In the worst case, it might not be possible to assign a reliability score that you can rely on (reliability squared) to a news source; let's consider some edge

In the worst case, it might not be possible to assign a reliability score that you can rely on (reliability squared) to a news source; let's consider some edge cases: - The news source has a biased author. Articles on related topics by that author may be untrustworthy and deviate from the score. - A particular author and their team have been worked off their feet for the past two weeks due to internal or external pressure. Their next article may not be as reliable as it should be. - The management of a news source may have changed (potentially months or years ago) and now they have decided that it is time to alter editorial policy. Subsequent articles may differ in accuracy. I think that news workers understand these concerns and take them seriously since it affects their reputations and career prospects. They probably also understand that there's a certain extent to which they can get away with small errors and mistakes. Demanding complete truth and accuracy might make the job impossible, or so time-consuming that the results become irrelevant. So there may be some element of a time-accuracy tradeoff. Perhaps fact-checkers and AI can rise above these challenges, or at least guide them, but we should be wary and allow for corrections, since much of what they do builds upon previously-seen data and consensus on what has previously been accepted as true.