Some cognitive fallacies and biases

Anchoring: The tendency for first impressions, even irrelevant ones, to continue to influence decision-making. A startling example: students were asked to estimate the number of nations in Africa. Before they estimated it, a wheel with the numbers 1-100 on it was spun to generate a random number. Those for whom the wheel came up 12 consistently estimated lower than those for whom the wheelcame up 92, even though there is obviously no relation between the random number from the wheel and the actual number of African nations.

Availability Bias: Our tendency to base evaluations of probability on the ease with which examples are recalled. However, availability is generally a result of features like salience (noteworthiness) or repetition. Shark attacks and airplane crashes areeasy to recall because of their emotional salience; as a result we tend to greatly overestimate their frequency. A special case of this is the so-called “flashbulb memory”, a memory concerning where we were or what we were doing when some especially noteworthy or emotionally charged event happened. Experimental studies reveal that these flashbulb memories, in which we are supremely confident, arein fact no more likely to be true than other memories.

Base Rate Neglect: When making judgments about probabilities, we often ignore base rates in favor of good stories. Base rate data tells us how representative one feature is of a whole population, or how likely an event is to occur independently of specific conditions. For example, from the fact that most men that have committed sexualassault have used pornography, we often conclude that pornography causes sexual assault. The missing base rate data is what percentage of men, independently of whether they have committed sexual assault, has used pornography. This fallacy is especially prevalent when stereotypes are involved. We will tend to judge it to be far more likely for a woman to be a lawyer than a waitress if we know thatshe reads a lot and majored in philosophy. The problem is that any woman is more likely to be a waitress than a lawyer—our decision is the result of the fact that reading a lot and majoring in philosophy fit our stereotype of lawyers better than our stereotype of waitresses.

Confirmation Bias: Our tendency to seek out and more effectively recall evidence that confirms a hypothesis ratherthan evidence that disconfirms it. Also refers to our tendency to interpret ambiguous evidence in a way that supports rather than refutes the hypothesis in question. Related to this is our tendency to evaluate evidence supportive of our beliefs less critically than those that potentially refute our beliefs, and to be more likely to remember confirming evidence.

Conjunction Effect: When giventwo statements, A and B, we often judge A and B together to be more likely than A or B alone. This is generally true when A and B seem to “fit” well. For example, we tend to judge that the claim “Jennifer is a feminist philosopher” to be more likely than either “Jennifer is a feminist” or “Jennifer is a philosopher” because being a philosopher seems to “fit” with being a feminist. In actuality,the likelihood of any two claims both being true is less than the likelihood that either alone is true.

Endowment Effect: Our tendency to rate the value of something we already own above the value of something we do not possess. For example, we routinely set a price to sell something we own significantly higher than we indicate we would be willing to pay to attain that same object.

FalseConsensus Effect: Our tendency to overestimate the degree to which others are similar to us in their beliefs, experiences, values or characteristics.

Focused v. Unfocused Predictions: We tend to remember unfocused predictions (vagaries such as “you will meet a tall, dark stranger”) that are confirmed, and forget those that are disconfirmed. This is because only confirmation is memorable....