We are always learning. Whether we search for the answer to a question we have or an error we’re having in a piece of code, that practice of what to search for and sifting through the results is learning. Some of the time the answer might be obvious, we solve our current problem and move on. Other times, we have to look in 2 or three different places, synthesize the answer, and apply it. What are you doing to capture that type of learning? How do you share it with others, including your future self?

The above is the outline for the talk I gave as part of the Lighthouse Labs Speaker Series on August 14, 2004.

While the context of my talk was about building a personal information and knowledge practice, I firmly believe in the same concepts for building knowledge within a company. I saw this article today by Tomasz Tunguz on The Most Important Investment a Startup Can Make talking about this company level investment in education:

As a startup grows and scales, it’s easy to forget about deepening employee education. But the enrichment both in knowledge and network building is invaluable. Furthermore, it’s a terrific investment in the business’ competitive advantage, its people.

Thanks to the Lighthouse Labs crew for having me, and to Hans Peter Meyer for live tweeting some of the things I said.

Below is the outline that I spoke from, which won’t necessarily make a ton of sense without me speaking to it, but it gives me something to link to.

Ancient History§

• 2002, started blogging
• 2004, I moved back to Vancouver
  • Flickr launched!
• 2005, Northern Voice Blogging Conference - first conference to use tags / have an official tag
• Launched Bryght, first commercial Drupal company, on 80 leased servers, running Xen VMs
  • Amazon AWS cloud launched in 2006

More history§

• Skype launched August 2003
• Most people still using AOL, MSN Messenger (until 2005 —> Windows Live Messenger)
• CVS was being replaced by SVN
  • 2010 - drupal.org moves from CVS —> git
• Twitter & Jaiku launched in 2006
• 2007 when Chris Messina first proposed the hashtag
• IRC will never die! (except, Slack is built on top of it and is awesome)

10,000 hours§

• Malcolm Gladwell reference
• What does it mean to be an expert at “the web”?
• What does “web literacy” mean?
• You all are learning code literacy. Maybe programming is a new type of literacy?
  • FTP, servers, HTML, CSS, DNS, SSH, version control, command line, etc. etc. etc.

How are you capturing knowledge?§

• Notes: for yourself, privately, as reminders, to get it stuck in your brain
• Reflection: reviewing notes, acting on them, thinking about what you’ve learned on a daily, weekly basis
• Self-study: what sources of information are you looking at to get better at what you’re currently interested in?
• Sharing: fully capture that knowledge by teaching it to others - share it!

Link blogging§

• Delicious is ancient history. Mag.nol.ia was in part built locally here in Vancouver, and lost everyone’s bookmarks.
• Evernote - has a web clipper, great for
• Postachio <— this is an investment, but it is also awesome. You hook it up to your Evernote account and can then publish a blog directly from Evernote.
• Tumblr - not just for cat blogs, has a great bookmarklet for capturing links
• Pinboard - Maciej runs this "Social bookmarking for Introverts" service. He is an excellent writer and you should read this thing he wrote about the Internet. It’s inspiring and worrying.

Link Blogging II§

• It’s easy to get started - just link blog instead of bookmarking
• You’re doing it for future self, not for an audience
• You have all this stuff on a website that you can get to from any computer
• Other people can leave comments and tell you you’re wrong
• You can use Google to search your past brain

I wrote about how I use Postachio for link blogging.

Tags§

• What do you care about right now?
• How many things would you tag with “Ruby” or “Rails”, how many would you tag with “Git”, how many would you tag with “product”, or “startup”?
• You can then point to a list of articles about “Ruby” or “product”. Here’s an example of all of my collected "product consulting" articles links.bmannconsulting.com/tag/product-consulting
• You can look back and see what you’re tagging stuff with. What are you interested in over time? How does those interests change.

We had a good discussion with people who said - "tags are BS!". Someone else pointed out that adding tags was like extra "votes" for those topics / terms with the text.

I really really wish I had my own text / knowledge / search clustering algorithm that I could run on my own content!

Boris’ Current Tags§

• Product, Product Consulting, Future of Work
• Tools
• Full Stack, angel investing, AngelList, syndicates, foundry, venture studio, convertible debt, equity, bootstrapping
• Vancouver, Canada, weareyvr, ecosystem
• Ruby, OS X, Heroku, S3, Jekyll, Harp, brew, git
• Past: Drupal, PHP, SVN, personal publishing, Barcamp, Northern Voice, Bootup Labs (etc. etc. etc.)

Blogging§

• Don’t stress about topics
• Get it out of your brain
• If someone asks you something twice, write it up and send out links
• Other good topics: How Tos, Reviews, Rants/Flame Bait
  • If you’re going to go to the trouble to figure something out, compare different solutions, or have a strong opinion about something - share it!

Storify§

Here’s the Storify of tweets from the event:

• tags :: philosophy of science

Logical positivismclaims that all we can say definitively about the world is through science

Although there is a very obvious utility to science, the best science could do is explain the objective. Science works very hard to remove the subjective from it. But science does not speak to the subjective and has much difficulty doing so in the areas where it tries, such as in psychology

But I think there is more to life than just what science can say. Science cannot speak to the sublime, or to thrill or love, or the parts of life that make life exciting. Science does not have much to say about a good movie.

Similarly, the institution of sciencehas a problem with ideology science is often used not for the pure pursuit of truth but for capitalistic ends. When science is synonymous with "the truth", science can come to mean anything that fits an agenda. A subtle example is the so-called "biology as ideology", that different races of people are somehow inherently different based on their biological race alone. Following this to its logical conclusion can end up legitimizing racist projects, as is what happened with eugenicsin the [[file:20210330201641-united_states.org][United States]] and Nazi Germany A more pernicious example is using science to justify the continued use of fossil fuels in the face of ever-devastating [[file:20210427204037-climate_change.org][climate change]].

• [[flancian]] https://twitter.com/flancian/status/1472528806393126913 pull

Via kottke:

In 1981, [[Coevolution Quarterly]] published a 20 question quiz written by [[Leonard Charles]], [[Jim Dodge]], [[Lynn Milliman]], and [[Victoria Stockley]] that is designed to reveal how well you know your local natural environment. Here are the questions:

Trace the water you drink from precipitation to tap.
How many days til the moon is full? (Slack of 2 days allowed.)
What soil series are you standing on?
What was the total rainfall in your area last year (July-June)? (Slack: 1 inch for every 20 inches.)
When was the last time a fire burned in your area?
What were the primary subsistence techniques of the culture that lived in your area before you?
Name 5 edible plants in your region and their season(s) of availability.
From what direction do winter storms generally come in your region?
Where does your garbage go?
How long is the growing season where you live?
On what day of the year are the shadows the shortest where you live?
When do the deer rut in your region, and when are the young born?
Name five grasses in your area. Are any of them native?
Name five resident and five migratory birds in your area.
What is the land use history of where you live?
What primary ecological event/process influenced the land form where you live? (Bonus special: what’s the evidence?)
What species have become extinct in your area?
What are the major plant associations in your region?
From where you’re reading this, point north.
What spring wildflower is consistently among the first to bloom where you live?

I feel emotionally troubled about how few I can answer! I wonder if anyone else is similarly spurred to put this together for [[Seattle]]… They’re obviously not all of equal weight; it’s far more embarrassing that I can’t tell you the dates of first and last frost than our shortest-shadow date.

First Principles: The Building Blocks of True Knowledge§

Metadata§

• Author: [[Authority]]
• Full Title: First Principles: The Building Blocks of True Knowledge
• Category: #articles
• URL: https://fs.blog/2018/04/first-principles/

Highlights§

• When it comes down to it, everything that is not a law of nature is just a shared belief. Money is a shared belief. So is a border. So are bitcoins. The list goes on.

• [[building bridges]]

Ghost Knowledge§

• [[abstractfairy]] "There are ideas that are common knowledge among the practitioners of a field but are not written down anywhere and journals do not consider publish worthy"

david r. maciver, whom I found via [[barnsworth burning]]:

…int), but it was still annoying. The core problem that causes all of this is that there’s a leaky pipeline of knowledge from epistemic communities to the outside world.
In order for you to discover a piece of knowledge:
It has to be interesting enough for someone to think it is worth writing down.
It has to be interesting enough that it gets accepted (though if not, it may end up on a random blog post if you’re lucky).
It has to be interesting or well organised enough that it gets surfaced in a way you can find.
It has to be accessible enough for you to be able to find it (e.g. it can’t use super technical terms that you’ll have no way to ever discover without access to an expert).
This pipeline is leaky enough that it would be very surprising if most knowledge produced by an epistemic community were accessible to you.
This may not seem like a big deal when you think of communities like mathematics, where most consumers of its contents are also members of the community, but it’s a big deal when you consider two things:
Everything is like this, including subjects that everyone would benefit from. I read a lot of therapy books for example and I’ll bet that there’s at least two orders of magnitude more ghost knowledge about therapy than I have access to.
Every community is an epistemic community. Many lessons are e.g. learned over and over again inside companies, and are never written down anywhere, or when they are are so defanged that nobody can benefit from them. The pipeline is different, but the problem is the same.
Given this, we are surrounded by ghosts:
The information that is written down and that we can access is so thin on the ground compared to what’s actually out there,
it’s astonishing that we ever get anything done.

Copyright David R. MacIver. …

• [[go]] https://hyperknowledge.org/

Indigenous and traditional ecological knowledge§

I heard this term from @squeakypancakes@sunbeam.city:

@neil Its colonized itek but if people will actually do it, then its in improvement.

https://sunbeam.city/@squeakypancakes/107067687343910639

Proof of Knowledge§

• [[cryptography]]
• [[pull]] [[zero-knowledge-proof]]
• we know something if we can compute it
• if we want to demonstrate knowledge of something, demonstrate either
  • we can compute it efficiently
  • we already have it
• imagine the same ZKP protocols where the prover is modelled as a black box
  • we allow rewinding this black box
  • "show me edge A-B" and "show me edge A-C" answered by the black box independently for e.g. 3-color problem
  • this allows computing things that aren’t possible to compute in the simulation model, because we can change the distribution of transcripts we see to a subset (transcripts prefixed by up to our rewinding point)

Authored by:: [[P- Joel Chan]]

Synthesis§

• Hypothesis: we have far better evidence of people being the initial / most important first entry points into ideas across disciplinary (and other) boundaries, compared to search or recommendation that is separated from a social interaction of some kind. This is a variant of [[C- In interdisciplinary domains, network-based foraging is more powerful than search-based foraging]]
• We have lots of evidence of people being an effective (and in many cases the most preferred) channel to cross-boundary information
  • In describing how scientists at an interdisciplinary center imported information from outside their specialty, [[@palmerWorkBoundariesScience2001]] identified a range of practices, from talking to personal contacts, reading literature, and engaging in more formal learning activities. A strong theme was the special efficiency and effectiveness of talking to people to access and filter cross-boundary information with maximal signal-to-noise ratio.
    • For example, Palmer writes, "no other type of information interaction is likely to be as efficient and profitable as interactive discussions with colleagues" (p. 33-34)
    • She also summarized that scientists at the interdisciplinary research center imported information across disciplinary boundaries predominantly via personal networks (pp. 31, 32-35). For example, A device physicist at the center said that the vast majority of their information came from keeping on contact with people and going to conferences
  • There is also research on sources of innovation in innovation contests and firm-/organizational-level innovation that suggests an [[outsider innovation]] phenomenon: breakthrough innovations are more likely to come from people who are technically marginal/distant from the problem domain
    • For example, [[@jeppesenMarginalityProblemsolvingEffectiveness2010]] found that Solvers who chose to submit their solutions to the 2nd stage of an innovation contest and self-rated themselves as more technically distant from the problem domain were slightly more likely to submit winning solutions for Innocentive science problem solving contests
  • Additional indirect evidence comes from the literature on collocation and collaboration, which so far we can see generally seems to find facilitative effects on knowledge transfer and collaboration from induced face-to-face contact
    • An entry point is [[@cataliniMicrogeographyDirectionInventive2017]], who found substantial changes in the likelihood of collaboration across research labs as a function of collocation, particularly for labs that were "further apart" in research areas.
      • This work suggests / is consistent with the idea that other channels of search across boundaries are less efficient than face-to-face (presumably "small touch", bc collocation) contact with people from other units (i.e., across boundaries). the logic is that if the search costs were the same / comparable, then those ideas would have initiation probability that is similar to collocation, in the absence of collocation.
    • Similarly, [[@boudreauFieldExperimentSearch2017]] found that The likelihood that any given pair of scientists who were assigned to the same breakout room to discuss their work would collaborate on a pilot grant proposal was estimated to be substantially (75%) higher ($$p(collaborate) = .28$$) compared to scientist pairs who were assigned to different rooms ($$p(collaborate) ~= .16$$). This estimated effect was statistically significant at p < .10.
      • Note, however: this effect seems to be driven by facilitating scientist pairs who are from the same clinical area to collaborate, which suggests there might still be important inefficiencies to accessing and using cross-boundary knowledge, even when you get initial access to it through a person.
• We lack evidence that literature discovery tools that don’t involve tight integration with at least one person can actually help people cross knowledge boundaries
• Why might people be especially efficient access points to cross-boundary information?
  • One explanation might be that [[C- Substantial portions of knowledge that is critical for innovation are not written down]], and are instead "in the heads" of people.
    • This is partially because [[C- Knowledge is fundamentally contextual]]. It is partially on this basis that [[C- CSCW research on knowledge sharing shifted from a repository model to an expertise sharing model around the mid-2000’s]] [[@ackermanSharingKnowledgeExpertise2013]]
  • Another related explanation could be the oblique nature of analogical inspiration: rather than an idea or a phrase or picture being "the idea" that you transfer, it may be more accurate to conceptualize a stimulus, such as an analogous paper as a point/component/spark in a process of inspiration that may lead to a good idea via adapting a direct solution, but also potentially via other routes, such as sparking [[problem (re)formulation]].
    • This, combined with the previous point, may mean that encountering a paper from a different domain, no matter how relevant, may be inert in itself, if it isn’t connected to a rich process of inspiration (e.g., reformulation, query)
• Note that there are still some inefficiencies for the people route
  • For example, [[@laneEngineeringSerendipityWhen]] reported that scientist pairs who were randomly assigned to talk to each other (and did so, face-to-face) at an interdisciplinary medical imaging symposium used about 6 new MeSH keywords from their partners in future publications when the pair had moderate overlap in intellectual interests, compared to low or high overlap (for which there were no clear effects)
    • It’s notable that the observed positive effects here were for estimated less than 20% of the scientist pairs!
    • And in some cases (e.g., when field similarity was high), there were dampening effects on co-authorship in the 6 years following the symposium.
    • #appraisal - these results seem a bit fragile to me: they rest on interaction terms in relatively complex OLS models.
    • Caveats aside, this result suggests that the likelihood that a randomly paired interaction, even within a relatively shared community of interest, and estimating effects on a relatively "lightweight" outcome (i.e., evidence of knowledge transfer, instead of more costly endpoints like copublication), is probably less than a coin flip!
  • These results raises the question: [[Q- What is the range of expected "benefits" of engineered interactions with potential "informants" across knowledge boundaries]]

Sources§

• collocation / structural holes / networks

  • TODO [[@palmerWorkBoundariesScience2001]] Chapter 2

    • scientists at the interdisciplinary research center imported information across disciplinary boundaries predominantly via personal networks (pp. 31, 32-35). For example, A device physicist at the center said that the vast majority of their information came from keeping on contact with people and going to conferences

  • TODO [[@cataliniMicrogeographyDirectionInventive2017]]

  • [[@hargadonTechnologyBrokeringInnovation1997]]

    • This paper introduces the [[model of technology brokering]] through the ethnography study of a product design company IDEO
      • IDEO designers are the brokers
    • (Semi-supportive claim) Upper-level managers are hub of information, quasi-librarians, informal reference systems. This applies to other employees during brainstorm sessions.
      • Semi-supportive as there is no comparison with written product
      • 

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        (p.737)
    • (Semi-supportive claim) In the firm IDEO, people answer knowledge-related questions through instant written product
      • 

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        (p.740)
    • (Supportive claim) People engage in casual interaction for knowledge exchange
      • 

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    • (Semi-supportive claim) knowledge is stored as organizational memory (sometimes artifacts, some time the people as experts) until future design projects come up
      • 

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      • 

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    • (Counter claim) Depending on which theory to explain observations away, for the IDEO case, information about potential solutions reside in physical artifacts, which demonstrate that organization of people, and produces exhibit "networks of juxtaposed components."
      • 

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    • TODO Paper that cites [[@hargadonTechnologyBrokeringInnovation1997]]
      • Scite search
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      • Semantic Scholar
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        • TODO Building Bridges and Breaking Bonds : Aspects of social capital in a regional strategic network
          • J. Frick
          • Business
          • 2011
        • {{TODO}} How Knowledge Transfer Impacts Performance: A Multi-Level Model of Benefits and Liabilities
          • S. Levine, M. Prietula
          • Business, Computer Science
          • Organ. Sci.
          • 2012
        • {{TODO}} Distributed Innovation in Classes of Networks
          • Y. Yoo, K. Lyytinen, R. Boland
          • Computer Science
          • Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008)
          • 2008
        • {{TODO}} The multiple dimensions of the interfirm network: the critical sources of product innovation
          • Thongchai Srivardhana
          • Economics
          • 2006
        • {{TODO}} Collaborative Brokerage, Generative Creativity, and Creative Success
          • L. Fleming, S. Mingo, D. Chen
          • Sociology
          • 2007
        • {{TODO}} Individual roles to achieve knowledge integration in Mergers and Acquisitions: Completing the Knowledge Broker concept with Knowledge Developer’s roles
          • Elvira Periac, S. Gand, Jean-Claude Sardas
          • Business
          • 2012
        • {{TODO}} Networks, Information and Brokerage: The Diversity-Bandwidth Tradeoff
          • S. Aral, Marshall W. Van Alstyne
          • Computer Science
          • 2010
        • {{TODO}} Brokerage vs . Cohesion and Collaborative Creativity : An Evolutionary Resolution
          • L. Fleming
          • 2005
        • {{TODO}} Knowledge Brokering: Spanning Technological and Network Boundaries
          • Carsten Bergenholtz
          • Business
          • 2011
        • {{TODO}} Nexus Work: Brokerage on Creative Projects
          • Elizabeth Long Lingo, Siobhan O’Mahony
          • Economics
          • 2010
        • {{TODO}} The Antecedents and Innovation Consequences of Organizational Knowledge Brokering Capability
          • D. Hsu, K. Lim
          • Business
          • 2007
        • {{TODO}} Knowledge Brokering and Organizational Innovation: Founder Imprinting Effects
          • D. Hsu, K. Lim
          • Business, Computer Science
          • Organ. Sci.
          • 2014
        • {{TODO}} The Impact of Social Capital on Innovation Intermediaries
          • S. Munkongsujarit
          • Business
          • 2013
        • {{TODO}} Bridges, brokers and boundary spanners in collaborative networks: a systematic review
          • J. Long, F. Cunningham, J. Braithwaite
          • Medicine
          • BMC Health Services Research
          • 2013
        • {{TODO}} The impact of intermediaries on innovation performance at small- and medium-sized enterprises in the Yangtze River Delta
          • Y. Shou, Y. Chen, Y. Feng
          • Business
          • 2013
        • {{TODO}} Technology intermediaries and regional innovation performance: an empirical study in China
          • J. Wu, Mengzhou Xu
          • Business
          • 2013

  • [[@burtStructuralHolesGood2004]]

    • This paper proposes that people who connect across groups, the [[structural holes]], are more familiar with alternative ways to think and behave, therefore express valuable ideas.

      • From observations of manager networks in a American electronic firm
      • This theory has predecessors, (also noted in the [[@hargadonTechnologyBrokeringInnovation1997]] paper),
        • The sociological theory of Simmel
          • 

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        • Social capital (which the structural holes are)
          • 

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    • (Scaffolding claim which is not directly supporting) A network diagram shows information flow. The text is saying information flow is more routine or more clear between people who connects more (than those who connects less?)

      • 

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      • 

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    • (Scaffolding claim that reveals an issue) This paper compares people who are structural holes vs. those who are not. Expect to have some comparisons on structural holes vs. written products (if they later states that supply-chain issues are also documented but not referenced as more frequent than talking to people)

      • 

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    • TODO Paper that cites [[@burtStructuralHolesGood2004]]

      • From Scite
        • Minor system issue
          • 

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        • 

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        • 

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        • 

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        • 

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        • 

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        • 

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          • For this: not sure it is supporting
      • From Semantic Scholar
        • 

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        • {{TODO}} Dynamic Capabilities of SMEs: The Contributions of Bricolage and Social Capital
          • T. Huynh, D. Patton
          • Sociology
          • 2017
        • {{TODO}} Knowledge Specialization, Knowledge Brokerage and the Uneven Growth of Technology Domains
          • Gianluca Carnabuci, Gianluca Jeroen Bruggeman
          • Economics, Biology
          • 2009
        • {{TODO}} Social networks, individual orientations, and employee innovation outcomes: A multi-theoretical perspective
          • Travis J. Grosser
          • Political Science
          • 2013
        • {{TODO}} The Role Of Social Ties In Fostering Innovation
          • M. M. Salaran, A. Maritz
          • Sociology
          • 2013

  • DONE [[@laneEngineeringSerendipityWhen]]

    • scientist pairs who were randomly assigned to talk to each other (and did so, face-to-face) at an interdisciplinary medical imaging symposium used about 6 new MeSH keywords from their partners in future publications when the pair had moderate overlap in intellectual interests, compared to low or high overlap (for which there were no clear effects)
• outsider innovation
  • TODO [[@cattaniDeconstructingOutsiderPuzzle2017]]
  • [[@frankeIntegratingProblemSolvers2014]]
  • DONE [[@jeppesenMarginalityProblemsolvingEffectiveness2010]]
    • Solvers who chose to submit their solutions to the 2nd stage of an innovation contest and self-rated themselves as more technically distant from the problem domain were slightly more likely to submit winning solutions for Innocentive science problem solving contests
• search / literature-based discovery
  • [[@sebastianEmergingApproachesLiteraturebased2017]]
  • [[@smalheiserRediscoveringDonSwanson2017]]
  • [[@kostoffLiteraturerelatedDiscovery2009]]
  • [[@swansonFishOilRaynaud1986]]
  • [[@swansonUndiscoveredPublicKnowledge1996]]
• recommender systems
  • DONE [[@packerImportanceSDICurrent1979]]
    • [[SDI]] use was associated with a significant reduction in efficiency of keeping up to date with the literature for scholars in self-reported low-[[Scatter]] fields; in contrast, SDI use was not associated with efficiency for high-scatter scholars (although there was a numeric trend in a positive direction)
  • [[@beelResearchpaperRecommenderSystems2016]]
• interdisciplinarity / domain analysis
  • DONE [[@moteReasonsVariationInformation1962]]
    • Scholars in fields of study with high degree of [[Scatter]] self-reported needing longer searches (> 30 mins) about 20x more frequently compared to scholars in low [[Scatter]] fields

• an [[article]].
  • [[ruben verborgh]]
  • #go https://ruben.verborgh.org/blog/2021/12/23/reflections-of-knowledge/

• [[flancian]] https://social.coop/@flancian/108376230292126834 pull

• [[flancian]] https://twitter.com/flancian/status/1530312309507334144 pull

There is no such thing as knowledge§

So sayeth [[Mike Hales]] https://social.coop/@mike_hales/107430510590782176

Because§

Dunno

It’s hard to pitch and sustain this kind of perspective, and I can’t easily point to other places where it’s up front in the same way. Culture is so saturated with idealist perceptions of ‘knowledge’ as ‘a body’ or as accumulatable ‘stuff’.

A historical, materialist framing - centred on practices of people-in-culture - is difficult to arrive at in the face of such hegemonic stuff

Epistemic status§

Type : [[claim]]

Agreement level : [[Concentrate and ask again]]

I’m not really sure what Mike meant by this, and Mike himself doesn’t seem to have a clear description.. But it’s interesting and provocative and I [[Trust Situated Knowing]] from Mike. I’d guess that Mike’s gist is around knowledge being a relationship rather than an abstract thing.

traditional knowledge§

• [[wp]] https://en.wikipedia.org/wiki/Traditional_knowledge pull

• a [[paper]]
  • [[go]] https://www.researchgate.net/publication/334126329_Weaving_a_Decentralized_Semantic_Web_of_Personal_Knowledge