When I think about this question in the context of research papers, for instance, I can't see a real issue.
Ideally, when posting research papers links, the title of the paper will be used in addition to the link, so if the link goes bad, people can still search for the paper.
Russel & Norvig's Artificial Intelligence: A Modern Approach is heavily cited on SE:AI, and the text was originally published in 1995. The book is in its 3rd edition now, (which is not always noted when cited,) but even the 3rd edition dates from 2009, earlier than the recent Machine Learning milestones (~2016) yet the textbook is still relevant and heavily utilized.
List questions do have some issues (see Neil Slater's answer) and seem to be off-topic in general across Stack exchange.
However, I'd still think lists of research papers on a given topic, ideally peer-reviewed, would provide utility and carry archival value. In the same way, lists of well-regarded textbooks could be useful.
Second Consideration: Contemporary Hacker Culture and Youtube
In some sense we're the "General AI" site, covering the full scope of the field, as opposed to focusing on any given specific aspect (distinct from stacks like Data Science.)
We seem to be the stack where beginners typically come to first. I created a getting-started tag because there are so many of these questions.
Many people today are learning the basics today via youtube videos. Where the videos are solid, they seem to provide benefit, but they tend to be more ephemeral, especially when they come from non-academic sources. (Erik Demaine's lectures on Time Complexity will likely be available for a very long time indeed, where a random youtuber using click-baitey titles subject matter to generate ad-revenues may not be.)
My feeling is, re: videos, is that anything commercial should be avoided, but anything coming from accredited academic institutions is reliable and suitable.