I came across “Not Even Wrong 2: An Audit of Public AGI Prediction, 1950–2026” by Luciano Floridi, Jessica Morley, and Claudio Novelli through a Medium post (I put the link at the end of my explanation). The audit has two stages: before determining whether a prediction came true, it first checks whether the outcome could have gone either way. The criteria are whether the claim refers to a specific observable state, whether there is a concrete test to show it, whether there is a real and fixed deadline, and whether someone other than the predictor could judge whether it has resolved. If any one of these conditions is missing, then the prediction is ‘not even wrong’ since it was not stated in a way that allows for verification. Accuracy is checked only in those who pass all four. 19 out of the 24 fail at the first stage. Two of them are falsifiable and entirely incorrect. Three remain unresolved. Overall, prediction quality has not noticeably improved over the seventy-five years. The latest predictions are mainly provided by the CEOs of firms which benefit from the forecast, and these entries obtain the lowest marks for falsifiability . No improvement in predictions over seventy-five years… Read the post here: https://medium.com/philosophytoday/the-agi-predictions-fail-the-falsifiability-test-f5a2b22dffc1?sk=6f3e1b8eaf315ad8644f42d67a785e97 submitted by /u/Smart_Fly_5783
Originally posted by u/Smart_Fly_5783 on r/ArtificialInteligence