Ecological Validity has two distinct usages that will both sometimes be used. The most common usage comes from the experimentaI sciences and refers to the degree to which experimental findings generalize to real-world settings. Studies that are true in a controlled lab setting often fail to generalize to real-world settings for a variety of reasons: real-world environments may be designed in ways that change how decision makers behave in artifical experimental contexts; scenarios used in experiments may be hypothetical and unrealistic in ways that affect decisions; study participants may not behave the same in a setting they know is artificial or because they do not have experience in the decision domain in cases where they would have such experience if they were in a position to make such decisions in the real world; and institutions and cultures often co-evolve alongside decision makers in real-world decision contexts to create meaning-laden values, practices, beliefs, and tools surrounding the decision activity that may be absent in an experimental context. The conception of validity is similar to the more general concept of external validity, which considers the generalizability of findings across various populations and scenarios.
The second meaning of ecological validity refers to the extent to which a particular cue in the environment provides accurate information to predict outcomes within that ecological context. This conception is important to the science of judgment and decision making because judgments are about external facts or dynamics that we rarely have direct insight to, and so we need to use cues as a proxy for the variables we wish to accurately make judgments about. This meaning comes from the work of the psychologist Egon Brunswick and his lens model of perception which has been influential in the psychology of judgment and decision making thanks primarily to the work of Kenneth Hammond.
The basic idea is that there are certain judgments people wish to make about the state of the world (say, how far away a tree is or whether G5 towers decrease immunity). We rarely have direct access to that information, so instead we use available cues in the environment that we believe correlate to and help predict the answers we seek (how large the object is on our retina, or what our respected peers or experts say on social media, for example). Cue validity is a measure of how well such cues work (e.g., how well the size of the tree on our retina does in allowing us to predict tree distance or how well our peers and respected experts on social media do at providing reliable information). In fact we often use multiple cues (we bring in knowledge about the usual range of tree size or what we already believe about the relationship between G5 towers and health, for example). Sometimes cues work really well in one environment or given one set of tools but poorly in other environments or with other tools: consider the different quality of information on social media from conversations with friends or publications in traditional news outlets before the Internet; or the kinds of cues hearing, deaf, or blind people use to assess a conversation from across the room. Brunswick’s conception of ecological validity is directly concerned with how well a cue works in a given environment.
This ties back importantly to the more common sense of ecological validity, particularly in criticisms of experimental methods in judgment and decision making, since experimental settings are often intentionally designed in non-standard ways so as to bring about a certain error in judgment or decision making. This is useful to establish that people do not use the optimizing models of rational decision making that have had such sway especially in the early days of rational choice theoryLink to Wikipedia entry More, but it can also make heuristics used in judgment and decision making seem particularly error prone and irrational, despite the fact they may tend to work well given the real-world environments in which they are most often used. This concern has played a central role in criticisms of the heuristics and biasesIn decision science, bias refers to systematic and predictable deviations from accepted models of rationality. In scientific language, "systematic" and "predictable" are not meant to... tradition by the controversial scholar, Gerd Gigerenzer, and it is a theme that will come up repeatedly when considering the rationality of gambler’s judgments and decisions in the casino, and “judgments and decisions in the wildDecisions from Experience vs Decisions from Description "Decisions from description" and "decisions from experience" are two paradigms in the experimental study of behavioral decision making....,” more generally.