: Psychological research indicates that people have a cognitive bias that leads them to misinterpret new information as supporting previously held hypotheses. We model such confirmatory bias in a symmetric model in which exactly one of two hypotheses is true. We show that the confirmatory bias induces overconfidence: Given any probabilistic assessment by an agent that one of the hypotheses is probably true, the appropriate beliefs should deem it less likely to be true. When the agent believes relatively weakly in a hypothesis after receiving extensive information, the hypothesis he believes in may be more likely to be wrong than right. If the confirmatory bias is strong enough, with positive probability the agent may eventually come to believe with near certainty in a false hypothesis even after receiving an infinite amount of information. Keywords: Confirmatory bias, overconfidence, bounded rationality. JEL Classification: A12, B49, D83 Acknowledgments: We thank Jimmy Chan, Erik Eyste...

The Human-Computer Interaction community has long been concerned with design. Terms such as `creativity' and `innovation' are frequently used when referring to the design process and in this paper we examine what creativity is with respect to design. Design is often a collaborative and, therefore, a social activity. We review the evolution of definitions of creativity, leading to our proposal of a unified definition, we present a theoretical account of why social creativity should in principle be more productive than individual creativity. We explain findings to the contrary in terms of three social influences on creativity and suggest that research in supporting design should focus on mitigating the effects of these social influences on the creativity of design teams.

The discovery of a creative solution occasionally corresponds to the sudden attainment of a mental insight. Our purpose is to formally describe this phenomenon and the cognitive mechanisms that lead to it. The approach is based on the replicability of just such an insight which underlies the solution to a well known puzzle: the nine-dot puzzle. The insight coincides with the realization that the problem can only be solved when a spurious constraint is removed. Two experimental results are reported: one on the nine-dot puzzle and the other on an architectural sketch design problem. The sketch design problem was structured with several restricting frames of reference to create a situation analogous to the nine-dot puzzle. Subjects ’ design behavior was analyzed to identify the mechanisms used in achieving the mental insights which allow designers to go beyond the implicit restrictions of these frames. A general model, called SMI-GI, of the mental insight based design and discovery process is described. This model foresees a computer system that can be used to simulate the mental insight mechanism and consequently lead to the systematic examination of this aspect of design creativity. 1. Creativity and the Sudden Mental Insight

Abstract. Can artificial systems be creative? Can they be designed to be creative on their own? And what are the requirements of such creative artificial systems? To be able to support humans who are expected to deliver creative solutions, or to automate part of their tasks, this paper presents a proposal for creativity requirements that provide a basis for designing creative artificial systems.

A better understanding of “human error” is needed to help overcome problems of people assuming they are to blame for their inability to use poorly designed technology. In order to investigate people's ability to recognize, and reflect on the causes of, particular types of errors, a problem solving environment was designed that allowed participants to verbally self-report erroneous and exploratory interactions. It was found that the pervasiveness of errors was recognizable but underlying cognitive and attentional causes of errors were not. Participants found that providing a causal account of device-specific errors during interaction was especially difficult. A striking feature of device-specific errors is that they involve actions that do not move an individual towards a goal state, but remain critical to performing a task correctly. Successfully identifying why an error has occurred requires an understanding of environmental cues and salience. Findings imply that HCI practitioners need to develop techniques to adjust the visual salience of cues, making it is possible to recognize and recover from error.

Abstract: Talents that selectively facilitate the acquisition of high levels of skill are said to be present in some children but not others. The evidence for this includes biological correlates of specific abilities, certain rare abilities in autistic savants, and the seemingly spontaneous emergence of exceptional abilities in young children, but there is also contrary evidence indicating an absence of early precursors of high skill levels. An analysis of positive and negative evidence and arguments suggests that differences in early experiences, preferences, opportunities, habits, training, and practice are the real determinants of excellence.

The Series provides compact, comprehensive and convenient surveys of what has been learned through research and practice as composition has emerged as an academic discipline over the last half century. Each volume is devoted to a single topic that has been of interest in rhetoric and composition in recent years, to synthesize and make available the sum and parts of what has been learned on that topic. These reference guides are designed to help deepen classroom practice by making available the collective wisdom of the field and will provide the basis for new research. The Series is intended to be of use to teachers at all levels of education, researchers and scholars of writing, graduate students learning about the field, and all who have interest in or responsibility for writing programs and the teaching of writing. Parlor Press and The WAC Clearinghouse are collaborating so that these books will be widely available through low-cost print editions and free digital distribution. The publishers and the Series editor are teachers and researchers of writing, committed to the principle that knowledge should freely circulate. We see the opportunities that new technologies have for further democratizing knowledge. And we see that to share the power of writing is to share the means for all to articulate their needs, interest, and learning into the great experiment of literacy.

Artificial intelligence Can a machine solve mathematical problems or prove theorems automatically? Are there computer programs which find solution strategies for puzzles? Can one reconstruct a city in three dimensional form, from a movie taken from an airplane? Can a machine read a mathematical formula written by hand on a piece of paper. What score can a computer reach in a standardized test like SAT? Can a machine pass the Turing test, can it behave in an online chat so that it can not be distinguished from an actual human? Here are some problems types in artificial intelligence. Most of them are purely mathematical: • problem solving: playing games, performing algorithms, solving puzzles

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Acknowledgements: Amongst several people who know they helped me, I want to thank especially Max Welling for our ongoing discussions and António Branco Vasco for his careful review. Correspondence concerning this article should be addressed to Hans Welling, Quinta do