Online research in philosophy

Subjectivity is essential to consciousness. But though subjectivity is necessary for consciousness it is not sufficient. In part one I derive a distinction between conscious awareness and unconscious subjectivity from a critique of Block’s (1995) distinction between access and phenomenal consciousness. In part two I contrast two historically influential models of unconscious thought: cognitive and psychoanalytic. The widely held cognitive model does not cover, as it should, the class of "for me" mental states that remain unconscious. In particular, personalist approaches to emotion require a theory of unconscious subjectivity to handle the case of unconscious emotion.

This commentary suggests that there are two distinct types of interacting cognitive processes. Conscious processes emerge from unconscious processes. The key problem of SOC is that it uses an overly narrow notion of the “cognitive unconscious” to show that the “cognitive unconscious” is not necessary. Yet, it has little to say about the roles of conscious and unconscious processes in general.

Unconscious thought theory (UTT) states that all information is taken into account and the attributes are weighted optimally resulting in better decisions in complex decision problems during unconscious thought. Very few studies have investigated the actual amount of information processed in the unconscious thought condition. We hypothesized that only a small subset of information might be considered during unconscious thought (like conscious thought). To test this possibility and to explore the way attribute information is selected and combined, we performed computer simulations on the datasets used by previous researchers. The simulations showed that considering a small subset (3-4) of attributes, yields results comparable to previous studies. There is no need to posit infinite capacity in the unconscious thought condition. The results also suggest that weight information is used for attribute selection that could potentially explain the difficulties in replicating the deliberation-without-attention effect.

Intuitive-automatic processes are crucial for making judgements and decisions. The fascinating complexity of these processes has attracted many decision researchers, prompting them to start investigating intuition empirically and to develop numerous models. Dual-process models assume a clear distinction between intuitive and deliberate processes but provide no further differentiation within both categories. We go beyond these models and argue that intuition is not a homogeneous concept, but a label used for different cognitive mechanisms. We suggest that these mechanisms have to be distinguished to allow for fruitful investigations of intuition. Specifically, we argue that researchers should concentrate on investigating the processes underlying intuition before making strong claims about its performance. We summarise current models for intuition and propose a categorisation according to the underlying cognitive processes: (a) associative intuition based on simple learning-retrieval processes, (b) matching intuition based on comparisons with prototypes/exemplars, (c) accumulative intuition based on automatic evidence accumulation, and (d) constructive intuition based on construction of mental representations. We discuss how this differentiation might help to clarify the relationship between affect and intuition and we derive a very general hypothesis as to when intuition will lead to good decisions and when it will go astray.

Intuitive-automatic processes are crucial for making judgements and decisions. The fascinating complexity of these processes has attracted many decision researchers, prompting them to start investigating intuition empirically and to develop numerous models. Dual-process models assume a clear distinction between intuitive and deliberate processes but provide no further differentiation within both categories. We go beyond these models and argue that intuition is not a homogeneous concept, but a label used for different cognitive mechanisms. We suggest that these mechanisms have to be distinguished to allow for fruitful investigations of intuition. Specifically, we argue that researchers should concentrate on investigating the processes underlying intuition before making strong claims about its performance. We summarise current models for intuition and propose a categorisation according to the underlying cognitive processes: (a) associative intuition based on simple learning-retrieval processes, (b) matching intuition based on comparisons with prototypes/exemplars, (c) accumulative intuition based on automatic evidence accumulation, and (d) constructive intuition based on construction of mental representations. We discuss how this differentiation might help to clarify the relationship between affect and intuition and we derive a very general hypothesis as to when intuition will lead to good decisions and when it will go astray.