David Weinberger Keynote: Too Big to Know #KMWorld

David Weinberger is Senior Researcher at Harvard’s Berkman Center for Internet & Society, author of Too Big to Know, and columnist at KMWorld.

[These are my notes from the KMWorld 2012 Conference. Since I’m publishing them as soon as possible after the end of a session, they may contain the occasional typographical or grammatical error. Please excuse those. To the extent I’ve made any editorial comments, I’ve shown those in brackets.]

NOTES:

• What Knowledge Has Been. From the beginning, knowledge has been about filtering signal from noise; it has been that which is settled (if people are still arguing about it, it’s not yet knowledge); it is settled (if we don’t know its place, it’s not knowledge); knowledge has been a system of stopping points (you stop your search for knowledge after you ask a certified “expert” who has mastered a “brain-sized chunk of the world” and asnwers your question). In addition, there have been several limitations imposed on knowledge by its physical medium: it must be permanent and preserved in permanent physical forms (e.g., books, newspapers); knowledge can be physically placed in only one place, therefore, it can’t be put in a different places at the same time; knowledge is in a final form (the author must convey the extent of her expertise on a specific topic within the covers of a single book — another stopping point).
• The New Knowledge. New media have unmoored knowledge and allowed it to expand beyond it old physical limitations. We’ve moved from knowledge contained in single physical objects to knowledge found in networks. For example, instead of placing scientific knowledge in a peer-reviewed journals, it can now be placed in a wide open network (arXiv.org) which can be linked into and out out of.
• Lessons from Science. (1)Peer review, for all of its goodness, does not scale. It has it place but is not robust enough to let science and knowledge get big enough fast enough. (2) Networks flood the ecosystem. (3) Knowledge contains differences. (4) At our best, we are learning how to deal with our differences.
• Lessons from Developers. When developers run into a problem they can’t solve, they post the question on a shared site like stack overflow where others can respond. Then the answer can be posted on another shared site like github. Lessons: (1) learning together requires humility and generosity. (2) One of the powers of iteration is that is scalable. (3) Public learning allows every interested person to learn together. In this way, every act of education leaves a track that everyone else can follow so they can become smarter too.
• Library of Congress Photo Collection. The Library of Congress posted collections of photos on Flickr.com so that the public could tag it with all relevant tags. The public jumped in enthusiastically and filled in the 75 available tags quickly. Some of these tags are factual (the date of the photo), aesthetic (“Red”) and on its face, wrong (e.g., tagging a photo of a woman at work as “Rosie the Riveter” even though it clearly is not a photo about Rosie). This range of tags creates messiness, which allows for a wider range of meaning and connection that was possible with the cleaner and disciplined approach provided by “experts.”
• The Echo Chamber Problem. When you give people lots of media choices, they tend to go towards choices that “”echo” their own views, thereby leading to confirmation bias. In addition, there is a concern that this tends to make us more extreme in our views…leading to “the death of democracy.” Weinberger mentions Reddit in which people can post and comment, all of which can be voted up or down by the readers. At its best, it leads to wonderful conversations that surface a variety of views and insights. (Weinberger points to the IAMA — “I am a…” conversation threads where there have been several open, respectful, occasionally humorous, often enlightening conversations.) Even though Reddit welcomes conversation among people with differences, the reality is that most people who participate share more than they disagree — at least with respect to how to interact with each other.
• How to Make Rooms/Networks Smarter. (1) Appreciate the power of difference. If we can maximize our networks for “fruitful disagreement,” we open the possibility of getting closer to “truth.” (2) Public learning allows more people to get smarter. (3) Embrace mess and inclusion — while we might like the clarity of cleanly organized systems, we miss a lot when we don’t permit messiness and inclusion. (4) Open a damn window! Rooms get stuffy unless you let new information/perspectives/air into the room.
• What are the characteristics of Networks and Knowledge?. Overwhelming, unsettled, unresolved, messy, deeply & loosely-connected, held together by our own interests. These are also the characteristics of a searcher of knowledge.
• What Do We Know?. What we have in common is not a single knowledge about which we agree, but a single world that we share and can disagree.