Works in ChatGPT, Claude, or Any AI
Add semantic quote search to your AI assistant via MCP. One command setup.
" "Two biases of memory, however, tend to enhance the illusory nature of our retrospective “understanding” of our own and others’ lives. The first is that we tend to overestimate specific events relative to general categories of events. The second is that we tend to recall specific events and to interpret them in ways that make sense out of a current situation—“sense” in terms of our cultural and individual beliefs about stability and change in the life course. Thus, memories, which appear to be beyond our control as if we are observing our previous life on a video screen, are like anecdotes in that they are often (inadvertently) “chosen for a purpose.” The result is that they will tend to reinforce whatever prior beliefs we have, just as anecdotes tend to reinforce the points they are meant to illustrate.
Robyn Mason Dawes (July 23, 1936 – December 14, 2010) was an American psychologist who specialized in the field of human judgment.
Works in ChatGPT, Claude, or Any AI
Add semantic quote search to your AI assistant via MCP. One command setup.
Related quotes. More quotes will automatically load as you scroll down, or you can use the load more buttons.
The realpolitik view of the individual human—that we are slaves to our desires and attitudes and that knowledge and rationality are necessarily secondary to these other factors—is simply wrong. We have the competence to be knowledgeable and rational, especially when we interact freely with each other. We can indeed change our minds. We can “bend over backward to be defense attorneys against our own pet ideas.” We can reconsider. We can be rational.
As discussed in Chapter 7, we often substitute a good (internally generated) narrative or story for a comparative (“outside”) analysis when we attempt to understand something unusual. We also often substitute pure association for comparison. This reliance on coherent “explanations” provides what is really an illusion of understanding, rather than understanding.
In this chapter, I present the other side of the coin. That is, even when we have a perfectly valid statistical explanation for a phenomenon, we may ignore it because no “good story” accompanies it to persuade us that we should believe it.