So — while it might indeed be true that 80% of a typical white-collar work day is spent in ’spoken’ conversations —how would you feel about wearing and/or utilizing commonplace ‘wearable technology’ to help ‘reality mine’ yourreal-world interactions? Writing for MIT’s Technology Review, Alex Pentland describes how the MIT Media Lab’s HumanDesign research group is doing just that.
This research dwells at an intersection where I can often be found lingering — experiencing the energy and thoughtbeing expended, expanded, and expounded upon in the cross-over area between social, information, and knowledgenetworking research. The tools and approaches that are being experimented with in the Human Design Lab evoke images ofsome scary sci fi however — mining and measuring our’ prosody‘ [n 1: the patterns of stress andintonation in a language [syn: inflection] 2: a system of versification [syn: poetic rhythm, rhythmic pattern] 3: thestudy of poetic meter and the art of versification.]
Two of the Lab approachescovered in this Reality Mining TheOrganization article are:
Expert and Collaborator Locator. With speech recognition technology, we can generate profiles of individuals based on the words they use in conversations. These profiles help identify the people within an organization who have particular expertise. By querying profiles—perhaps by picking people who socialize during lunch or group activities—a manager can form a team of employees with harmonious social behavior and skills. This technology can also minimize redundant work by helping managers identify clusters of people who work on similar projects within the larger organization.
Collaboration Tools. Although standard data-mining operations can analyze existing corporate information, the results reflect a limited and static view of an organization’s human and social capital. Augmenting knowledge management with information gathered by unobtrusive wearable sensors that measure such qualities as tone of voice, or “prosody,” and body language could be enormously helpful to organizational collaboration. The results can help managers understand who is working with whom and infer the relationships between colleagues. A database of employee profiles that responds to changes in e-mail and oral-conversation behavior and content can lend insight into the sources of an organization’s in-house expertise. Querying this database for interests, skills, or even recently used vocabulary would be an efficient way to find people who might work well together.
Mr. Pentland’s article wraps with some lip service to privacy protection and cultural transparency — in theworkplace these issues are enormous. Knowledge Management has stumbled flat onto its posterior over and over again —around these identical issues of culture, trust, privacy, and what we often refer to as ‘transparency.’ In an academicsetting these ‘innovations’ sound fascinating. In a military setting these ‘interactional analytics’ can be mandated.In a commercial setting these ’serendipitous studies of swarming susurrant syllables’ are more difficult to imagine.
