The decision question
How can I tell whether something really got worse or the past only looks better in memory?
Reviewed lenses
- Declinism – when the present is judged against an idealized past — Declinism is best treated here as an umbrella label for judging the present as worse than an idealized past, not as one standardized cognitive-bias construct with a single mechanism. Research directly supports several narrower ingredients: people can remember past experiences more positively than they experienced them, negative affect associated with autobiographical memories often fades faster than positive affect, and large multi-study work finds a pervasive illusion of moral decline. None of this means that every claim of social, technological, institutional, or personal decline is false; real decline must be tested against domain-specific evidence.
- Rosy Retrospection – when a past experience is remembered more positively — Rosy Retrospection describes a pattern in which later evaluations of a past experience can become more positive than evaluations recorded during the experience itself. The classic work studied specific meaningful events and found more positive anticipation and later recollection than in-the-moment experience. This does not mean that every fond memory is false, that all past periods were worse than remembered, or that nostalgia is itself a bias.
- Fading Affect Bias – when negative emotional intensity tends to fade faster — Fading Affect Bias describes an average asymmetry in autobiographical memory: affect linked to negative events tends to weaken faster over time than affect linked to positive events. It is a group-level pattern with important moderators, not a rule that every painful memory becomes mild or positive. Recent large-sample work also finds the pattern when people directly report how the affect of their memories changed, rather than relying only on calculated differences between retrospective ratings.
- Denomination Effect – when the shape of money changes our willingness to spend it — Raghubir and Srivastava reported field and laboratory studies showing lower spending likelihood when the same amount of money was held as one larger denomination rather than several smaller denominations. Later work by Raghubir, Capizzani and Srivastava connected denomination and numerosity to how accurately people remember and monitor money in a wallet. More recent research also shows that the direction can differ in special contexts such as tipping, so denomination is not a context-free switch that always changes spending in one direction.
- Hot–Cold Empathy Gap – when one state is a poor guide to choices in another — The hot–cold empathy gap describes difficulty predicting preferences, behavior, or experience across different visceral or affective states. In a relatively cold state, people can underappreciate how pain, hunger, sexual arousal, craving, fear, anger, and other hot states will change motivation and choice; in a hot state, they can also overproject the current state into the future. The pattern can be intrapersonal or interpersonal and should not be reduced to a generic claim that emotion always causes bad decisions.
- Anchoring Effect – when a starting number pulls later estimates toward it — Anchoring is a well-supported effect in which an initial numerical value can pull a later estimate toward it. A 2026 meta-analysis covering 2,601 effect sizes found a large overall effect, but also substantial variation across studies. The effect should not be treated as a rule that every number changes every judgment: incidental anchors, anchors from a different dimension, clearly random values, incentives, and some debiasing conditions were associated with smaller or null effects.
- Anthropomorphism – when nonhuman systems are read as humanlike — Anthropomorphism is the attribution of humanlike properties, intentions, emotions, or mental states to nonhuman agents. It is a well-established psychological phenomenon, but it is not automatically a cognitive error: humanlike models can sometimes be useful. The risk appears when humanlike cues are treated as evidence for capabilities, understanding, accuracy, consciousness, or motives that have not actually been demonstrated.
- Appearance–Capability Expectation – when a robot’s design changes what you expect it can do — Research supports the broader pattern that a robot's appearance, morphology, framing, and human-likeness shape expectations about its competence, social qualities, and likely behavior. However, 'Form-Function Attribution Bias' is not an established standardized name in the literature. On this site it should be treated as a project label for appearance-driven capability expectations, not as a universally recognized cognitive-bias construct.
- Availability Heuristic – when easy-to-recall examples shape frequency judgments — Availability is a judgment heuristic: people can use how easily examples or scenarios come to mind when estimating frequency or probability. That shortcut is not automatically an error because memorable or accessible examples can correlate with real frequency. Bias appears when accessibility is driven by factors that are not diagnostic of the quantity being judged.
- Confirmation Bias – when a belief shapes how evidence is searched and judged — Confirmation bias is an umbrella label for several ways existing beliefs or hypotheses can influence information search and interpretation. It should not be reduced to one behaviour such as reading only agreeable news, and a preference for confirming tests is not irrational in every task or environment.
Decision guides
- Work & project decisions
- Forecasting & future choices
- AI-assisted decisions
- Project estimation & delivery
- Checking claims & misinformation
- Comparing plans & pricing
- Defaults, settings & choice architecture
- Presenting risk & options
- Reviewing KPIs & proxy metrics
- Was the past really better?
- Continue, change, or stop a project
How to use this page
Start with the decision, not with a label for a person. Open the evidence behind the lenses that fit, compare nearby concepts when needed, and keep uncertainty visible.

