 Lara Buchak (2013) proposes what is arguably a more elegant version of this solution. Her suggestion is that we should assign exponentially less weight to small probabilities as we calculate an option’s value. A possible weighting function r discussed by Buchak is \(r(p) = p^2.\) Her proposal is, thus, that if the probability is \(\frac{1}{8}\) that you win $8 in addition to what you already have, and your utility of money increases linearly, then instead of multiplying your gain in utility by \(\frac{1}{8},\) you should multiply it by \((\frac{1}{8})^2 =\frac{1}{64}.\) Moreover, if the probability is \(\frac{1}{16}\) that you win $16 in addition to what you already have, you should multiply your gain by \(\frac{1}{256},\) and so on. This means that small probabilities contribute very little to the risk-weighted expected utility.