Agreed, it's a problematic term that conflates theoretical research with better search results.
Deep learning and machine learning (ML) are both unromanticised (un-hyped) terms.
In some cases, it's just tooling with a better interface. As we have done with other complex computing systems (e.g. Deep Blue, Watson), we might just end up naming it a computing system for querying, e.g.
https://en.wikipedia.org/wiki/LCARS
We would like a neutral term for such a system, and in this sense it's better to call it "A.I." than to make a verb from google or bing or other corporate name.
But in refined cases, such tooling may offer a credible (as in "believable") human experience, like Weizenbaum's Eliza (https://en.wikipedia.org/wiki/ELIZA). Some users of Eliza fully believed that Eliza listened and understood at a profound human level. Eliza was a simple computer programme.
Computing systems are not humans. They have no accountability in real life. People may be so comfortable with the user-experience that they cannot distinguish it from interacting with another human. That doesn't make the computer system alive and accountable. And if it's run by a corporation, it will almost certainly make big promises while energetically seeking to avoid accountability. ^_^