Section 3: Identifying Bias and its Impact Flashcards

Principle of Charity
Example: "You oppose immigration? Let's discuss border policy merits."


is a rule of rational discourse that requires interpreting someone’s argument in the most reasonable, strongest possible form—even if they didn’t express it perfectly—before critiquing it

• Interpret arguments in their strongest form

Confirmation Bias
Example: Believing a diet works despite contradictory studies

• Favoring info that supports existing beliefs

Availability Heuristic


is a cognitive bias where people judge the likelihood or importance of something based on how easily examples come to mind

• Judging likelihood by memorable examples

Anchoring Bias
Example: 50shirtmakes50shirtmakes30 seem "cheap"


is the tendency to rely too heavily on the first piece of information offered

• Over-relying on first info received

Representativeness Heuristic
Example: Assuming quiet people are unfriendly


is a mental shortcut where people judge the probability of an event by how closely it matches their expectations (stereotypes, prototypes, or past experiences) rather than using actual statistical likelihood

• Stereotype-based judgments

Aliefs
Example: Fear on a glass floor despite knowing it's safe

a mental reflex or an automatic belief that conflicts with your conscious beliefs or reasoning. It’s the way our brains can sometimes react without us thinking about it, even if it doesn’t match what we know logically

• Gut reactions contradicting beliefs

Bounded Rationality
Example: Picking a "decent" restaurant quickly

means that people try to make smart decisions, but their ability to do so is limited by:

• "Good enough" decisions with limited info

System 1 Thinking
Example: Jerking hand from a hot stove

• Fast, automatic

System 2 Thinking
Example: Calculating mortgage rates

• Slow, logical

Algorithmic Bubbles
Example: Only seeing one political viewpoint

• Echo chambers from personalized feeds

Ad Hominem
Example: "You can't argue for taxes if you avoid them!"


happens when someone attacks a person’s character, appearance, or background instead of responding to their actual argument or ideas

• Attacking the person

Straw Man
Example: "You want lower tuition? So you hate teachers?"

fallacy happens when someone distorts, exaggerates, or misrepresents another person's argument to make it easier to attack. Instead of engaging with the actual argument, they create a weakened version of it and knock that down instead.

• Misrepresenting an argument

False Dilemma
Example: "Either ban cars or accept pollution deaths!"


happens when someone presents only two choices as if they’re the only options, when in reality, there are more possibilities

• Only two extreme options

Slippery Slope
Example: "Legalizing weed → heroin epidemic!"

• Unfounded chain reaction

Post Hoc
Example: "I wore red → team won → red is lucky!"


happens when someone assumes that just because one event happened before another, the first event must have caused the second

• Assuming causation from correlation

Texas Sharpshooter
Example: Highlighting only successful diet cases

• Cherry-picking data

Hasty Generalization
Example: "One bad Uber ride → all drivers are rude!"


happens when someone makes a broad conclusion based on a small or unrepresentative sample of data, instead of having enough evidence to support it

• Broad conclusions from small samples

Appeal to Ignorance
Example: "No one disproved ghosts → they exist!

• "No proof against X → X is true!"

Genetic Fallacy
Example: "Nazis used euthanasia → it’s always evil"

• Judging ideas by origin

Red Herring
Example: "Why discuss taxes when aliens exist?"

is a fallacy where someone introduces irrelevant information or a distraction to divert attention away from the real issue or argument

• Irrelevant distractions

Selection Bias
Example: "Married men live longer" (healthier men marry)




- occurs when the sample used in a study is not representative of the population being studied, leading to skewed or inaccurate results.

• Non-representative samples

Random Sampling
Red Flag: Surveying only college students about retirement

• Equal chance for all members

Confounding Variables
Example: "Coffee drinkers live longer" (maybe they exercise more)"


is an unaccounted-for factor that distorts the apparent relationship between the variables you're studying, creating a false or misleading association.

• Hidden influencing factors

Base Rate Neglect

happens when people ignore general statistical information and focus too much on specific details or personal stories.

• Ignoring general prevalence