Todd and Gigerenzer begin their response by addressing the ideals that the adaptive toolbox conflicts with. These idealistic assumptions are:
- More information is always better – Sternberg argues “you are always better off using as much information as possible when time allows” for consequential decisions. Todd and Gigerenzer argue this ideal is misleading and “in order to make sound decisions in an uncertain world, one must ignore some of the available information”. Engel points out that “frugality conflicts with legal systems, which often run on the defensive vision that more is always better” (767).
- Optimization is always better – Shanks & Lagnado argue that fast and frugal heuristics cannot account for human behavior because they do not optimize and human behavior can be optimal. Todd and Gigerenzer emphasize the distinction between optimizing processes (heuristics do not employ) and optimal outcome (heuristics can reach). Furthermore, using optimization does not guarantee an optimal outcome.
- Complex environments demand complex reasoning strategies – Allen suggests that social environments are “responsive” rather than “passive” and therefore, are so complex that they require demonic reasoning abilities. Todd and Gigerenzer respond that “simple social exchange rules can coordinate social interactions without logical reasoning” (768). Furthermore, logic can make one predictable and therefore more open to exploitation.
- Search can be ignored – Oaksford argues “information is usually integrated in decision making by pointing to examples (such as speech perception and sentence processing) where the necessary information is available simultaneously, obviating search” (768). Todd and Gigerenzer emphasize the requirement of searching for cues in many decisions situations.
Where do heuristics come from?
In this section, Todd and Gigerenzer address clarification questions about the origins of heuristics. They give three answers for where heuristics come from.
First, heuristics can arise through evolution. Baguley & Robertson express concerns about how heuristics get into the adaptive toolbox. Todd and Gigerenzer clarify they had no intention of giving the impression that evolution and learning are mutually exclusive. They further explain that “there would be strong selective advantages in coming into the world with a least some heuristics already wired into the nervous system” (768). Houston mentions that there is growing literature surrounding the use of heuristic by animals in specific environments. Hammerstein states the difference between an optimizing process and an optimal outcome. He discusses evolution as an optimizing process for how decision mechanisms come about in biology. He also argues that “a heuristic that was evolved for adaptive use in one environment may be misapplied in another” (769).
Secondly, heuristics can arise through individual and social learning. Baguley & Robertson claim that certain heuristics can be learned. Todd and Gigerenzer agree with this claim but emphasize the distinction between adding a new tools to the adaptive toolbox and learning to use old tools in a new way. Solomon distinguishes two developmental changes that apply to this distinction. Changes in core “theories”, concepts, and reasoning principles may be called the tools in the toolbox while changes in “expertise” with age may change how or when tools are used. Furthermore, many developmental questions arise from the adaptive toolbox perspective. Barrett & Henzi question if fast and frugal heuristics are specific to human reasoning. Todd and Gigerenzer claim that humans rely heavily on social learning of heuristics which enables rapid addition of heuristics into the adaptive toolbox and is the foundation for culture. Gorman also describes how both heuristics and decisions themselves can be obtained from other individuals.
Finally, heuristics can arise through the recombination of building blocks in the adaptive toolbox. Huber purposes that the adaptive toolbox is made up of many “partial” heuristics and multiple “partial” heuristics are used most decisions.Todd and Gigerenzer claim Huber overgeneralizes from the artificial lottery problem of risky choice and his assertion sets up a false opposition. The adaptive toolbox can hold both “partial” and “global” heuristics.
How are heuristics selected from the adaptive toolbox?
Many commentators propose ideas about heuristic selection. Todd and Gigerenzer point out that “heuristic selection may not always be a problem” (770). Feeny claims that there are situations when heuristic selection is not needed. Heuristics in the adaptive toolbox are designed for specific tasks and this reduces the selection problem. Furthermore, the knowledge available reduces the set of possible heuristics when making a decision.
However, even after making the set of possible heuristics smaller, there still may be multiple heuristics applicable for a given situation. Morton suggests “a meta-heuristic which chooses between heuristics using the same principles as the fast and frugal heuristics themselves”. Feeney fears an infinite regress of meta- and meta-meta-strategies for determining the best heuristic and meta-heuristic for a given situation. Cooper and Feeney also worry that meta-heuristics won’t always pick the best heuristic. Todd and Gigerenzer respond with the claim that “the whole point of the adaptive toolbox approach is not aiming at optimization” (770). Furthermore, since more than one heuristic can be used in many situation, the choice between them isn’t critical.
Cooper questions the conditions required for selecting certain heuristics. Todd and Gigerenzer respond that most heuristic-relevant conditions haven’t been discovered yet. Margolis fears that heuristics that adapt to certain conditions may be harmful when significant changes to an environment occur. Todd and Gigerenzer point out that these maladaptive heuristics may be “replaced by new more appropriate heuristics acquired through individual or social innovation and learning” (772).
How can environment structure be characterized?
Todd and Gigerenzer stress the importance of environmental structure in order to understand cognition and behavior in terms of adaptation, as these are shaped by previous environments. Two approaches to studying the structure of environments are the search for environmental/ecological texture and the search for invariants in the visual environment. However, both these approaches overlooked the relationship between heuristics and environment. Simple Heuristics focuses on a few types of environment structures: environments in which lack of recognition is informative; noncompensatory information; scarce information; J-shaped distributions; and decreasing choice sets.
Allen and Sternberg touch on important points about cost-benefit analysis, stating that there are cases in which the cost of making a wrong decision outweighs the benefit of simple heuristics and therefore it is worth the extra time and analyses of the more consequential decisions. Todd and Gigerenzer respond by taking into account the significance structure of the decision, using the example of avoiding poisonous mushrooms differently when they are lethal or not. They conclude that while consequential decisions are often overthought and require justification, it is likely that the decision is reached very quickly, and much of the following thought processes are used to justify the decision that was made originally.
The difference between friendly and unfriendly environments, as Shanteau & Thomas point out, is that “friendly” envs. can all be positively correlated, while a subset of “unfriendly” envs. can be negatively correlated. Todd and Gigerenzer welcome this, further explaining that unfriendly envs. contain tradeoffs to simple heuristics. As the number of cues increases in an unfriendly environment, the performance of fast and frugal heuristics decreases. To mitigate this, we can combine partial heuristics to eliminate poor options first, then use a lexicographic process on the remaining.
An important area of adaptation to these heuristics is social rationality, and the authors agree with commenters calling for research to combine psychology and game theory for the understanding of interactive strategies. Simple heuristics may be exploited by more complex thought. They may also be exploited in J-shaped distributions, which occur in environments of power laws and Poisson processes.
Heuristics monitor and assess valid environmental cues at the surface level covarying with the decision variable rather than cues causally linked, since both are caused by the same process. It is possible a decision can be made with only one surface level cue, in comparison to the several or more casual cues necessary.
How can we study which heuristics people use?
It is difficult to obtain empirical evidence for heuristic use, but Todd and Gigerenzer stand firm in the belief that it is possible especially in the case of new predictions. In situations where there is little prior knowledge, it is easy to diagnose how they come to simple conclusions on new information. They criticize hypothesis testing in psychology, stating that there is no hypotheses other than a null hypothesis, and that we cannot assume how people use heuristics and use aggregated means. Instead, the adaptive toolbox is necessary to study heuristic usage, which includes (1) specifying potential heuristics, (2) deriving predictions for each, and (3) testing each participant’s judgement against those predictions. This encourages precise predictions based on individual differences in knowledge.
Solomon proposes that this methodology is important in ontogenic development, following pre-schoolers through childhood, adolescence, and into adulthood. Chater additionally speaks on the complementary studies of simple heuristics and rational analysis, which finds optimal solutions through elimination processes of simplifications.
What is the evidence for fast and frugal heuristics?
While it is widely accepted that animals use simple heuristics in their environments, it is more difficult to analyze human usage. Cooper and Harries & Dhami claim there is little evidence that humans use fast and frugal heuristics; however, Todd and Gigerenzer stand by their piece and empirical evidence along with other studies who found similar results. Humans often look up only one or two cues in order to avoid finding conflicting evidence. Cue dependency can be ignored in suitable environments for accurate strategies. Despite their hesitations, Harries & Dhami conclude that simple heuristics can even be used in legal or medical decisions.
The authors push back on Allen’s note that there is no evidence that people make inconsistent, intransitive judgments, using another study in which some people incorrectly inferred that A is greater than B, B is greater than C, BUT C is greater than A (which is intransitive).
Kainen asks for examples of heuristics in other fields such as perception, engineering, and language processing, but Todd and Gigerenzer stress that we must be aware of artificial mechanisms working similarly to the human mind.
What criteria should be used to evaluate the performance of heuristics?
Todd and Gigerenzer focus on multiple corresponding criteria rather than internal coherence. Since many people often violate first order logic (see the cities example) and ignore laws of probability, the authors question whether cognitive psychology properly evaluate human reasoning and cognition. Instead, they believe we should focus on correspondence between heuristics and environments.
Allen and Fuller note the tension between coherence and correspondence to the real world, despite the ability for a belief to satisfy both criteria. However, we cannot have complete coherence given our bounded rationality. Simple heuristics focus on inferences, where coherence and correspondence may diverge. Bermudez questions the justifiability of simple heuristics evaluated on success alone; the authors push back saying that the process of evolution and learning use success to improve processes for future decision making.
Many responses extend the discussion of performance criteria of heuristics in societal and legal settings, raising fundamental questions. What are the implications of using simple heuristics with regard to the law?
Conclusion
This study of bounded rationality and its multidisciplinary results have relevance for many sciences attempting to understand organisms’ behaviors. Using the adaptive toolbox to find what lies inside is difficult, but fast and frugal heuristics allow us to reevaluate some underlying assumptions of world representations. We must extend our understanding of ecological rationality- how environment structures and heuristic mechanisms work together.
Questions:
Other than quick decisions, where and when can fast and frugal heuristics be effective?
It is likely that animals use fast and frugal heuristics most of the time. Humans obviously have capabilities much greater than this. However, are the fight or flight type decisions something that animals are superior to us in?
Where is the line between decisions and beliefs, especially if we are using simple heuristics
What are implications of using simple heuristics with regard to legal processes?
The authors argue from a transformative view of epistemology insofar as they acknowledge the necessity of empirical evidence to justify their view of fast and frugal heuristics.
The authors also state that “the adaptive toolbox is necessary to study heuristic usage, which includes (1) specifying potential heuristics, (2) deriving predictions for each, and (3) testing each participant’s judgement against those predictions”
To what extent is this process similar to the scientific method?
In accordance with both Chelsea and Eliza, I am also sympathetic to the evolutionary approach that many responders to Todd and Gigerenzer have employed to explain the adaptive utility of “fast and frugal” heuristics. In conventional discourse, heuristics are often though of as implicitly disadvantageous “shortcuts” that are inferior to a more complete, comprehensive disposal of knowledge in a given situation. As responders such as Goldman (p. 751) point out, however, there is compelling reason to believe that people who effectively employ heuristics often possess more “problem-specific” knowledge than their non-heuristic-employing counterparts who possess more “total” knowledge, which is considerably less effective for the purposes of problem solving. Goldman specifically mentions the “recognition heuristic” for its counterintuitive nature in this regard. Goldman cites Gigerenzer while mentioning this counterintuitive nature, who wrote “The recognition heuristic can thus lead
to a paradoxical situation where those who know more exhibit
lower inferential accuracy than those who know less” (Gigerenzer
et al. 1999: pp. 45–46).
Can this counterintuitive, heuristic advantage (that results from possessing less total knowledge but more problem-specific knowledge) be empirically measured? That is, can we definitively say that “less is more” in terms of the volume of situational knowledge that one possesses, as Goldman argue?
Must one be conscious of the fact that they are employing a heuristic, such as the aforementioned recognition heuristic, in order to realize its epistemological “less is more” benefit?
For the most part, I agree with Todd and Gigerenzer on their perspective of fast and frugal heuristics as a structural model of human reasoning under natural constraints of limited time and knowledge. Undeniably, as Sternberg mentioned, more information is better to make a well-informed decision, but it is unrealistic to expect unlimited information to contribute to the formation of a belief when ignoring certain information can lead to the same belief just as well in a shorter amount of time. However, several commentators brought up many good points that I think are worth to take into consideration.
For example, as Tim already pointed out, as well as Neve and Marissa in their questions section, multiple commentators raised the concern that fast and frugal heuristics is not unique to human reasoning based on primate studies. Assuming that primates cannot rationalize and hold knowledge the same way as humans, what part of fast and frugal heuristics, if any, is actually unique to human rationality? Todd and Gigerenzer responded to this concern by stating that “humans probably are extreme in our reliance on social learning” (769). They failed to further elaborate how exactly humans are extremely reliant on social learning as compared to other species, except that social learning is the basis of culture.
The commentaries from Allen and Sternberg about the cost-benefit analysis were convincing to me because it highlights a weakness in the fast and frugal heuristics argument, which is that there is no room for self-monitoring in belief formation. Much of Todd and Gigerenzer’s response to their comments involved stressing that rationality often occurs after the belief has been formed. Their response seems reasonable when taking into consideration the biases and stereotypes people have and attempt to justify, but I also believe that biases can be consciously changed by being more aware of their existence. Is there a more sophisticated model of justification as other commentators have proposed that is just as plausible?
Kainen’s commentary also made me question how mathematics is rationalized according to fast and frugal heuristics. Is fast and frugal heuristics even applicable to mathematics?
Since other commentators have pointed out that there is little evidence to support that humans use fast and frugal heuristics, I’m curious to know if there has been any empirical evidence to back up Todd and Gigerenzer’s argument since they’ve written this paper.
I had similar thoughts as Olivia about the Baguley and Robertson response. When faced with the task of selecting a heuristic from our toolbox, fast and frugal heuristics are only supplementary (743). I think of fast and frugal heuristics not as a motor-response reaction, such as removing your hand from a hot pot (that does not involved cortical decision-making processes), but rather as a gut-reaction. If you’re taking a test and come across a multiple-choice question that you’re unsure about, teachers and professors often council you to go with your gut reaction (have you ever written an answer down and then changed it, but when you get the test back, the answer you erased was the right one?).
Fast and frugal heuristics are engrained in us evolutionarily, as with our animal counterparts, and I think they are our first “decision-making” process, but that, as Baguley and Roberston assert, we defer to other heuristics to make more sound or complex decisions. I think Allen’s response regarding complex environmental factors shows why the first-response of fast and frugal may not always be the best decision. “Failures of logical or probabilistic consistency provide additional vulnerabilities that a logically or statistically proficient opponent might exploit” (742). In short, complex decision-making outweighs fast and frugal in a complex situation. However, Todd and Gigerenzer note that “the general assumption that increasingly complex environments can only be tamed by increasingly complex strategies is doubtful” (773). Maybe, when overwhelmed by information, the gut-reaction of F&F is preferable, but more complex heuristics should also be consulted? I am unsure of where to draw the line, but I’d be more inclined to say there’s overlap between F&F and complex heuristics and that we often use both.
I am interested in the discussion on how to study which heuristics people employ. As discussed in the summary above and on pages 773-774, Todd and Gigerenzer propose a method of studying heuristics that differs from comparing group means to a null hypothesis. I have doubts about sections (2) and (3) of Todd and Gigerenzer’s proposed testing model: “(2) deriving the predictions for each heuristic on the experimental task, and (3) testing each participant’s judgement against the predictions of each heuristic” (774). Could there not be a case where two heuristics lead an individual to the same conclusion? If so, it would be difficult to derive predictions. It would also be difficult to determine whether a participant’s judgement was a result of one heuristic or another. It is also possible that individuals may use the same heuristics, however this heuristic leads them to a different conclusion. For example, ignorance-based heuristics are dependent upon the experiences of an individual. Participants could employ ignorance-based heuristics that motivate different decisions. The proposed alternative is testing heuristics by comparing mean outcomes to a null hypothesis. I do not feel this method would resolve the issues highlighted above either. Is it necessary for participants to self-report which heuristics they use in order to study heuristics?
One of the main questions that I have about fast and frugal heuristics lies in the distinction or the dividing line between these heuristics and higher level processes. This subject was discussed in depth by Baguley and Robertson, who come to the conclusion that “fast and frugal heuristics supplement traditional problem solving research” (743). But do we not use fast and frugal heuristics all the way up to the highest level of though? I would argue that, try as we might, we cannot ever shake the instinctive decision making process that comes naturally to us. Animals, it is widely agreed, use fast and frugal heuristics to make ‘decisions’ (is it really a decision if they are not conscious of it?) in their lives, and are humans not just animals capable of higher level processing? Even in the highest level decision making and other forms of thought such as problem solving and discovery, I think that we cannot help but use these shortcuts in our cognitive processes.
Also, as we discussed briefly in class, is there a limit to the amount of information that humans can effectively process when it comes to making a decision? We now have almost unlimited information at our fingertips, so how can fast and frugal heuristics adapt to this change in environment? Perhaps the bigger decisions in life do not use fast and frugal heuristics and therefore we are able to take more information into account. Sternberg points out that Gigerenzer and Todd look at many different decision making scenarios, but not really any with high stakes, and he takes issue with the idea that fast and frugal heuristics can be applied to all decisions. I don’t know whether f+f heuristics can be nested and layered to an extent that they can be applied to the highest level decisions and take more information into account. And if they cannot, how will we continue to thrive in a world where our decision-making mechanisms do not match the environment? What would this disconnect even look like?
When Todd and Gigerenzer began by addressing the ideals that the adaptive toolbox phenomena conflicts with, specifically that more information is always better, it reminded me of Professor Khalifa’s comment about our lives with Internet. We have access to an overwhelming amount of information, and it would be impossible to consider it all. The Internet analogy supports Todd and Gigerenzer’s argument that we must ignore some information in order to make sound decisions. Therefore, would Sternberg think that it is impossible to ever make the correct decision when the Internet is a resource?
Whenever anyone in this paper mentions the addition of a heuristic tool to the toolbox, I can’t help to think about how the theory of evolution works. I have been imagining heuristic tools as traits. A new trait arises because of an adaptive mutation. It is not as if a random trait can just randomly appear within a population without any sort of connection to previous genotype. Therefore, when Solomon asks what heuristics are added to the box, my instinct is to reject this possibility (769). Is it possible for a heuristic to simply be “added” to the toolbox? Solomon’s other questions like which ones are modified, or which ones are preloaded, seem to make much more intuitive sense.
Continuing with this thought process, Todd and Gigerenzer’s statement that “there would be strong selective advantages in coming into the world with at least some heuristics already wired into the nervous system” seems to be believable. It makes sense that people are born with certain predispostitions, or potential abilities. However, their productive emergence is dependent on the environment. So while someone has a certain heuristic hard-wired into their nervous system, it won’t be useful unless that individual is in an environment that promotes the heuristic.
Todd and Gigerenzer, Feeny, Morton, Cooper, and Margolis, all address the issue of selecting a heuristic to use. While they all have slightly different opinions, they share the notion that a heuristic is to be “selected”. For me, the action of selection is associated with consciousness. I know that we talked pretty extensively in class about how consciousness and heuristics connect (and concluded that there are elements of both consciousness and unconsciousness), but I was wondering how it applied to heuristic selection. With Morton’s suggestion of a meta-heuristic being used in the heuristic selection process, which parts of that meta-heuristic are conscious and which parts are unconscious?
I found the evolutionary approach that many of the responders took to fast and frugal heuristics to be extremely interesting, and believe that this line of thought provides the best arguments for this type of decision making process. I took issue with Todd & Gigerenzer’s statement that “there would be strong selective advantages in coming into the world with at least some heuristics already wired into the nervous system” (768) to be troubling, however. As I understand it, these processes involve quite a bit of knowledge about the world. This knowledge and experience from interacting with the environment is how these heuristic pathways are able to form, and I find it implausible that a person with no previous interaction with the world could have heuristics “already wired into the nervous system.” Perhaps the authors meant that the human brain has an inherent ability to form these quick decision making frameworks, given enough interaction with the outside world. If this is the case, I wonder how these “decisions” differ from classical conditioning. If a stimulus is similar enough to one you’ve seen before, does your previous experience with that stimulus kick in and allow you to make a correct decision with little more information? How is this different from conditioning, from an evolutionary perspective?
To me, this question ties in with the idea of cognitive penetrability that we talked about on Tuesday, and whether fast and frugal heuristics constitute a conscious process. If, as I suggested above, these heuristic pathways were merely the product of a conditioned response, then I think that cognitive penetrability would be limited. I do believe, however, that there can be examples of fast and frugal heuristics that are cognitively penetrable. In the example that Morton gives of choosing a restaurant to eat at, the person in question will presumably be aware of the different factors influencing her decision, and perhaps even know the exact reason she chose a certain restaurant. To me, this indicates a certain degree of cognitive penetrability. Whether she is aware of the exact form of her thought process, and why she chose to weight certain arguments over others is a bit more murky.
I’d also like to touch on the lack of evidence that many of the commenters cited in their objections to fast and furious heuristics. I find this argument puzzling, as there are many examples in psychological research that show that humans are able to make “quick and dirty” decisions, if under time pressure. In a study I found entitled “Examining decision heuristics in a timed visuomotor task” (Ross, 2014), it was shown that research subjects were able to estimate the location of certain moving objects, with very little sensory input. I do agree, however, that more complex examples of fast and frugal heuristics, involving more intricate decisions are hard to find.
Ultimately, I think that the kind of decision making process that Todd & Gigerenzer describe is useful and plausible in situations where people have to make quick decisions, with limited information. I am not convinced of its applicability to more complex situations, and I still believe that these kinds of higher order processing require both applications of fast and frugal heuristics, as well as a more thorough consideration of a wider sampling of information.
On page 746, Cooper discusses the use of simple heuristics. Gigerenzer et al. (1999) “suggest a range of heuristics, but fail to address the question of which environmental or task cues might prompt the use of any specific heuristic.” After reading this quotation, I wondered if heuristics occur simultaneously or individually. For example, if you are driving in a foreign country, you must combine heuristics such as traffic lights, directions, etc. Is this actually a fast and frugal approach then if multiple are working simultaneously? This also made me think about the “Halle Berry” neuron study where one individual neuron fired when the subject saw a picture of Halle Berry. Repetition and modification of heuristics can change them and make them more instinctual.
To go along with this idea, I wonder if all cognition is fast and frugal heuristics. Baguley and Robertson discuss the adaptive toolbox on page 743. Since we are always making minor adjustments and modifications to our thinking, will most cognition eventually become heuristics or vice versa? Chater opposes this idea by explaining that many aspects of cognition are too sophisticated to be modeled in this way (745).
Barrett and Henzi discussed their study of heuristics in baboons (744). They learned that baboons primarily use simple heuristics and can make major social decisions based on these heuristics. Do you think that heuristics have greater adaptive value in animals than cognitive thinking based on a higher cost-benefit ratio? How can we measure heuristic strategies in animals? There is no universal agreement on what constitutes a heuristic strategy or even a heuristic, just that it is relatively fast and fairly simple? This is especially important as animals are used to learn more about humans.
Lastly, Gorman talks about population growth and how “the heuristic with the greatest global consequences may be the one that determines how many children to have. The greater the risk of losing a child, the more children humans want, Instead of investing heavily in one child, this is a “spread the risk” heuristic” (752). In more affluent societies, parents tend to invest in fewer offspring. Is this actually a heuristic if thought is going into having the child? Pregnancy and infancy are a large investment for a parent. I also have a broader question that has less to do with philosophy: If research showed that population growth was causing significant problems, do you think it would be beneficial to create laws that only provide healthcare for a certain number of children? Would this actually affect parents cognitively and influence how many children they have? Are hospitals actually going to reject a child that cannot afford healthcare if he or she is not one of the first in his or her family?