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A turning point

The fake is getting a bit too real.

We’re not ready.

This is going to get worse before it gets better.

This Generative Adversarial Network (GAN) creates, from scratch, a new face every time it is refreshed:

Doing this requires some super-expensive and powerful hardware, but now there’s a website that bypasses that requirement: generating a fancy new face is as easy as refreshing your browser with the aptly-named Every time you load the page, an algorithm generates a new human face from scratch.

The website uses an implementation of machine learning known as Generative Adversarial Networks, or GANs. These programs “learn” from a large number of training inputs—say, real human faces—in order to produce new examples. uses code previously released by Nvidia researchers on GitHub.

And in the same week, we have seen surprisingly human text come from a different algorithm:

At its core, GPT2 is a text generator. The AI system is fed text, anything from a few words to a whole page, and asked to write the next few sentences based on its predictions of what should come next. The system is pushing the boundaries of what was thought possible, both in terms of the quality of the output, and the wide variety of potential uses.

When used to simply generate new text, GPT2 is capable of writing plausible passages that match what it is given in both style and subject. It rarely shows any of the quirks that mark out previous AI systems, such as forgetting what it is writing about midway through a paragraph, or mangling the syntax of long sentences.

Our old human brains are about to get lapped.

We need verified identity. We need provenance. We need education.

We need vigilance.

We need to greatly increase our collective ability to spot, label, and disregard unreliable information.

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Thank you, JPBarlow

RIP John Perry Barlow, EFF Co-Founder

A Declaration of the Independence of Cyberspace

Governments of the Industrial World, you weary giants of flesh and steel, I come from Cyberspace, the new home of Mind. On behalf of the future, I ask you of the past to leave us alone. You are not welcome among us. You have no sovereignty where we gather.

We have no elected government, nor are we likely to have one, so I address you with no greater authority than that with which liberty itself always speaks. I declare the global social space we are building to be naturally independent of the tyrannies you seek to impose on us. You have no moral right to rule us nor do you possess any methods of enforcement we have true reason to fear.

More …

Davos, Switzerland
February 8, 1996

Principles of Adult Behavior

1. Be patient. No matter what.
2. Don’t badmouth: Assign responsibility, not blame. Say nothing of another you wouldn’t say to him.
3. Never assume the motives of others are, to them, less noble than yours are to you.
4. Expand your sense of the possible.
5. Don’t trouble yourself with matters you truly cannot change.
6. Expect no more of anyone than you can deliver yourself.
7. Tolerate ambiguity.
8. Laugh at yourself frequently.
9. Concern yourself with what is right rather than who is right.
10. Never forget that, no matter how certain, you might be wrong.
11. Give up blood sports.
12. Remember that your life belongs to others as well. Don’t risk it frivolously.
13. Never lie to anyone for any reason. (Lies of omission are sometimes exempt.)
14. Learn the needs of those around you and respect them.
15. Avoid the pursuit of happiness. Seek to define your mission and pursue that.
16. Reduce your use of the first personal pronoun.
17. Praise at least as often as you disparage.
18. Admit your errors freely and soon.
19. Become less suspicious of joy.
20. Understand humility.
21. Remember that love forgives everything.
22. Foster dignity.
23. Live memorably.
24. Love yourself.
25. Endure.

October 2, 1977

Donate to the EFF.

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Vigilance for the truth

Vigilance is still king.

Democratic ideals require a few things to function on the network:

  • We need identity.
  • We need persistence.
  • We need transparency.
  • We need multiple people to care.

With these, the voice of everyone has a chance against the voice of the motivated, the monied, and/or the already powerful.

Without vigilance, the story that remains will be only the story that was retold the most broadly, not necessarily what happened.

Gilad Lotan writes about some of his recent work:

No matter how much volume, how many tweets, or Facebook likes a campaign generates, if the messages aren’t embedded within existing networks of information flow, it will be very difficult for information to actually propagate. In the case of this hoax on Twitter, the malicious accounts are situated within a completely different network. So unless they attain follows from “real accounts,” they can scream as loud as they’d like, still no one will hear them. One way to bypass this is by getting your topic to trend on Twitter, increasing visibility significantly.

Social networked spaces make it increasingly difficult for a bot or malicious account to look like a real person’s account. While a profile may look convincingly real — having a valid profile picture, posting human readable texts, and sharing interesting content — it is hard for them to fake their location within the network; it is hard to get real users to follow them. We can clearly see this in the image above: the community of Russian bots are completely disconnected from any other user interacting with the hashtag.

The same principle holds for Wikipedia, which is even harder to game as it is easy to identify those accounts who are not really connected to the larger editing community. The more time you spend making relevant edits and the more trusted your account becomes the more authority you gain. One can’t simply expect to appear, make minor edits on three pages, and then put up a page detailing a terror act without seeming suspicious.

As our information landscapes evolve over time, we’ll see more examples of ways in which people abuse and game these systems for the purpose of giving visibility and attention to their chosen topic. Yet as more of our information propagation mechanisms are embedded within networks, it will become harder for malicious and automated accounts to operate in disguise. Whoever ran this hoax was extremely thorough, yet still unable to hack the network and embed the hoax within a pre-existing community of real users.

Then John Borthwick finishes some of the same thoughts:

Last year I wrote a post here on medium about how attention and reading are evolving. We are living in an era of unprecedented transparency — and interestingly many of these hacks are happening in broad daylight. Unless we measure and value attention — time spent reading, listening, or viewing versus the raw click volume we aren’t going to build things that are actually of interest to humans. Take note of how bots are being used as part of these hacks.

And he finishes with:

Perspectives matter:

My assumption has always been that increased transparency would result in a greater efficiency of information flow and that in turn, would naturally bend towards facts. Put another way, in an open society, with efficient information flow, fact and truth will win out. It’s impossible to measure this on the aggregate — and I believe that on the aggregate that is true — but its clear there are local cases where this simply isn’t the case. Russia is more far open a society than it was 30 years ago. Or turn to the middle east and take a read of Gilad’s post about Israel, Gaza, War & Data. Or dig into how fake sites made up news about a Texas town under quarantine for Ebola to harvest clicks, or how “real” news sites make up news. Or Craig Silverman’s piece on how a Priest died and met God in the “48 minutes” before he came back to life. In all these cases transparency isn’t succeeding at winnowing out bullshit. And mainstream media offers an implicit assist by assuming its role is to be the established view from nowhere.

Media critics like Jay Rosen use the term, ‘view from nowhere’ to describe how some media strives to a balance between objectivity and the reporting of facts, often erring on reporting each side of an argument. They offer each perspective equal weighting, setting up the false impression that both perspectives are equally valid since they required equal coverage. As Rosen outlines (in a debate with himself) mainstream media is loath to say: ‘this is rubbish.’ They want to provide “perspective” — rather than take a position. And in today optimized world they want to generate SEO and social traffic from both sides of an argument.

Match this phenomenon with the torrid pace of sharing before or without reading and you have a toxic mix that can be effectively gamed or hacked. In the post I wrote last summer I noted how a huge percent of articles shared are never actually read: “Chartbeat looked at user behavior across 2 billion visits across the web over the course of a month and found that … a stunning 55% spent fewer than 15 seconds actively on a page.” Transparency was meant to be the new objectivity. Yet if people aren’t reading before they share — if mainstream media is balancing every perspective, if headlines without branded context are now content — media can and will be hacked, and perspective will be narrowed rather than broadened.

As Dmitry Tulchinskiy, bureau chief Rossiya Segodnya, said in August: “What is propaganda? Propaganda is the tendentious presentation of facts …It does not mean lying.” Tendentious — expressing or intending to promote a particular cause or point of view — with such a clear choice of words, I wish he had talked more about the methodology.

Please be present.

Please engage.

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Goodnight claimID

From a coffee shop on Franklin Street in May 2006…


To today…


After 7 years, 6 months, and 20 days, Fred and I have closed the doors we opened at

We tried for months to keep the existing codebase up and running, but have hit a wall and decided to make a clean break for 2014 as our professional and personal lives are moving on.

I’d like to thank all our users, testers, critics, and well-wishers. We both learned a lot and continue to polish the principles we put into place on a napkin in late 2005.

The wiki won’t forget…




Site Maintenance Ninjas.


There is already an open source project to help collect your claimID links from the Google Cache and the Internet Archive…

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This is a Website

Back to basics.

Zeldman re-nails the truth to the door:

We were struggling, whether we knew it or not, to found a more fluid society. A place where everyone, not just appointed apologists for the status quo, could be heard. That dream need not die. It matters more now than ever.

Also relevant in the last few days…

Kevin Marks consolidates and makes clear the call for publishing on your own site under the monikers of IndieWeb and POSSE:

The IndieWeb is a group of people who recognise that the silos are important for connecting – but you should have your own site. Don’t replace those tools, but use them to connect the rest of the web.

Its principles:

  • You should own your own data. Have your own page, not a Facebook or Google one.
  • You should have visible data. People can read it, programs can index it. You can’t crawl Facebook or Twitter any more.
  • POSSE – Publish on your Own Site and Share Elsewhere. Spread links to your own stuff.
  • Make tools for you, not for other people. If you wouldn’t use it, other people won’t. Odeo was a classic example: a podcast platform built by people who didn’t podcast.
  • Document what you do. Say what works – help other people by doing so. And Open Source what you make, because you get help and it ensures that what you do will last.
  • Design and UX are really important. Don’t just add them on top of what you’ve built.
  • Be modular. Don’t try to build everything – build pieces that plug together. It makes it easier to swap things out, or replace dead services.
  • The Long Web – expect it to last, don’t destroy history and spread copies elsewhere.
  • Bet on the web – open outlasts closed. Make infrastructure that others can build on.

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Star Wars Traceroute

I approve. Well done.

[01:53:34:terrell:~] traceroute
traceroute to (, 64 hops max, 40 byte packets
1 DD-WRT ( 1.778 ms 0.965 ms 0.972 ms
2 X.X.X.X (X.X.X.X) 4319.610 ms 653.098 ms 989.215 ms
3 X.X.X.X (X.X.X.X) 10.783 ms 11.015 ms 9.044 ms
4 X.X.X.X (X.X.X.X) 14.951 ms 15.737 ms 17.228 ms
5 X.X.X.X (X.X.X.X) 20.725 ms 23.103 ms 22.108 ms
6 X.X.X.X (X.X.X.X) 20.635 ms 20.397 ms 20.367 ms
7 X.X.X.X (X.X.X.X) 19.392 ms 21.003 ms 20.632 ms
8 X.X.X.X (X.X.X.X) 25.919 ms 27.565 ms 28.348 ms
9 X.X.X.X (X.X.X.X) 29.569 ms 28.365 ms 47.818 ms
10 X.X.X.X (X.X.X.X) 36.890 ms 42.500 ms 34.361 ms
11 ( 37.376 ms 33.859 ms 34.832 ms
12 ( 71.284 ms 73.373 ms 74.729 ms
13 Episode.IV ( 75.255 ms 74.035 ms 72.494 ms
14 A.NEW.HOPE ( 73.352 ms 72.094 ms 80.763 ms
15 ( 78.096 ms 73.407 ms 72.188 ms
16 Rebel.spaceships ( 75.278 ms 74.521 ms 72.252 ms
17 striking.from.a.hidden.base ( 73.525 ms 72.386 ms 75.327 ms
18 have.won.their.first.victory ( 72.208 ms 76.449 ms 71.627 ms
19 against.the.evil.Galactic.Empire ( 71.237 ms 75.359 ms 75.141 ms
20 During.the.battle ( 73.632 ms 73.249 ms 98.531 ms
21 Rebel.spies.managed ( 71.557 ms 76.052 ms 74.371 ms
22 to.steal.secret.plans ( 74.359 ms 75.895 ms 70.592 ms
23 to.the.Empires.ultimate.weapon ( 72.119 ms 70.990 ms 72.564 ms
24 the.DEATH.STAR ( 72.542 ms 74.445 ms 69.418 ms
25 ( 72.837 ms 74.931 ms 73.238 ms
26 ( 78.216 ms 75.765 ms 75.968 ms
27 ( 77.789 ms 71.486 ms 82.158 ms
28 ( 70.843 ms 72.229 ms 71.074 ms
29 sinister.agents ( 93.551 ms 73.051 ms 77.141 ms
30 Princess.Leia.races.home ( 72.978 ms 74.585 ms 86.441 ms
31 aboard.her.starship ( 71.213 ms 73.221 ms 73.960 ms
32 custodian.of.the.stolen.plans ( 76.098 ms 72.299 ms 83.800 ms
33 ( 76.698 ms 94.189 ms 75.499 ms
34 people.and.restore ( 74.464 ms 76.196 ms 77.622 ms
35 ( 74.305 ms 73.426 ms 72.192 ms
36 0——————-0 ( 73.460 ms 72.617 ms 72.484 ms
37 0——————0 ( 93.170 ms 74.607 ms 72.840 ms
38 0—————–0 ( 76.676 ms 71.048 ms 72.883 ms
39 0—————-0 ( 72.887 ms 75.016 ms 72.747 ms
40 0—————0 ( 74.049 ms 71.829 ms 71.965 ms
41 0————–0 ( 79.273 ms 77.037 ms 74.715 ms
42 0————-0 ( 71.096 ms 70.350 ms 73.542 ms
43 0————0 ( 77.069 ms 74.029 ms 98.237 ms
44 0———–0 ( 72.721 ms 75.693 ms 79.453 ms
45 0———-0 ( 75.535 ms 73.245 ms 73.831 ms
46 0———0 ( 75.518 ms 74.066 ms 75.403 ms
47 0——–0 ( 73.700 ms 82.691 ms 75.254 ms
48 0——-0 ( 113.922 ms 76.521 ms 72.705 ms
49 0——0 ( 77.582 ms 73.703 ms 70.344 ms
50 0—–0 ( 77.320 ms 71.889 ms 72.693 ms
51 0—-0 ( 80.346 ms 71.921 ms 80.707 ms
52 0—0 ( 80.125 ms 77.102 ms 80.215 ms
53 0–0 ( 77.728 ms 80.163 ms 77.070 ms
54 0-0 ( 73.702 ms 77.104 ms 72.118 ms
55 00 ( 72.092 ms 74.901 ms 78.953 ms
56 I ( 73.664 ms 75.796 ms 77.909 ms
57 By.Ryan.Werber ( 77.864 ms 77.650 ms 70.416 ms
58 When.CCIEs.Get.Bored ( 73.452 ms 76.024 ms 92.681 ms
59 CCIE.38168 ( 77.365 ms 75.129 ms 75.953 ms
60 FIN ( 98.664 ms * *

A reading list as personal description

Eugene Eric Kim has captured my attention before.

And now he’s done it again a few minutes ago:

What My Reading List Says About Me

I’m a hard one to nail down. I have lots of different interests, and while they’re all form an integrated whole in my head, that may not be as apparent to others. It got me thinking about whether or not I pay enough attention to my online persona. The answer is probably not, but the real question is whether or not I care enough to do something about it. (Again, the answer is probably not.)

So then I thought about looking at other data about myself to see what I could learn. I decided to check my Evernote tags. I’ve been an avid Evernote user for several years now, and it is my primary tool for clipping interesting articles. I’m also an avid tagger, so I have a pretty good emergent taxonomy to use for analysis.

I decided to look at my most frequent, topical tags. (I have a set of tags that I use for internal organization, which are irrelevant for the purposes of this analysis.) I then created a tag cloud using Wordle. Here were the results

He has used his own tagging rather than the tagging of others, but that’s okay. All this data is still cognitively generated, not coming from an algorithm or massively chewing through all the full text of the documents he’s reading. The words come from a human brain, one that is doing the due diligence of condensing and distilling the concepts of what is important, what is relevant, from the mass of stuff it’s reading.

The distinction is key – and I think EEK’s exercise is illustrative of value being revealed with some simple counting and strong placement.

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Field Report from Collective Intelligence 2012

It was an amazing trip to MIT this week. I spent a beautiful three sunny days in Cambridge visiting friends and attending the Collective Intelligence 2012 conference. I was there to present my dissertation work (a little depressingly compressed into an 8-page paper and poster) to some of the smartest people I have ever met.

The conference was the first of its kind and hopefully will stand as the first in a long line to continue investigating how we work together in seemingly intelligent ways. The overview text from the conference website:

Collective intelligence has existed at least as long as humans have, because families, armies, countries, and companies have all – at least sometimes – acted collectively in ways that seem intelligent. But in the last decade or so a new kind of collective intelligence has emerged: groups of people and computers, connected by the Internet, collectively doing intelligent things. For example, Google technology harvests knowledge generated by millions of people creating and linking web pages and then uses this knowledge to answer queries in ways that often seem amazingly intelligent. Or in Wikipedia, thousands of people around the world have collectively created a very large and high quality intellectual product with almost no centralized control, and almost all as volunteers!

These early examples of Internet-enabled collective intelligence are not the end of the story but just the beginning. And in order to understand the possibilities and constraints of these new kinds of intelligence, we need a new interdisciplinary field. Forming such a field is one of the goals of this conference.

We seek papers about behavior that is both collective and intelligent. By collective, we mean groups of individual actors, including, for example, people,
computational agents, and organizations. By intelligent, we mean that the collective behavior of the group exhibits characteristics such as, for example,
perception, learning, judgment, or problem solving.

Topics of interest include but are not limited to:

    human computation
    social computing
    wisdom of crowds (e.g., prediction markets)
    group memory and problem-solving
    deliberative democracy
    animal collective behavior
    organizational design
    public policy design (e.g., regulatory reform)
    ethics of collective intelligence (e.g., “digital sweatshops”)
    computational models of group search and optimization
    emergence and evolution of intelligence
    new technologies for making groups smarter

Invited Speakers

All the plenaries were excellent and nearly all the accepted paper sessions were strong as well. I began the conference a little in awe of the names walking so near me at a conference with a population of only 203. But the intimacy of such a setting allowed me to have hallway conversations and lunch(es) with some of the researchers I most admire in this interdisciplinary field.

I am tickled that my work will be found in the proceedings alongside such strong, visionary research.

The full proceedings are online at and freely available.

My paper is here: Collective Cognitive Authority: Expertise Location via Social Labeling

And the accompanying poster:

For posterity, I’ve included my tweets from during the conference:

19 Apr – walking through MIT campus for start of Collective Intelligence 2012 #ci2012
19 Apr – remarkable collection of interdisciplinary luminaries in this room. pleased to be here #ci2012
19 Apr – i’m a poster. RT @gegenhuber #ci2012: 104 paper submission, 18 for presentation, 16 for poster. Very diverse group.
19 Apr – nice trend so far of showing faces of named collaborators on slides #ci2012
19 Apr – remarkable work being done at #ci2012
19 Apr – Anita Woolley (CMU) looking for ‘c-factor’, traits/markers that indicate who exhibit collective intelligence #ci2012
19 Apr – says Anita Woolley (CMU) “when sensitivity to signaling within the group is higher, CI is higher” (re: women, ants, etc.) #ci2012
19 Apr – listening to @YBenkler – he works on a different level. impressive. #ci2012
19 Apr – says @YBenkler “collaboration among diverse participants will benefit from structure, and could benefit from power” #ci2012
19 Apr – says @YBenkler “but power can undermine intrinsic motivation” #ci2012
19 Apr – Ian Spiro (NYU) et al have built a markerless motion capture tool using mechanical turk #ci2012
19 Apr – and the code is open! #ci2012
19 Apr – incredible. realtime crowds @msbernst – can bring in huge group responses in half a second using ‘retainers’ #ci2012
19 Apr – says @ipeirotis “brain functions are biologically expensive (MTurk workers want to use only their motor skills)” #ci2012
19 Apr – says @ipeirotis “confuse bad MTurk workers by punishing with unpredictable ‘errors’ (fake loading messages, 404s, etc.)” #ci2012
19 Apr – Bob Kraut (CMU) discussing self/group motivation dynamics – how to get social identity to align group goals #ci2012
19 Apr – Bob Kraut (CMU) says publicizing important community tasks helps align individual motivation with group goals #ci2012
19 Apr – .@jpom orig Woolley Science article – signaling part of ‘social intelligence’, made connection to ants today #ci2012
19 Apr – speaker @winteram on Group Identity, Culture, and Collective Intelligence and Social Learning #ci2012
19 Apr – speaker @rbmllr (MIT) showing a ‘wickedly hard handwriting example’, using iterative improvement MTurk HIT #ci2012
19 Apr – says Yahoo’s @xeeliz “I’m interested in the collected as well as the collective. Are they the right data?” #ci2012
19 Apr – And I do love hearing @xeeliz speak – smart, funny, relevant, british #ci2012
19 Apr – Ed Hutchins (UCSD) talks about ‘distributed cognition’ – began by studying high-staked small groups (Navy ship navigation) #ci2012
19 Apr – Ed Hutchins (UCSD) says “What will happen when all airlines/pilots carry iPads instead of 30lbs of paper (maps/data)? Don’t know!” #ci2012
19 Apr – .@benbendc asking “who are we?” to the community in the room “what do we want to do?” #ci2012
19 Apr – says @benbendc “We need a Large Social Collider” – demanding our Sputnik moment #ci2012
19 Apr – .@zittrain saying “significance of this room’s expertise” … agreeing with @benbendc “this stuff matters” #ci2012
19 Apr – says @zittrain “we have a new unit/particle – ‘cogs’ in our field. both cognition… and cogs in a machine” #ci2012
19 Apr – says @zittrain “These arm’s length markets… are laundering ethics” #mturk #ci2012
19 Apr – always book @zittrain as a final speaker. anyone having to follow would be depressed. #awesome #ci2012
19 Apr – .@zittrain writing a book this summer named “Cog” – hopes to offer solutions to our new realities of collective intelligence. #ci2012
20 Apr – speaker @ladamic discussing information diffusion in social networks. “How and how much are we influenced by our people?” #ci2012
20 Apr – says @ladamic “preference of viral social objects: true > funny > awesome > cute” #ci2012
20 Apr – says @cfchabris “simple response time for groups is second highest predictor for collective intelligence” #ci2012
20 Apr – says @cfchabris “turn taking in groups correlated with high CI, followed by social ability (Reading the Mind in the Eyes test)” #ci2012
20 Apr – says @cfchabris intelligence may be a property of all “species” of complex information processing systems #mice #monkeys #groups #ci2012
20 Apr – .@klakhani (Harvard Business School and NASA Tournament Lab) covering many examples of innovation contests #ci2012
20 Apr – Scott E. Page (Michigan) layering economic model math on Surowiecki’s Wisdom of Crowds (diversity = inverse covariance) #ci2012
20 Apr – speaker @seydaertekin on predicting wisdom of crowds without ground truth to best use limited budget #crowdsense #ci2012
20 Apr – Yu An Sun (Xerox) speaking on dealing with when the crowd majority voting doesn’t work, other methods, comparisons #ci2012
20 Apr – being controversial, @nikete w/ @mdreid on Crowd & Prejudice, and impossibility of crowd labeling without a gold standard #ci2012
20 Apr – Michael E. Roberts (DePauw) Group Foraging in Dynamic Environments, modeling group/food behavior #ci2012
20 Apr – Pavlin Mavrodiev (ETH Zurich) showing examples/models of non-independent opinions effecting ‘wisdom of crowds’ #ci2012
20 Apr – Ying Zhang (PARC) on thermodynamic principles in social collaborations – Wikipedia as thermodynamic system #ci2012

Thank you to everyone at MIT, CSAIL, the NSF, the Kendall Hotel, and the conference committee for a thought-provoking, inspiring, and tasty week.

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My First Two Books

It’s been a big week in my publishing life.

Last week, two documents that I’ve been working on for years are now available in book form.

First, my dissertation is now available from ProQuest in a lovely academic hardcover edition. I plan to order one for my shelf. Everyone else, please, just download the PDF (it’s creative commons). ProQuest has enough money already.

And second, the iRODS 3.0 microservices book is now available on Amazon. Everything you wanted to know about iRODS.


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Pesce on Expertise

Mark Pesce’s in my brain again, or rather, still.


If you know something that others want to know, they will find you.

In addition to everything else, we are each a unique set of knowledge, experience and capabilities which, in the right situation, proves uniquely valuable. By sharing what we know, we advertise our expertise. It follows us where ever we go. Because this expertise is mostly hidden from view, it is impossible for us to look at one another and see the depth that each of us carries within us.

Every time we share, we reveal the secret expert within ourselves. Because we constantly share ourselves with our friends, family and co-workers, they come to rely on what we know. But what of our colleagues? We work in organizations with little sense of the expertise that surrounds us.

Before hyperconnectivity, it was difficult to share expertise. You could reach a few people – those closest to you – but unless your skills were particularly renowned or valuable, that’s where it stopped. For good or ill, our experience and knowledge now extend far beyond the circle of those familiar to you, throughout the entire organization. Everyone in it can now have some awareness of the talents that pulse through your organizations – with the right tools in place.

And then:

Every employee in an organization has a specific set of talents, but these talents are not evenly distributed. Someone knows more about sales, someone else knows more about marketing, or customer service, or accounting. That’s why people have roles within an organization; they are the standard-bearers for the organization’s expertise.

Yet an employee’s expertise may lie across several domains. Someone in accounting may also provide excellent customer service. Someone in manufacturing might be gifted with sales support. A salesman might be an accomplished manager. People come into your organization with a wide range of skills, and even if they don’t have an opportunity to share them as part of their normal activities, those skills represent resources of immense value.

If only we knew where to find them.

You see, it isn’t always clear who knows what, who’s had experience where, or who’s been through this before. We do not wear our employment histories on our sleeves. Although we may enter an organization with our c.v. in hand, once hired it gets tucked away until we start scouting around for another job. What we know and what we’ve done remains invisible. Our professional lives look a lot like icebergs, with just a paltry bit of our true capabilities exposed to view.

I gotta build this thing and get it out there…
Contextual Authority Tagging

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