Dan Gilbert, who was featured in the post on Regret, has done much work on affective forecasting. In many respects this post based on the paper co-written with T.D. Wilson, “Why the brain talks to itself: sources of error in emotional prediction,” and published in Phil. Trans. R. Soc. B (2009), is just a more generalized explanation of affective forecasting and its shortcomings. Gilbert is a good writer, but he likes a good analogy or one liner almost too much at times. In this case, Gilbert uses an analogy of Mark Twain working on his jokes and notes that the “When the human brain talks to itself, it does not always tell the truth.”
Gilbert like Haidt and Kurzban and even Kahneman emphasizes the modularity of the brain. I believe that this is a useful idea especially Kurzban’s press secretary and Haidt’s elephant driver. However, it seems to me, modularity can overemphasize the separateness of individual modules. A turbocharger is separate from the engine, but there is feedback at least in one direction, and the two do work together. Decision making is complicated and we need to look at it under certainty, under conditions of risky choice, and under affect, and eventually with everything put together, In the post Feeling is for Doing, I look at affect as motivator and forward thinker. Gilbert is looking at how we can mispredict our emotions/affect. Obviously, this can lead us to poorer decisions. Affective forecasting can significantly influence a range of important life choices including decisions to seek diagnostic medical testing, get divorced or file for personal bankruptcy.
Gilbert explains that the brain specializes in memory because memory enables prediction, and prediction gives organisms a head start. Since memory-based prediction requires past experience, human beings have developed a different and more sophisticated technique that allows them to make predictions about future events they have never experienced before–simulation using memory. We know which future events will feel good and which will feel bad because we feel good or bad when we simulate them.
Gilbert says that premotions (our affective reaction during simulation) accurately predict emotions when the content and context of the preview are similar to the content and context of the view, and the reason why errors in emotional prediction occur is that these two criteria often go unmet. Gilbert and Wilson provide the following reasons:
(a) The problem of dissimilar content. Events do not always unfold precisely as we imagine them. One especially dull reason for this is that the future is inherently uncertain. There are others.
(i) Previews are unrepresentative. The first reason why previews provide a poor basis for prediction, then, is that they tend to be based on memories that are not representative of the future events that those previews were meant to simulate.
(ii) Previews are essentialized. If previews contained every detail of the views they were meant to simulate, then imagining a dental appointment would take precisely as long as the appointment itself. Nonetheless the elimination of incidentals may have a significant impact on our emotional reactions to it.
(iii) Previews are truncated. Just as previews tend to emphasize the defining rather than the incidental features of future events, so they tend to emphasize the event’s early occurring rather than late-occurring moments.
(iv) Previews are comparative. How would it feel to buy a lottery ticket that paid $50 if one’s friend bought a ticket that paid $80? Many of us have the compelling intuition that we would be slightly unhappy, and that we might actually be happier if we had won only $40 and our friend had won only $10.
(b) The problem of dissimilar context. Accurate predictions also require that the
context in which previewing occurs be similar to the context in which viewing occurs, and as it turns out, this is not always the case either. Why do contexts matter? When viewing immediately follows previewing—for example, when we see a doughnut, buy it and pop it into our mouths—the contexts in which these two operations were carried out are likely to be similar. But when previewing precedes viewing by a substantial interval—for example, when we see a doughnut, buy it, take it home and eat it for breakfast the next morning—the two contexts are likely to differ. When this happens, the premotions we experienced at the bakery may be unreliable indicators of the emotions we will experience when we eat the doughnut at home the next day.
The most interesting of these reasons is probably that previews are truncated. Previews take little account of adaptation. For many reasons, emotions tend to dissipate over time, which means that previews tend to emphasize precisely those moments that evoke the most intense emotion. This leads to one of the most pervasive errors of emotional prediction—the impact bias—which is the tendency for predicted emotions to be more extreme than actual emotions. Part of this is what Gilbert calls immune neglect—the tendency to overlook coping strategies and other aspects of the “psychological immune system” that can reduce future distress.
Gilbert seems to suggest that if our independent modular brain systems were more transparent to each other, we would be better able to predict our emotional states. This seems reasonable, but I keep thinking that emotions are motivators and not planners, so why should we expect good predictions from them. It seems possible that coping strategies might not kick in adequately if we did not fear extreme emotions.