6. Novel claims and conjectured model of steering cognition
The evidence from CAS-based research supports the following claims:
6.1. A heuristic kind of cognition, which I will call 'steering cognition' is proposed. Steering cognition functions not as a parallel processing system to algorithmic cognition but as a series processing system. Data is proposed to handled by steering cognition prior to processing algorithmically.
6.2. A model of steering cognition as a neural API (application programming interface) is conjectured in which heuristic cognition serves as a data-integrator between the external data set (the world) and the internal data set (memory). An API is a software mechanism used in web development to sit between two server-based applications (such as Facebook and Instagram). The API serves to bridge the different data-binding and coding structures of the two applications by converting the data delivered by one application one structure into a structure receivable by the other. In the analogy, the neural API functions to turn round and manipulate data of varied structures and forms such that it can be appropriately located within the data structure of internal memory.
Figure 1.1 Figure 1.2
6.3. Algorithmic cognition (referred to in Figure 2 as Analytical cognition) is the computation of data already located in the internal data set. Steering cognition (I) integrates algorithmic processing with embodied processing (sensory-motor control of our bodies, eyes, ears etc…)
Figure 2. Imagination (I) places a conjectured central role in steering cognition; it biases attention, via embodied cognition to detect and retrieve varied data from the environment. This data is processed by the machinery of the imagination to ensure that it located correctly in the epistemic categories for algorithmic (labelled analytical) processing.
6.4. Steering cognition centrally involves the function of the imagination, which serves as a plastic data manipulator and simulator in working memory. Novel representations of data are initiated within the imagination prior to being filed, located, within long term memory.
6.5. The imagination integrates with other circuits in the executive function system, which provide a mechanism for self-regulation, effortful control, attentional bias, self-other thinking and metacognition.
6.6. The imagination serves to connect algorithmic cognition with affective, or implicit memories, stored in closely located cortical regions. As such it is conjectured to be at the centre of a distributed system for integrating cognitive-affective engagement with the environment. Imagination may be involved in early-stage concept formation as well as novel abstraction and concept-association.
6.7. Steering cognition enables human cognition in a real world of epistemically varied, novel data. The ‘state’ of a person’s steering cognition (measured by the proxy CAS) can be said to give them heuristic momentum; an up and running set of attentional biases which, unless explicitly checked and adjusted, will drive cognition in a certain direction.
6.8. Walker showed that distress causes students to less closely regulate their steering cognition- it increases bias polarity. By polarising biasing of their steering cognition, accuracy is sacrificed for data processing speed and momentum- conjectured to be an evolutionary response to threat.
6.9. In one longitudinal study over 12 months, Walker found that adults consolidated prior steering cognition biases despite repeated opportunities to shift them in the face of new stimuli. Walker also found a match between the adult’s steering cognition bias and their perception of the biased state of other people around this; this suggested a kind of projection was occurring, supporting a view that fixed cognitive steering bias involves a kind of attention blindness and representation bias identified by heuristics and biases studies.
6.10. Walker has evidenced (with assessments of over 2,700 individuals between the ages of 8 and 50) that heuristic biases become more stable with age. Walker claims that bias configurations can be associated with distinct personality patterns and different professional roles, suggesting that they become manifested as habitual, recognisable and functional traits in adults.
7. Explanations of previous evidence
The neural API model, supported by our data, offers alternative accounts of the robust evidences upon which the dual mind model has been built. For example:
7.1. Kahneman’s evidence of heuristic bias: Contra Kahneman, the cognitive steering data has indicated that heuristic bias is not always negative. Rather bias is the essential mechanism by which an individual steers their cognition to cope with an epistemically varied landscape. The ability to adjust bias to optimise the data processing of the epistemic task at hand is a previously unidentified contributor to academic outcome.
7.2. Some of Kahneman’s heuristic bias errors can be explained by a notion of heuristic momentum; bias continuing in an epistemic direction, unable to stop or adjust to unforeseen tasks. The well-evidenced ‘fast speed’ of heuristic cognition is explained as a state of such unreflected cognitive steering: when all the cognitive steering cogs are aligned in a pre-set pattern then data is processed through them very fast; this leads to cognitive errors when unexpected environmental cues have to be negotiated (Figure 3.1).
7.3. Automaticity is the same phenomenon: in repetitive tasks, cognitive steering biases become fixed in a certain configuration, which means no effort needs to be maintained in adjusting it to search for, and process, varied and different kinds of data. As such, data is retrieved and passed down to algorithmic cognition very fast. This is an accurate process when the data task is repetitive and consistent; however, it is inaccurate if the brain has to process a difficult or trap question.
7.4. This has previously been misinterpreted as a second parallel processing system (system 1) which is always fast, automatic and makes errors. In Walker’s model, cognitive steering is not necessarily fast or automatic. It can become fast and automatic if the settings of the cogs get aligned such that it only has to search and locate a single kind of data (Figure 3.1). In that circumstance, steering cognition becomes like an open channel through which data passes directly through, rather than being turned around, manipulated and simulated- a time consuming, effortful process.
7.5. What has previously been described as slow and effortful system 2 is in fact,steering cognition whirring away coping with varied kinds of data (3.2). When instructed to do so, a person can consciously engage their steering cognition, accurately process the external data, locating it into the right place in the memory for algorithmic processing. An individual may still, after this slow, conscious and effortful process make computational errors if they have poor algorithmic cognition. The speed of algorithmic cognition itself is determined by other factors such as working memory and prior knowledge.
7.6. Thus, steering cognition is neither fast or slow; it is fast AND slow. It is a regulated processor which is differentially engaged depending on the degree of complexity of the epistemic landscape the learner is engaging in at the time. In circumstances where external data is simple, of one kind, or the learner presumes it is, heuristic momentum is conjectured to maintain a set of up and running cognitive biases which will automatise the attention of the learner. Previous priming effect evidences can be explained by the phenomenon of heuristic momentum: priming effect works (often affectively or associatively) by conditioning the cognitive steering system to a specific bias state, which results in attentional blindness.
7.7. The failure of past experiments to detect this fast and slow function of heuristic cognition may be due the fact that experiments had been done with adults rather than children. Adults exhibit ‘fast heuristic processing’ because their heuristic cogs have become fixed in a static configuration through habituation iterated over their childhood. Children and adolescents do not yet exhibit such fixed patterns and therefore potentially exhibit heuristic adjustment, both fast (fixed) and slow (data manipulating/integrating).
7.8. Finally, previous studies were conducted upon populations of individuals exposed to a single priming effect; Walker’s studies investigated the response of the same individual to multiple priming effects consecutively. Walker was able to evidence, therefore, the adjustment of heuristic biases between different priming effects, which had not previously been observed.
Figure 3.2 Heuristic labour occurs when the heuristic system is fully engaged to process multiple kinds of epistemically-varied data. This results in slower, more effortful attention and stronger retention in long term memory.
Figure 3.1. Heuristic biasing or momentum results in attentional blindness and fast processing- collecting only certain kinds of the available data and passing it without manipulation and simulation to analytical processing.