John Seely Brown Keynote: Knowledge Sharing in our Exponential World #KMWorld

KMWlogo_Stacked_Session Description: People & Tech — the Future of Knowledge Sharing

People are at the core of knowledge-sharing—the key to high functioning organizations. In John Seely Brown’s words, “We participate, therefore we are.” New and emerging technology can only enhance learning, sharing, and decision making to create successful organizations. Join our inspiring and knowledgeable speaker as he shares his view of the future of people and tech working together to share knowledge and create winning organizations.

Speaker: John Seely Brown, Director, Palo Alto Research Center

[These are my notes from the KMWorld 2017 Conference. I’m publishing them as soon as possible after the end of a session, so 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:

  • We live in an Exponential World.  We are experiencing an exponential curve along which roughly every 18 months we have something new we have to think about. And that new thing forces us to change our view of our current best practices.
  • Whitewater Rafting. Whitewater rafting is a good metaphor for this age. In this period of rapid shifts (every 18 months), we are constantly creating tacit knowledge but do not have enough time to distill that knowledge and make it explicit. This means that we have to acquire new skills rapidly. However, the half-life of our skills is about five years. So we can never rest.
  • Scalable Learning. In this age of exponential change, we don’t merely need scalable learning. We need scalable UNLEARNING. This is the ability to forget our old tacit knowledge (and the associated beliefs) in order to replace it with newer, more correct knowledge and skills. The challenge is that we are caught in our own Competency Trap: sticking with what we know/do best — even in the face of obvious and unavoidable change.
  • Unlearning is hard. Unlearning depends on being able to find and expunge our own tacit knowledge and beliefs. The challenge is that sometimes we are completely unaware of those beliefs — we don’t realize we have them.
  • Start by Getting out of your Comfort Zone. Jack Hidary has a helpful protocol: every year, he takes a few days to learn something completely outside his area of expertise: (1) Attend a conference and sit and listen to every session. (2) On day 2, do not attend any conference session. Instead, sit by the coffee pots and listen to how subject matter experts talk about the subject. They will be “shamanistic,” using lots of jargon. Notice what they take for granted, notice what they miss. (As an outsider and novice, you will see things they do not see.) (3) On day 3, go outside and think about what you have heard and observed. Then determine what is actionable and worth pursuing. Using this approach, he attended an energy conference, did a quick deep dive into this area of expertise, realized we needed to switch to hybrids. He took action by convincing New York City Mayor Michael Bloomberg to convert some of its taxi fleet to hybrids. And he convinced President Obama to launch the Cash for Clunkers program.
  • Orchestrating Serendipity:
    • Choose serendipity environments
    • Develop Serendipity practices
    • Enhance Serendipity preparedness
  • Reverse Mentorship. Ths is a very practical and effective way to learn new skills
  • Institutional Innovations. How do we help our organizations think differently — not just use new tools?
    • Hackamonth — This is silo busting at Facebook. It’s a hackathon that lasts for 30 days to crack a problem. They do solve a lot of problems but, more importantly, they are building deeper communities of practice across the whole company.
    • Skadden Arps — they have implemented bi-directional learning opportunities by pairing young associates with senior partners. This work is facilitated: Peter Lesser (Skadden’s CEO) is the convener/moderator/translator.
  • New tools for empowering the edge.
    • cloud computing enables the edge to access all the power it needs without core approval
    • cloud enables nearly infinite scalability and reach, and enables new business models
    • social media amplifies engagement with external partners, customers and others in the core
    • bog data allows you to interpret weak signals
    • blockchain enables smart contracts with no overhead
  • Listening Tools. We also need tools that help us listen to each other better, interact with each other better.
  • Reality Mining. Sandy Pentland studies how to build great teams. He has learned that “patterns of communication are the most important predictor of a team’s success.” Just by listening to the intonation of the communications, the amount of information actually shared, the amount over-talk, Pentland’s group could separate the high-performing teams from the low-performing team.
  • Amplifying DevOps. DevOps creates a great deal of “digital dust.” Can we collect all these communications (across email, Slack, Jira, etc.) and mine them to improve our understanding? How would this then change the way we work?
  • What we Need for the Big Shift. The Big Shift calls for more than just scalable learning and unlearning. It calls for a new ontology  = a new way of being. This means blending in ourselves Homo Sapiens (man who thinks), Homo Faber (man who thinks) and Homo Ludens (man who plays). This playing isn’t just about recreation. It’s about “playing with” ideas and challenges in order to reach a breakthrough moment, an epiphany. Therefore, we need to learn how to do this type of play:
    • probing and pushing the boundaries
    • how to invent within a space of rules
    • deep tinkering
    • how we interrogate context is a form of “play” — like a detective who makes sense of the clues she reads in her environment.
  • Imagination is the Key. It is the way that we play, it is the way that we fuse or find an internal blend of knowing, making, and playing.
  • Our Symbiotic Relationship. When Big Blue defeated Gary Kasparov some thought it was the end of the ascendancy of humans. However, it also signaled an opportunity. Zack Stephens nd Steven Cramton were winners of the Freestyle Chess Tournament, which effectively is “a race with the machine” that is “a generative dance between us and the machine.” We need to look for opportunities for more generative dances.
  • What about IA? IA is Intelligent Augmentation. We can use intelligent augmentation to provide imagination (as the binding agent) with new properties.
    • Homo Faber + IA = digital assistants
    • Homo Ludens + IA = freestyle chess, Go masters
  • Networked Imagination: We need to create in each of us a product blend of human & machine. Then we need to figure out how to create distributed communities of practice that function as networked imagination.
  • CAUTION: “The real difficulty in changing any enterprise lies not in developing new ideas, but in escaping from the old ones. (John Maynard Keynes)
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John Seely Brown: The Entrepreneurial Learner#KMWorld

John Seely Brown, Chief of Confusion, Co-Chair of Deloitte’s Center for the Edge.

[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:

  • Context. Infrastructure over the last three centuries has followed a predictable S-curve: long periods of stability (approximately 50 years) followed by a period of intense instability, and then more stability. Now, we are looking at an indefinite period of change in which we should experience exponential growth in computation. This is our BIG Shift.
  • What’s happening in our BIG Shift?. In the old world, we could expect our knowledge to last over a work life of 50-60 years. Now, our knowledge has a half-life of five years. With knowledge changing this quickly, we can’t focus on knowledge stocks anymore; we have to focus on knowledge flows. With respect to infrastructure, we no longer have those 50-year S-curves. Instead, we are experiences a rapid set of S-curves of approximately one year each.
  • The Skadden Example. Peter Lesser, CTO of Skadden, noticed that incoming associates were solving training problems by posting queries/status updates via Twitter. He realized that the firm could learn from this example, so he set up a reverse mentoring program to understand better how to harness this behavior.
  • Learning Exemplar: World of WarCraft. This online game has two kinds of learning spaces. The first is the in-game learning: a kind of “collective indwelling” with constant experimentation and tinkering. This is a great way to share tacit knowledge. This game is too completed to play without specific data and personalized dashboards. Therefore, individual players set up personal dashboards that track the data of most interest to that individual, with a view to improving personal performance. The players also participate in after action peer-brased reviews that results in exponential learning. (This has been documented.) “Out-of-game” learning is more about creating a knowledge ecology that helps players gain and create knowledge faster. This learning happens daily within “guilds” that analyze the performance of the prior day and then provide recommendations for the next day’s game. They use videos, wikis, blogs, databases and various forums. This is a great way to filter information and create feedback loops rapidly.
  • Creating a Pull Platform: SAP. SAP created a software developer network to capture the insights of users. This provided an accelerated means of improving the Netweaver product.They created a new “pull platform” in which participants connect, innovate and reflect. The more individuals participate (posing smart questions, providing useful answers), the better they are known and, in some cases, the more individuals receive new career opportunities. Because of the strenght of the this community, the average time it takes to receive an answer to a question is 17 minutes. That answer usually can be validated by the next day.
  • Social Bookmarking: Mitre Corporation. Rather than forcing explicit knowledge (e.g., creating profiles, filling out expertise, etc.), they decided to try to capture information on the fly. The method they used was Social Bookmarking: as individuals found useful materials online and bookmarked it with a brief explanation, their system was able to builds links between people interested in similar topics. The next step could be to build gamification tools into this system to increase participation.
  • Looking closely at how work REALLY gets done: Xerox. The $200 million problem was rethinking how Xerox’s technology representatives work. When they examined how the work really happened, they discovered that trouble-shooting wasn’t simply about pulling out the heavy technical manual and looking up the answer. Rather, a tech rep would call up another tech rep who would come over to help. Together they would “create a dance around the machine” in which they conducted specific tests, analyzed the results and told stories to each regarding the last time they saw results like this. In other words, they worked by creating stories as they recovered prior experience, added the new data and that combination became the new story. This pattern of working led to the “Eureka” system, which gathered these stories and then arranged for them to be reviewed and validated. As more of a person’s stories were validated, that person (and the reviewer who validated the story) enhance their reputation within the community of tech reps. This social credibility proved valuable.
  • Intimate with Scale: Google Hangouts. This tool allows you to create a discussion group of up to 10 participants who converse via a video call. However, they have provided “legitimate peripheral participation” by allowing an unlimited number of people in your circles to listen into the hangout without being one of the 10 initial participants. (It’s like overhearning a great conversation.)
  • Supporting Distributed Work. Here’s the big challenge: much of the real work happens in the emergent, so how do we really support distributed work? We should create immediate ad hoc social groups that can solve problems in process immediately. As these exception conditions emerge, are resolved and documented, you have a remarkable knowledge process resulting in a rich knowledge base.
  • Takeaways. (1) in a world of constantly changing contexts, best practices don’t travel very well. (2) As contexts change, we need to move past stories (which explain a specific event) to narratives (which create a framework for moving us to action, perhaps in a new direction). (3) there are important shifts occurring: knowing what has moved to knowing what and where; making things moves to making things and contexts (e.g., remix); (4) in sense-making, we move from playing to reframing; in media, we move from storytelling to transmedia (e.g., how a story jumps from one medium to another — this has huge implications for corporate branding). (5) Identity Shift is the biggest shift of all. We’re moving from a sense of “I am what I wear/own/control” to “I am what I create, share and others build on.” How do I put something into play so others build on it? When you figure this out, you understand agency and impact.
  • Creation Spaces. Look below the radar screen. Interesting things are happening in cities within new “maker spaces” and “hacker spaces.” They are building new things that could change our economy.

 

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