The title of Eugene O’Neill’s 1939 noir epic on man’s need for self-deception could be the chyron for a recent article in the Proceedings of the National Academy of Sciences (PNAS) entitled “Ice Sheet Contributions to Future Sea Level Rise from Structured Expert Judgement” by J.L. Bamber, M. Oppenheimer, R.E. Kopp, W.P. Aspinall, and R.M. Cooke. The PNAS paper describes a structured expert judgment (SEJ) uncertainty quantification of ice sheets’ contribution to sea level rise (SLR) out to 2300 under +2°C and +5°C stabilization scenarios. Expanding on the methodology of Bamber and Aspinall’s groundbreaking 2013 study, the PNAS study again treats individual experts as testable statistical hypotheses, but this time, it targets upper-tail dependence between ice sheet processes. The result is higher median assessments and expanding uncertainties, especially in the upper tail, relative to the Fifth Assessment Report of the United Nations Intergovernmental Panel on Climate Change (IPCC AR5). Its potential for capturing a more nuanced and accurate picture of uncertainty, is precisely why Riskthinking.ai employs SEJ in the development of its scenarios tools.