There are three kinds of decision making environments with less than perfect information about the outcome of a decision that vary in the extent to which the information available to decision makers is imperfect. A decision making setting is defined as risky when both the possible outcomes, and the probability of those outcomes, are known before a decision is made. A decision making setting is defined as ambiguous when the possible outcomes of a decision are known before the decision is made, but the probabilities of those different outcomes occurring are not known, when a decision is being made (for survey see Camerer amp; Weber, 1992). Finally, a decision making setting is defined as uncertain (or sample space ignorance, i.e. Michael Smithson et al, 1999) when neither the possible outcomes, nor the probabilities of those outcomes, are known when a decision is being made.Results of Fox and Tversky (1995) suggest that expert bias can influence individual perception of ambiguous environments. If people feel that they have more expertise about the environment they are more confident about their estimate of the probabilities. One possible implication of this finding is that experts might perceive ambiguous environments as risky more often.This study demonstrates that expert bias influences individuals' perception under sample space ignorance as well, but not the same way as in ambiguous environments, i.e. in such environments experts are less confident then non experts in their estimates of possible outcomes, and experts are more likely then non experts to expect that something completely unexpected might happen
