 Levi (1967) measures the information content \(I(g)\) of a partial answer \(g\) in \(D(B)\) by the number of complete answers it excludes. With a suitable normalization, \(I(g) = 1\) if and only if \(g\) is one of the complete answers \(h_{j}\) in \(B\), and \(I(g) = 0\) for a tautology. If we now choose \(u(g, h_{j}) = I(g)\), then \(U(g\mid e) = I(g)\), so that all the complete answers in B have the same maximal expected utility 1. This measure favors strong hypotheses, but it is unable to discriminate between the strongest ones. For example, the step from a false complete answer to the true one does not count as progress. Therefore, information cannot be the only relevant epistemic utility.