In general, a primary factor reviewers in computing conferences are asked to consider is the degree to which a submission make a "substantial contribution" to the community. What is or isn't a substantial contribution is subjective and entirely dependent on the prevailing ethical perspectives in various communities. Papers -- a key unit of academic progress (for better or worse) are entirely subject to concerns of ethics. Certainly, there are interesting argument around how much time and paper space should be spent on speculating about negative impacts, and people are having those conversations.
The fact that ethics is "trending" is because more researchers would like tackle ethical challenges explicitly, instead of falling back on the default of a given community. For instance, here is a paper that quantitatively (with reproducibility!) analyzes the values in ML papers. https://arxiv.org/abs/2106.15590 This is one way to have a very empirically-grounded discussion of the topic.
IMO, many researchers can and do debate topics of ethics in AI, and in doing so move the field forward (and increase likelihood that computing will have more positive impacts than negative ones).