Stanovich and West set out to address two major topics in their response: the role of individual differences in the normative/descriptive gap and the two-process model of evolutionary rationality (System 1) and normative rationality (System 2).
R1. Individual differences and the normative/descriptive gap
R1.1. Normative applications versus normative models.
First, they touch on the distinction between normative applications and normative models, claiming that many authors misunderstood their attempt to use patterns of individual differences. S&W clarify that they used patterns of individual differences not to determine whether normative models are adequate, but to determine when to apply a certain normative model to a particular situation. They stress the importance of empirical data in determining the applicability of certain normative models (rather than their correctness). With their data, S&W were trying to shed light on specific norm applications in particular situations and whether the norms applied were appropriate to the situation or not (for example, they reference the cabs problem and the applicability of Bayes’ Theorem to the situation).
R1.2. The understanding/acceptance assumption.
They also discuss the understanding/acceptance assumption and its efficacy as a tool for judging different explanations for the normative/descriptive gap. They confirm Schneider’s view that the assumption is “necessary but not sufficient criterion” (702) for understanding the gap in behavior. Notably, the assumption posits that intelligent people are more likely to apply the correct normative application. S&W next turn to the Allais paradox, countering the belief of Ayton and Hardman that the assumption fails if it cannot judge the normative model applied in this case. However, S&W argue that norm misapplication is at fault for the dispute arising from this paradox, and the understanding/acceptance assumption should not be held accountable.
R1.3. Relativism and rational task construal.
In the next section, S&W look at rational task construal. S&W cite the Panglossian view on rational task construal, that any and all task construals are rational and intransitivity can be eliminated by construing the problem in such a way that removes the intransitivity. In this view, the task is construed in such a way that makes the task and task responses rational and the person involved rationally competent. However, alternative task construals do not protect one from irrationality, as one can be charged with irrationality in a different part of the process. Cognitive evaluation is crucial for determining the rationality of task construals.
R1.4. Cognitive ability and the SAT.
S&W strongly defend their usage of tasks from the heuristics and biases literature and SAT scores as different measures of cognitive ability. They claim that the tasks they measured were of a completely different nature than those on the SATs, and that, notably, reasoning tasks do not have a correct answer. Correlation, or lack of correlation can be used to examine the normative model and task construal used in particular problems. S&W refute the claims of those who criticize their use of SAT performance as an indicator of cognitive ability. They draw clear relationships between general intelligence, working memory, computational capacity, and fluid intelligence, all reflected by SAT scores. Notably, the authors mention that education does not appear to affect performance on heuristics and biases tasks. They also note their usage of converging measures of cognitive ability that measured intelligence in a different way than the SATs and showed the same correlations.
R1.5. Alternative interpretations of computational limitations
In their target article, S&W interpreted cognitive ability measures as agents of overall cognitive intelligence. They admit, however, that there are several alternatives: (1) Cognitive ability measures may be indicators of an individual’s tendency to respond to problems with appropriate strategies, and (2) that cognitive ability may portray the number of different problem representations with which an individual can cope. These alternative interpretations therefore lead us to three distinct computational limitations: (1) limitations in how one can successfully process information, (2) limitations in the flexible deployment of strategies to solve a problem, and (3) limitations in the types of problem representations one can handle and, thus, the types of strategies one can use to solve a problem.
R1.6. Alternative Construals as a Computational Escape Hatch.
Ball & Quayle bring up an interesting idea of a computational escape hatch, which prompt S&W to blur the line between seemingly distinct notions of alternative task construal and computational limitations. Alder suggests, and S&W agree, that perhaps tasks are being interpreted as different from what the experimenter intended because individuals cannot fully grasp that task, and thus the normative model. S&W mention that alternative construals can be used as computational escape hatches by either being consciously aware of all the alternative task interpretations and choosing the one with the lowest computational demands, or choosing it without being aware of the other alternatives.
R1.7. Thinking Dispositions and Cognitive Style.
S&W agree with Kuhberger and argue that thinking dispositions and cognitive capacities are different, distinguishable concepts as they function on different levels of analysis. They argue that cognitive abilities indicate individual differences in the efficiency of processing at the algorithmic level while thinking dispositions indicate individual differences at the intentional level. S&W have found that thinking dispositions can explain variance independent of cognitive capacity supporting the separability of the two.
R2. Rationality and Dual Process Models
As Friedrich and others point out, S&W are proud of their ability to “bridge between the evolutionary and traditional biases perspectives” (707), especially in order to reinforce their argument for the dual-system processing. The goals of the 2 systems should be similar, to strive for normative rationality, but Frisch stresses that it is not necessarily that both systems will compute and conclude the same way. System 1 processes, or lack of processing, are often attributed to any irrational behavior. However, S&W recognize the potential downfall in overanalytics, citing Hardman’s research in which they found those who were analytical made less effective decisions. They also continue to support the rationality behind the Meliorist framework.
R2.1. Short Leash, Long Leash Goals
S&W explain short leash vs long leash using the Mars Rover example, in which something that can no longer be “short leash” controlled remotely must be given the “long leash” ability to control itself (710). Giving Systems 1 short leash goals of “if A, then B” allows it to remain functionally rational. System 2 is more equipped to reach for long leash goals, in which we boil it down to “Do whatever you think is best,” as offered by Dawkins. In order for System 2 to correctly strive for this goal, however, it must be given the tools to analyze and also be able to recognize what “is best,” a point that Greene & Levy comment on. S&W here push against Ayton’s notion that a rational bee with long leash goals should not sacrifice itself for the good of the hive, saying that evolutionary psychologists mistakenly presuppose that those with evolutionary rationality necessarily have individual rationality. System 2, unlike System 1, is capable of continuous goal evaluation.
R2.2. Cultural Evolution of Normative Standards
Schneider believes that “cultural evolution of norms somehow present difficulties for our conceptualization” (712). S&W disagree, as they feel cultural history of evolution supports that individuals creating progressive change in standards are of high intelligence. Then, others with less intelligence can use the newly developed standards themselves as learners. Panglossians often downplay the evolution of reasoning norms, since an “incorrect” response should never happen, but fail to recognize that changing norms can allow this once “incorrect” response to now be “correct.”
R3. Process and Rationality
Commentators such as Hoffrage, Kahneman, and Reyna critic the lack of algorithmic-level process models for many of the tasks mentioned in the target article. While S&W agree that these process models are important, they argue that this was not the point of their research program. They felt that rather than focusing entirely on the algorithmic-level model it was best to explore intentional-level models and its variance in rationality as well. They argue that exploring intentional-level constructs does not detract from the search for more extensive algorithmic-level specification and that the two levels may actually have a synergistic interplay.
R4. Performance Errors
Hoffrage treats many errors that Stanovich & West as computational as performance errors, most notably “recurring motivational and attentional problems” (713). However they argue that this is not appropriate because such errors are “in fact like cognitive styles and thinking dispositions at the intentional level,” (713) since stability and predictability goes against the random nature of performance errors. Stanovich and West argues that this is the most important implication of a performance error – that it is to be considered “trivial”, and reminds us that it only becomes something significant when it is repeated and forms a pattern.
R5. The Fundamental Computational Bias and “Real Life”
Commentators criticise the authors for focusing on problems that are not similar to real life, however the authors respond by arguing that “real life” is no longer real life as technology has “presented evolutionarily adapted mechanisms with problems they were not designed to have.” (714) They gave examples such as the food people eat as well as communications and advertisements. Commentators such as Ayton and Hardman therefore point out the necessity of the “fast and frugal” heuristics studied by Gigerenzer. Kahneman acknowledges that this process is important, but reminds readers that system 2 is still necessary to correct the associated biases. The authors seem to agree with these analyses and do think that most humans still live in the world of system 1 and laments that there are “very few situations where System ½ mismatches are likely to…have knock-on effects.” (714)
R6. Potentially Productive Ideas
Stenning & Monaghan suggests other ways to reparse the System 1/2 differences, such as cooperative vs. adversarial communication or explicit vs. implicit knowledge. Moshman’s dissection between “what a system computes,” and “how the processing is implemented,” may lead to greater explanatory power with greater clarification. The authors acknowledges other ideas such as a finer-grained scoring system by Hoffrage & Okasha, taking into account the test subjects decision-making history by Fantino, and the inclusion of further tools such as developmental data by Reyna & Klaczynski or the notions of rationality in other literatures such as philosophy by Kahneman.
R7. Complementary Strengths and Weaknesses
The different “camps” have all advanced the field through their own lenses respectively; the Panglossians have demonstrated that the answers to real-world problems are often “in human cognition itself,” (717) and that mankind is already optimising in the real world. The only necessary action is to characterise and optimise further the process. The Apologists have shed light on the power of evolution and its ability to shape cognition. The Meliorists have argued for the possibility of cognitive change and warned against the possible results of mismatches between the ways we think and the way we should think in a modern day society.
Similarly each have its weaknesses as Meliorists sometimes jump ship too quickly and blame flaws in reasoning while the Panglossians are often forced into uncomfortable positions to defend the human rationality; thus it is necessary to be open to the other possibility and take that into account. The Apologists can sometimes be too old-fashioned and fail to recognise the huge differences between the modern society and that during which humans evolved.
Discussion Questions:
- Do you think the characterizations by Stanovich & West in R7 are valid?
- Did S&W defend their choice to use the SATs as a cognitive ability measure well?
- Do you agree with the criticism that the alternative task construal is a way to mask computational limitations?
- Does S&W argument that today’s society is too technologically advanced for System 1 to continue to adapt make sense?
In the section R1.6 of Stanovich and West’s response to peer commentaries, they propose that notions of alternative task construal and computational limitations may be inseparable as an explanation of the normative/descriptive gap state that, “an alternative construal might be hiding an inability to compute the normative model” (706). I take issue with these implications. Blurring the lines of alternative task construal and computational limitations seem unfair. Is possible that the degree in which an individual understands information is based on the way the information is presented? Maybe some individual’s neural pathways allow them to be better at interpreting information they hear over information they read. If they read the task they are unable to fully interpret the task but once they hear the task they can properly acquire that information and are perfectly capable of computing the correct normative model. Therefore, an alternate construal is not necessarily related to an individual’s cognitive ability or computational power.
In Section R1.4 S&W suggest that there is a negligible link between SAT scores and level of education. In the target article they found a positive link of SAT scores to computing the normative model and therefore rational cognitive abilities. If this is true, does it mean that higher level education does not improve an individual’s ability to rationally reason and compute the normative model. If intelligence is linked to an individual’s ability to compute the normative model, then what is the point of higher level education?
In response to Olivia’s earlier comment, it seems to me that there could be motivation that led to System 1 processing as well. Perhaps both the amount and type of motivation could affect which System was used. Survival motivation, (basic physical survival: escaping danger, finding nourishment, etc.) for example, would seem to lead to System 1 processing, while more complex social or spiritual motivations could lead to System 2 processing. It seems survival motivation could be unconscious.
There has been a lot of debate over the word “intelligence,” and as I mentioned in class, I feel the ambiguity of the word itself and the multiplicity of its varied connotations could be primarily to blame. The kind of “intelligence” I believe the authors are referring to, and which the SAT attempts to measure, is a particular ability of information processing and drawing logical conclusions (deductive and inductive reasoning, among perhaps other things). I will call this instead rationality, to distinguish it from other cognitive ability sets, equally important but fundamentally different, which could also be called intelligences (such as creativity). I personally do (at least like to) believe that there could exist a test which specifically and accurately tested rationality and only rationality, independent of education or cultural context, but I’m not sure what this would look like. The SAT certainly is not this kind of test. Even this test would not distinguish between innate and acquired rationality, which would have to be empirically studied.
A lot of people seem to be taking issue with S&W’s seemingly narrow interpretation of intelligence. I think most of us are in agreement that people can be “smart” in different ways and good at different things. It is a messy business to parse out “intelligence” from all this, and even then these descriptions of intelligence could still be dependent on subjective definitions.
But in their description of the duel process system of reasoning, S&W outline two broad “types” of intelligence, interactional and analytic, which relate to System 1 and System 2, respectively (659). I think that when they refer to intelligence and cognitive capacity in terms of the SAT and logical tasks they are talking about analytic intelligence, and if you accept this their arguments seems tighter. I’m wondering if people might view S&W’s paper, and especially their version of the duel process system, differently if they are willing to temporarily roll with this definition of intelligence.
In terms of the SAT, I agree that the test is inherently flawed and the thing it assesses best is just how good you are at the SAT. But I wonder if the SAT could still be a useful to correlate with performance on these reasoning tasks. Even if you disagree with S&W’s conclusions regarding the SAT, would it be possible to draw any other meaningful conclusions from these comparisons? Or is the SAT so inherently flawed that comparing it to anything is just totally misleading?
Given the target article’s deeper focus on normative application and alternative task construal, I was more curious and interested in the interpretation of computational limitations and cognitive ability. Our inability to always think rationally and form to a normative model may not be due to accidental misinterpretation of such problems and models, but rather due to simple cognitive deficiencies that we, as humans, sometimes refuse to admit. I believe that this mistake comes from the complex distinction between human and non-human cognition. S&W say that “Computational limitations in humans are not fixed in the way they are in a computer and…[therefore] they should not be conceived as absolute limitations” (705). But what exactly do they mean by this? Are these limitations less static and more dynamic as humans evolve (hopefully) in the direction of greater cognitive ability? If so, how might cognitive ability evolve: through greater processing power, metacognitive control, and/or number of problem representations available to the rationalizing mind? Furthermore, are ‘computational escape hatches’ evolutionarily ingrained in human rational or are they more consciously ingrained in the individual’s self-interests and thinking dispositions?
S&W state the understanding/acceptance principle is used as a clue to infer whether some task construals are more rational than others in order to avoid ‘the trapdoor of relativism’ (704). They then introduce an analogy about morality and state that just as the recognition of a situation with moral dimensions is a large part of morality, the construal or a problem is a large part of rationality. Therefore, we wouldn’t set aside moral evaluation just because we have accepted all judgments of moral relevance, so we also should not set aside cognitive evaluation because we have accepted all task construals as rational (704). I think that this is a valid argument, but it makes me question the idea of morality in terms of normativity. How much does morality play a role in considering the rationality of a situation? S&W state that if we accept views in which rationality and morality coincide, it is clear that many cultural institutions like schools, churches, and parents, attempt to teach this rationality (706). Is this implying that moral judgment is a part of the total competence or intelligence of an individual? I would say that there are instances where a highly intelligent individual when facing a moral dilemma can act morally wrong, but still highly rationally. How would S&W say this plays a role in explaining the gap between the normative and the descriptive?
Conversation, and perhaps the debate, about what intelligence exactly is seems to be an ongoing one among S&W’s reviewers and our own peers in class. S&W’s discussion on SAT and some peer reviewer’s (particularly Schneider and Sternberg) skepticism towards the SATs as an appropriate way to measure intelligence only further convinces me to think that a conversation aimed to reach a concrete definition of intelligence – if this is at all even possible – to be an important one. What criteria is used to define “intelligence”? How does our way of assessing “intelligence” (i.e. SAT) shape our understanding of what rational human reasoning?
Schneider (696) introduces us to the tension between intelligence and education. At what point can we look at intelligence independent from each individual’s experiences (i.e. education). This reminded me of Ryan’s point in class about how some have more “access” to certain resources than others. Hence, it seems natural to ask the following: is it fair to create a set of standards or a test against a certain standard to measure human intelligence, which seems to be arbitrary in and of itself?
Even before asking questions about what “kinds” of tests would “accurately” measure intelligence, it seems important to, first, ask ourselves what this “intelligence” is in the first place. Are intelligence and rationality independent of one another? Can someone “perform” well on an intelligence test, but his/her methods of producing such results was by irrational reasoning and thought processes?
In his response to S&W’s target article , Kuhberger brings to light the role of motivation in the systematic variation (pg. 685). It seems as though higher motivation pushes people to System 2 processing and motivation can also dictate which system they fall into depending on their wants/feelings. However, it appears as though is only a hindrance in tasks that require System 1 processing. Is this always the case? Or can motivation be beneficially used in System 1 processing? Does it matter if the motivation is conscious or unconscious? Is there unconscious motivation?
Moshman (pg. 690) discusses that differences across individuals can largely be attributed to developmental differences. From what I remember, S&W did not discuss developmental differences in their target article and their responses to Moshman do not touch on the developmental aspect of his commentary. That being said, what would S&Ws stance be? Would it be fair to consider developmental differences potentially as a fifth explanation for the descriptive/normative gap?
I am honestly still trying to wrap my head around S&W’s argument for intelligence testing through the use of the SAT. Schneider’s support (695) for their idea of intelligent people being more likely to use the most effective rational strategies definitely makes sense, but as discussed in class, how do we quantify that intelligence? I agree with her- I think that the understanding/acceptance assumption is important but not enough to explain rationality. And as experience also plays such a huge role in how we judge a rational choice. What if someone never had traditional schooling, cannot understanding written language, but has physically studied his/her surroundings for years, and is still considered the wisest person in a community? They obviously would not be able to take the SAT, much less get a high score, but their experiences have made them able to observe and make the rational decision. This would go back to Schneider’s point regarding automaticity with repetition…it is as if we were to ask a 5th grader to write the ABCs, it’s become so automatic to them because of how much they have done it.
I was particularly fascinated by the example of schizophrenia and reasoning ability brought to light by Oaksford and Sellen. I think this is a great example of how our definition of logical performance can change depending on how crucial we view exceptions. Given this definition of “rationality”, O&S discovered that “logical performance was positively correlated with high levels of what it usually regarded as a dysfunctional psychological trait” (691). I think this finding is a huge step in not only how we view reasoning in individuals with neural disorders, but also that amongst the general population, there may be different – and acceptable – ways of reasoning that result in the same conclusion. My main question for this response is: have there been any other studies done on reasoning and neural disorders, and if not, which should we look at first? I instinctively lean towards autism, though one would suspect logical reasoning performance to increase in autism patients.
I find it hard to believe that education does not affect performance on heuristics and biases tasks. In addition, although the SAT may measure a certain aspect of intelligence, I do not think it is fair to use it as a measure of intelligence generally. There are many forms of intelligence- such as creativity- that are not represented in this task. This led me to a question-do normative models as well as these methods of testing intelligence miss the mark in terms of encapsulating human behavior? As I suggested in my last set of questions, by limiting human reasoning to a specific model, does that disregard all of the important differences that make us individuals?
I agree with Hoffrage’s argument that errors are not necessarily performance errors; more often than not, these errors are indicative of different “cognitive styles.” To argue against S & W’s rebuttal of Hoffrage, could it be true that these errors are not random and are in fact in a pattern, but we do not have the knowledge to decipher that pattern? Or could it be that these errors are entirely explained by the fact that evolution is an imperfect process?
I have also been thinking about the System I vs. System II distinction. It is very true that the neural processes of our brain are often broken into systems- for example, the sympathetic and parasympathetic systems of the peripheral nervous system deal with essentially opposite functions. However, even these systems are closely related and constantly compensating for one another. In addition, we are never consciously aware of the interplay between these two systems. Are we consciously aware of the distinction between System I and System II in our own processes? How are emotions processed (or are they even processed at all?) in System I and System II?