Human dynamics: computation for organizations

Alex Pentland

doi:10.1016/j.patrec.2004.08.012

Human dynamics: computation for organizations

2005-03-01

35

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AI

DOI：10.1016/j.patrec.2004.08.012

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The human dynamics group at the MIT Media Laboratory proposes that active pattern analysis of face-to-face interactions within the workplace can radically improve the functioning of the organization. There are several different types of information inherent in such conversations: interaction features, participants, context, and content. By aggregating this information, high-potential collaborations and expertise within the organization can be identified, and information efficiently distributed. Examples of using wearable machine perception to characterize face-to-face interactions and using the results to initiate productive connections are described, and privacy concerns are addressed. (C) 2004 Elsevier B.V. All rights reserved.

Human dynamics: computation for organizations

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