Beth Kanter (currently a visiting scholar at the Packard Foundation), recently analyzed the list of “foundations that tweet” on the Philanthropy411 blog. Beth gives a really interesting breakdown of the various ways the foundations are using Twitter as well as takes a look at the “profiles” the use.
She breaks the profiles into four types:
- Pure Foundation Brand
- Foundation with Personality
- Employee with Foundation Association
- Pure Personal Account
Personally, I generally think options 1 and 4 are boring. Profile 1 types tend to be versions of press release distributors. Profile 4 types tend to tweet about their cats, what happen on a TV show last night and other personal conversation that doesn’t interest me (I’m not referring to the profiles that Beth uses as examples, just making a generalization).
But Profile 2 and 3 types are really interesting. These are either foundation branded Twitter profiles that clearly are authored by a real person writing like a normal human does or individual branded Twitter profiles where the person’s connection to a foundation is clearly noted.
I think the lesson to be drawn here is that in the search for how best to share knowledge, the key thing is to put humans at the center. Knowledge is not some sort of physical element that we can stack in a room somewhere and index easily. Knowledge is a concept that is rooted in the very fact that we are human.
Information we can stick into databases and take humans out of the equation. Knowledge on the other hand (or dare we say wisdom?) cannot be separated from the human element in which it is rooted.
As we strive to build a more effective philanthropy, to share knowledge and support what works, let’s not become disconnected from the human element that drives philanthropy. Any hope we have to build a philanthropic field that is high performing and high impact must be built on a framework that embraces our humanity rather than tries to overcome it.
It is a messy world out there. But humans are uniquely good at organizing, contextualizing and identifying patterns in messy information landscapes.