This paper shows that recent arguments from group problem solving and task performance to emergent group level cognition that rest on the social parity and related principles are invalid or question begging. The paper shows that standard attributions of problem solving or task performance to groups require only multiple agents of the outcome, not a group agent over and above its members, whether or not any individual member of the group could have accomplished the task independently.

The resurgence of interest in collective behavior is in large part due to tools recently made available for conducting laboratory experiments on groups, statistical methods for analyzing large data sets reflecting social interactions, the rapid growth of a diverse variety of online self‐organized collectives, and computational modeling methods for understanding both universal and scenario‐specific social patterns. We consider case studies of collective behavior along four attributes: the primary motivation of individuals within the group, kinds of interactions among individuals, typical dynamics (...) that result from these interactions, and characteristic outcomes at the group level. With this framework, we compare the collective patterns of noninteracting decision makers, bee swarms, groups forming paths in physical and abstract spaces, sports teams, cooperation and competition for resource usage, and the spread and extension of innovations in an online community. Some critical issues surrounding collective behavior are then reviewed, including the questions of “Does group behavior always reduce to individual behavior?”“Is ‘group cognition’ possible?” and “What is the value of formal modeling for understanding group behavior?”. (shrink)

Computational modeling of sketch understanding is interesting both scientifically and for creating systems that interact with people more naturally. Scientifically, understanding sketches requires modeling aspects of visual processing, spatial representations, and conceptual knowledge in an integrated way. Software that can understand sketches is starting to be used in classrooms, and it could have a potentially revolutionary impact as the models and technologies become more advanced. This paper looks at one such effort, Sketch Worksheets, which have been used in multiple classroom (...) experiments already, with students ranging from elementary school to college. Sketch Worksheets are a software equivalent of pencil and paper worksheets commonly found in classrooms, but they provide on-the-spot feedback based on what students draw. They are built on the CogSketch platform, which provides qualitative visual and spatial representations and analogical processing based on computational models of human cognition. This paper explores three issues. First, we examine how research from cognitive science and artificial intelligence, combined with the constraints of creating new kinds of educational software, led to the representations and processing in CogSketch. Second, we examine how these capabilities have been used in Sketch Worksheets, drawing upon experiments with fifth-grade students in biology and college students in engineering design and in geoscience. Finally, we examine some open issues in sketch understanding that need to be addressed to better model high-level aspects of vision, and for sketch understanding systems to reach their full potential for supporting education. (shrink)

We discuss the important, but greatly under-researched, topic of the social aspects of human wayfinding during navigation. Wayfinding represents the planning and decision-making component of navigation and is arguably among the most common, real-world domains of both individual and group-level decision making. We highlight the myriad ways that wayfinding by people is not a solitary psychological process but is influenced by the actions of other people, even by their mere presence. We also present a novel and comprehensive framework for classifying (...) wayfinding in complex environments that incorporates the influence of other people. This classification builds upon the premises of previous wayfinding taxonomies and is further structured into four parts based upon (1) the nature of the interaction between the actors and (2) the time frame in which the interaction takes place. We highlight gaps in our current understanding of social wayfinding and outline future research opportunities. (shrink)

Cognition in work teams has been predominantly understood and explained in terms of shared cognition with a focus on the similarity of static knowledge structures across individual team members. Inspired by the current zeitgeist in cognitive science, as well as by empirical data and pragmatic concerns, we offer an alternative theory of team cognition. Interactive Team Cognition (ITC) theory posits that (1) team cognition is an activity, not a property or a product; (2) team cognition should be measured and studied (...) at the team level; and (3) team cognition is inextricably tied to context. There are implications of ITC for theory building, modeling, measurement, and applications that make teams more effective performers. (shrink)

When animals share decisions with others, they pool personal information, offset individual errors and, thereby, increase decision accuracy. This is termed ‘swarm intelligence.’ But what if those decisions involve conflicts of interest between individual decision-makers? Should animals share decisions with individuals whose goals are different from, and partially in conflict with, their own? A group decision model developed by Larissa Conradt and colleagues finds that, contrary to intuition, conflicting goals often increase both decision accuracy and the individual gains derived from (...) shared decisions. Thus, conflicts of interest, far from hampering effective decision making, can actually improve decision outcomes for all stakeholders, as long as they also have some goals in common. By contrast, conflict-free decisions shared by animals which all have the same goals are often surprisingly poor. (shrink)

The central point is that the consciousness is an advanced information channel. Consciousness is not the seat of the self or free will. The action is in the sub-consciousness brain systems. Consciousness is a "just so story teller" consciousness collects and correlates scenes into sequential presentations. The function of consciousness is to provide a new information channel between other brain systems. The pre-consciousness communication between brain systems evolved and is limited by the possible pathways, these pathways did not provide the (...) possibility of a historical correlation or integration with a high level pattern of cause and effect at a significantly abstract but focused level. Consciousness provides this pathway. Consciousness provides this pathway by providing a method for the brain to take its existing expressions both visual and auditory and re-create a time line of experiences and conversations that are then re-presented to the rest of the brain through the existing sensory channels at the level of the brain. This is not a feedback loop in the simple sense, but a feedback loop of a rarified and extremely intensely processed, correlated and organized remembering. This allows the brains different functional entities to get information that it could not get from the evolved pre-consciousness internal pathways. These presentation are used by the other brain systems in a manner similar to any sensory input. This perspective would place Consciousness in the position of a cyber reality generator that feeds back to the rest of the brain. (shrink)