A meta-cognitive account for the impact of implausible suggestions on estimations

A meta-cognitive account for the impact of implausible suggestions on estimations Giovanna Egidi (g.egidi@gmail.com) Center for Mind/Brain Sciences, The University of Trento Trento, Italy Uri Hasson (uri.hasson@unitn.it) Center for Mind/Brain Sciences, The University of Trento Trento, Italy Abstract knowledge of the domain (e.g., people’s longevity). They consider the boundary value of the distribution, for example, that the maximal age a person can reach is 117 years old. Because the given anchor exceeds this value, people can reject it as a viable estimate and end up adjusting their estimate to that boundary. Importantly, in this process, people do not need to rely on their knowledge of the particular target in question (Gandhi). It is only in the next step, when people are asked to provide an absolute number that they access specific knowledge of the target. At this stage they compare target- related knowledge to the domain-maximum value to which they had adjusted and test the hypothesis that the target item’s extension is similar to the domain maximum. This confirmatory testing increases the accessibility of knowledge consistent with the hypothesis (e.g., Gandhi accomplished many things in his life; is often portrayed as an old man) and this knowledge is then used to form the absolute judgment (Mussweiler & Strack, 2000, 2001). This model explains how implausible anchors of different magnitudes can produce equally high estimates (e.g., the anchors 214 and 271 yield comparable estimates for Gandhi’s age; Mussweiler & Strack, 2001). In addition, this model makes an implicit assumption regarding the role of knowledge: Because the internally generated domain- maximum value that people use as a proxy for adjustment is the upper limit of the domain, this value must be the upper bound for estimates. People should therefore not provide estimates higher than that boundary. In this paper, we consider the relative role of knowledge and confidence in mediating the effect of implausible suggestions. Building on the aforementioned framework, we develop an account that explains how the impact of extreme anchors is mediated not only by people’s knowledge, but also by their confidence in that knowledge – i.e., by their meta-cognitive assessment of their own knowledge. A central premise of our account is that people’s confidence in their knowledge of the domain in question can affect their sensitivity to extreme anchors in the context of the comparative judgment. For example, consider two people who think that the maximum age a person can live is 125 years. One person is certain of this assessment, but the other is not. It is reasonable to expect that the first person will effectively adjust to 125 (as in Mussweiler & Strack, 2001), but that the second person will still be influenced by the initial implausible anchor. Confidence in target knowledge We propose a model of why implausible numeric suggestions function as anchors and influence people’s estimates. In two experiments we tested the hypothesis that people’s confidence in their knowledge modulates their susceptibility to implausible suggestions. We found that higher confidence reduces the impact of implausible anchors. A third experiment showed that knowledge, defined as participants’ agreement on a value, weakly affects the impact of a suggestion. These results indicate that theoretical accounts for the impact of implausible suggestions on estimations should consider the role of meta-cognitive information. Keywords: confidence, knowledge; anchoring; suggestions; assimilation Introduction People often make numeric estimations in circumstances of uncertainty. It is well known that in these situations they tend to assimilate their estimates to numeric values suggested to them. This assimilation bias, called anchoring (Tversky & Kahneman, 1974), has been demonstrated in several domains (for a review, see Chapman & Johnson, These suggested values do not have to be reasonable to exert an effect on estimation. For example, people who are asked to estimate Gandhi’s age at death provide higher estimates after being asked whether Gandhi died at the age of 214 than after being asked whether he died at the age of 86 (Mussweiler & Strack, 2001). The fact that even blatantly implausible suggestions can affect estimates is counterintuitive: because people should easily identify the claim Gandhi lived to 214 as false, they should easily discard this suggestion. This suggestion should therefore have little impact on judgment. Why is it then that implausible anchors affect people’s estimates? One possibility is that the influence of these suggestions is mediated by internally generated knowledge (e.g., Mussweiler & Strack, 2001). On this explanation, anchoring occurs as a consequence of two processes: an adjustment process (Tversky & Kahneman, 1974) followed by a selective accessibility process (Mussweiler & Strack, 1999, 2001, Strack & Mussweiler, 1997). Implausible suggestions are typically given by asking people to consider a numeric value via a comparative question, e.g., Was Mahatma Gandhi younger or older than 214 years when he died? When answering this question, people draw on their