Key Concepts: Dual + Process Theories and the Tripartite Theory of Mind

There is an interesting chapter (which I link to here) by Stanovich on the “tripartite” mind that got me thinking about research, as well as being human.

Stanovich distinguishes, first, the Autonomous Set of Systems (TASS) which includes all automated parallel/associative processing. This is the set of systems that creates a “primary” representation of reality. They create the world as we initially perceive it – drawing on schemas as well as perceptual inputs. This is what dual systems theorists call System 1.

Second, he distinguishes the algorithmic mind – which creates secondary – “decoupled” representations. This is most clearly related to working memory capacity – our capacity to sustain representations in memory (and screen out distractions). He distinguishes two general abilities of the algorithmic mind, the second more sophisticated than the first. The first starts with the simplest model of the world that the person can come up with quickly, then adjusts that model, serially (one adjustment at a time). In social terms, this could be someone who is angry at their boss and who we advise to “correct” for different biases associated with anger. Basically, the angry person has one model, then we advise them to adjust it so that – if our advice is helpful – it better resembles the world.

There is a second ability of the algorithmic mind – to simulate different models of the world, and to select between them. This is a more cognitively-loading process. Intuitively, people are more likely to use this ability when they are thinking about the future. Even then, they’ll tend to want to default to a simpler process and start with a single model and then serially process it until they’re more confident in it. This approach will ultimately be more biased, assimilating or contrasting to the first impression. I think we’ve all found ourselves unable to fully break away from that initial model when forecasting future events.

Simulating and comparing multiple models could (should!) also be the process when people are perspective-taking. Rather than starting with a single model or schema (often a cultural schema) and then comparing their target’s behavior to that model (adjusting their impression of the target accordingly), people could start with multiple possible interpretations from different sources and rely on unfolding personal experience to distinguish the superior from the inferior models. Ethnographers and clinical psychologists become very good at this sort of thinking.

Last, in Stanovich’s theoretical model, is the reflective mind. This includes intentional, guiding goals, that a) can trigger the need to go beyond the TASS (the autonomous set of systems) and b) guide the algorithmic mind. People, of course, can differ in their tendency to override the TASS or to engage in single model vs. multi-model thinking. Measures like the Need for Cognition, the Need for Cognitive Closure, Personal Need for Structure, Actively Openminded Thinking, etc provide the researcher information.

I should, in closing, note that TASS-processing isn’t bad! Ideally, people would grow better at a)  recognizing when TASS-processing will fail them and b) being mindful enough of their goals that they can judge when a model is 1) sufficiently detailed and 2) gives appropriate weights to different variables. The TASS, at least in perhaps too tightly controlled thin slicing studies, can be better at both “1” and “2.”

Research Methods: Purposes

I tackle socially-relevant questions and compare different methodological approaches to answering them.

My specialities are social psychology (M.A. University of Chicago, M.A. University of British Columbia), communication (Ph.D. The Ohio Stat University), and cultural anthropology (BA with honors Darmouth College). The first three required specialization in quantitative research, emphasizing rigorous statistical training and the use of subtle experimentation to identify key variables for understanding human behavior. You may have heard of a “crisis” in the social sciences. I prefer to think of it as growing: As social scientists, we have to be honest about the limitations of our tools and strive to overcome these limitations.

Dealing with the complexity of human behavior is inherently difficult. We are unable to have the same level of certainty that a physicist or chemist may have (and even drug companies have had great trouble replicating key, published and oft-cited, findings in their field). In order to detect a reliable pattern that is consistent across situations, the best human-behavior studies would have thousands of people doing hundreds of tasks, a practical difficulty that is only occasionally surmountable.

All is not lost, however. Even a smaller study can highlight an important relationship between different factors. At that point, it’s the field’s duty to conduct more research, replicate or fail to replicate the result, and to try to understand whether the initial result was due to chance or due to a third variable that moderates (that influences the strength of) the effect.

Looking from an interdisciplinary perspective, however, we can be inspired by laboratory-studied relationships and look for independent evidence of their relevance to “the real world.” The laboratory allows us to take a micro-view, to get at what people can’t or won’t tell us about themselves. We can then take these findings to the field and look for evidence for or against the laboratory results.

As a cultural anthropologist working with the Maori, New Zealand’s indigenous people, I was keenly aware of the fact that my cultural narratives, as well as the narratives the Maori used to describe themselves, drove the questions that I asked. I was able to ask questions that pitted these potential interpretations against one another and to record the response of individual Maori informants. Were they skeptical of the narrative? Did it make sense to them? What was their emotional response? Were some members of the community more open to my account than others? Were they open to the account, but did it strike them as novel? These are all questions an anthropologist asks.

As a communication scientists, I walk a middle ground between the controlled laboratory experiments of social psychology and the qualitative messiness of real world behavior. My collaborators and I manipulate websites carefully and observe average differences in behavior (e.g. selection of messages and time spent reading them). This step has both internal and external validity. However, we then use those differences in behavior to model observed changes in attitudes. We cannot say for certain that the behavior preceded the change in attitudes. Instead, attitudes may have shifted behavior. In our attempt to consider the wider implications of ecologically valid behavior, we lose some control.

Truly useful social science research is a balancing act.

For better or for worse, shaping the world in innovative ways requires an attention to both process and product, the navigation of multiple approaches, and a willingness to investigate and to challenge our most basic assumptions in a systematic way.

In the end, we all do the pragmatic thing. We all choose a side, take a stance, and act. However, we can do so humbly, aware of complexities, without blinders. We can do so boldly, honestly, and in a way that convinces others that we have selected the best response given what we know at the time.