Abstract
This study addresses a general concern, a specific concern, and a synthesis between them. The general concern is how to foster human collective intelligence, in this work approached from a human-technological angle. The specific concern is how to foster human fluency in formal languages for automated deduction. Human collective intelligence
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occurs, loosely speaking, when the intelligence of a group of people is greater than the sum of the intelligence of the individuals of that group. Important motivations to foster human collective intelligence are to help people (1) deal better with problems and (2) become better, more fluent and more refined at what they are already good at. This study covers a large class of facets related to fostering collective intelligence with an abstract overarching approach, and then works out a limited, yet carefully selected set of facets in detail. The overarching approach (the Orcoba-Approach) facilitates human individuals or collectives to acquire or improve a given capability. The core of the approach consists of expressing the capability in a permanent record that enables the targeted capability to be, at least partially reproduced and examined. Such a record contains both a description of relevant human capabilities and activities, and specifications of complementary artefacts used. The approach facilitates people, or other actors, to share, add and adapt records, and does so guided by the differences in performance teams achieve with them. It does so in a way inspired by biological evolution, accelerating the improvement of the best records. The concern for fostering human fluency in formal languages for automated deduction (briefly: formal fluency) is inspired by the following. Since the second half of the 20th century much work has been done on developing and improving the application of computers to boost our capability to reason over our collective knowledge. One major branch of development involves automated deduction: knowledge that is represented in a formal language for automated deduction enable special computer programs to automatically produce knowledge-representations that are deducible from the given knowledge. This technique enables people to extend works of others to an unprecedented degree, contributing to the general concern of this work to increase human collective intelligence. Although automated deduction is nowadays widely applied for the purpose just given, we are only scratching the surface of its full potential. A way to contribute to the relation of this full potential is to foster more people reaching formal fluency. The latter is the specific concern of this study. This work’s contribution to fostering formal fluency consists of subjecting it to the specialised approaches to foster human collective intelligence developed in the first part of the work. This work presents both how to tailor these approaches to formal fluency and the lessons learnt about favourable elements for a record for formal fluency. The most sophisticated fruit of this work consists of the design and partial implementation of the serious game developed for this purpose, SWiFT.
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