Abstract
Despite the advancement of artificial intelligence there are still some problems which are beyond current computing capabilities including some high dimensional pattern recognition tasks and those that require creativity or intuition. These problems are often delegated to interested participants through carefully engineered human computation systems, crowdsourcing systems or collective intelligence systems. However, all these systems require a fore-planned platform to coordinate the production of the intellectual product such as a vote or a statement from the human participants. Outside of these platforms, however, there is a vast amount of independently created intellectual products, for example in tweets, YouTube comments, online articles, internal company reports and minutes. These are largely untapped due to a lack of awareness of the potential that exists within them and the inaptness of the tools and techniques that would be required exploit the data. In this paper we propose Post-Hoc Collective Intelligence (PHCI) as a novel research and argue that it has important distinctions from the closely related research areas. In so doing we present an informed argument for the PHCI framework having 5 components which give structure to implementation and research pursuits.
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Notes
- 1.
The first stage of the decision making process is generally referred to as “intelligence” but it is generally accepted that in that context it refers to process of gathering information about the environment and the problem. Thus, to avoid confusion with the use of “intelligence” in this work we refer to this step as “research”.
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Jones, D.J., Mansingh, G. (2018). An Argument for Post-Hoc Collective Intelligence. In: Chatterjee, S., Dutta, K., Sundarraj, R. (eds) Designing for a Digital and Globalized World. DESRIST 2018. Lecture Notes in Computer Science(), vol 10844. Springer, Cham. https://doi.org/10.1007/978-3-319-91800-6_16
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