The challenge and opportunity of Extelligence

0 Comments 02.12.17

Being human is hard.  It’s complicated, at least if you want to do it well, I think.  Now picture the amount of data available to us exploding in the next few years.  Most of that data will be processed for us by machines, but the sheer number of analytical conclusions the machines offer us will be overwhelming, as well.

Models and Frameworks 

I’m excited about the conscious and practiced use of models to understand data super-rich experiences.  My latest favorite has been something I learned from a Kirk Borne blog post.  This is about data science, but it can just as easily be applied to any complex part of life, I think. “Dimensionality reduction is a critical component of any solution dealing with massive data collections. Being able to sift through a mountain of data efficiently in order to find the key (1) descriptive, (2) predictive, and (3) explanatory features of the collection is a fundamental required capability for coping with the Big Data avalanche.”

I added the numbers to that sentence but have literally found it very useful to look at complex situations and ask myself, “of all the things you could say about that situation, which one or two are most descriptive of the whole?  Then, of all the qualities of this experience, which are most predictive of its outcome?  Finally, which of the many parts of this whole thing go the furthest in explaining the whole thing?”

I used that framework in an influencer engagement training session with a very large B2B company last week, explaining that the thought leadership data mining system I’d just trained them to use could be best defined by its networked nature – the people at the center of the community have built and earned a ton of connections to others, that’s the most defining quality of the situation.  The most explanatory feature, I believe, is the humanity of the participants.  They’re all just like you, and they’ve worked hard to contribute to the network.  You’re going to have to too, and be human with the people you can connect with, if you really want to understand the social space you’re looking to do business in.  Finally, the most predictive quality of social networking is its cumulative nature, I said.

We’d previously discussed how all tasks can be understood as either optimization tasks (to be completed as fast as possible), maintenance tasks (where there’s a linear relationship between effort and outcome) and investment tasks (greater than linear, sometimes exponential value derived relative to effort).  And we talked about how influencer engagement can and should be done as all three of those task types.  Mixing it up.  So the most predictive feature of the experience is probably its cumulative nature – the more you do all kinds of work in connecting with influential people online, co-creating value with them, the more impact each engagement makes over time.

That’s a couple of models, I suppose, both identifying the most defining, explanatory, and predictive features in a phenomenon, and the model of optimization, maintenance, and investment tasks.  What are those kinds of things? I think they could be understood as forms of “extelligence.”


Tonight I was reading some writing from Belgian Internet of Things thought leader Rob van Kranenburg (amazingly thought provoking, delightful to see that tons and tons of other leaders in IoT follow him on Twitter according to our data) and came across the term “Extelligence.”

“Extelligence,” van Kranenburg writes,”a term by Ian Stewart and Jack Cohen, a biologist and mathematician, is cultural capital available to us as external media.”  It’s external, not internal like in-telligence. Get it? Cool.

Van Kranenburg concludes a strongly worded piece of writing titled The end of strategic leadership: be extelligent or extinct with the following:

“In an information-rich, digitally connected world, where much of the knowledge and tools that we make use of are outside our heads there will be a need to develop new communication ‘senses’ that allow us to manage and make use of the enormous amount of information we will be confronted by. This will lead to the development and adoption of new and different types of human-computer interfaces and different ways of communicating with technology.  We know this as deep learning and machine learning; artificial intelligence.

“But this is the superficial reading of extelligence.  Extelligence, a term by Ian Stewart and Jack Cohen, a biologist and mathematician, is cultural capital available to us as external media. For them ‘complicity’ – a combination of complexity and simplicity –  of extelligence and intelligence is fundamental to the development of consciousness, and your business, institution, government or startup.

“What does this mean if you are over 50.000, 100.000 as an organization? Get the scouts and scavengers on the ground operating autonomously, build complicity only in the links between them. Provide good exits to anyone else and keep them close to where you think the teams are not heading.”

New communication “senses” that allow us to manage and make use of the enormous amount of information we will be confronted by?!  How exciting is that?  I nominate “the network,” social media, frameworks and models as great new sources of extelligence, of cultural capital available to us as external media!

I said I’d mention the challenges, too, in the title of this blog post.  I think the biggest challenge is that this requires stretching your brain, or hiring someone to help you think.  I do that every week, personally, and my counselor tells me “people aren’t stupid, they’re just cognitively efficient. We’ve evolved to expend the minimal amount of energy possible so we can keep it in reserve for a crisis.”

Well, we’re in a crisis, but it’s abstract, collective, and we’re not inclined to recognize it, much less address it with tools of extelligence.  Thus the challenge.

But wow are the opportunities incredible.


PS: Speaking of leveraging the network as a source of extelligence, I just wrote this first blog post in months because I finally figured out how to get my blog to load faster. I posted a Twitter poll asking if it was maddeningly slow for others and found (a) that a fair number of people reported it loaded just find and then (b) one of my contacts pointed out a specific problem that was slowing the load! So I fixed it and now I feel like blogging!  Thanks, extelligent internet friends!

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One of the most important websites for the future of big data & AI is up for sale this week

2 Comments 05.23.16

The future of the world will be impacted in major ways by big data and artificial intelligence.  That much is undeniable, right?

But how is data accessed and how does AI make connections and recommendations between technologies, data sets, and users?  Through something called an API, or Application Programming Interface.

APIs are already big but they’re sure to get a whole lot bigger. The founding team behind Siri, for example, is making headlines with a new AI assistant called Viv that’s all about weaving together different technologies from different products and services, through their APIs of course.  Uber’s API is huge news.  Amazon Alexa’s voice API is big.  IBM’s Watson is all about building out an ecosystem of empowered applications through its API.  Not just web technologies but buildings, infrastructures, all kinds of things are going to have interfaces to program applications on top of them.

APIs are the technical pathway through which the symphony of combinatorial innovation is being built.

Here’s the fascinating news of the day: the most influential man in the world of APIs, Kin Lane, has just put his website up for sale.  Kin built API Evangelist up to become one of the most important technical blogs in the world, with his bare hands and support from sponsors, and now he’s walking away from it to dedicate the next months of his life to support a member of his family.  It’s a beautiful, inspiring story of a man sacrificing something great he’s built for the love of family, for principals, for empathy, for healing.  It’s incredible.

In the meantime, APIs are poised to be the glue of the big data, artificial intelligence enriched world, and API Evangelist already has that community’s ear with its blog posts, best practice guides, and great social presence.

We all have until Friday to enter bids to buy it.  Bidding starts at $10,000. I hope someone pays a lot of money for it and does great things with it.

Below: From a Little Bird report on the most influential people and organizations in the world of APIs. These are the API experts that other API experts follow most.

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Ethics in Autonomous Corporations, Investments in Human Community, and the Strategic Value of Social Media: Three Good Twitter Conversations This Week

1 Comment 05.22.16

Last weekend I started what I’d like to make a regular series of blog posts rounding up some of the most interesting conversations I was fortunate enough to have over the previous week on Twitter. Here’s last week’s about blockchain, news algorithms, and people discovery.

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Above: thinker @LAPrice, CMX community summit founder David Spinks, and marketer Dave Ewart. Three men, but I also got to interact a little with Margaret Cho this week, which was awesome!

This week’s highlighted conversations, which I welcome you to join me in or just check out from your own vantage point, include the following.  If I mischaracterized what anyone was saying, please do let me know. 😉

I’m @MarshallK on Twitter and would love to chat with you, too.

Ethics and the Autonomous Organization

An incredible but under-reported thing happened this month when an organization called The DAO raised $120 million in two weeks (now almost $150m), all from people buying into what’s called a Decentralized Autonomous Organization.  As Wikipedia says, “A decentralized autonomous organization (DAO), also known as decentralized autonomous corporation (DAC), is an organization that is run through a set of business rules that operate within computer code (smart contracts).”

The DAO platform will allow shareholders to vote on proposals for financial and technical resources to be deployed in some really interesting ways.  I’ve heard of decentralized autonomous organizations more and more lately and the easiest example of one to wrap your head around may be an autonomous taxi that drives passengers around, but isn’t owned by anyone in particular, it just caries out a set of rules its been programmed to follow, and makes money, which then goes to the shareholders who funded its creation.

Stan Higgins writes a good overview of some pros and cons of The DAO on Coindesk this week.  My Twitter buddy LA Price puts it differently, though.  “The skynet kickstarter just made it’s first milestone?” he quips, “I wouldn’t be at all certain that the DAO is an unalloyed good thing.”  Thank you for saying that!

I ran a Little Bird analysis to see who in the world of Blockchain (the broad medium in which the DAO will operate) appears most interested in Ethics, and found author Don Tapscott, @BigPrivacy, EtherumLabs, philosopher Melanie Swan, and Michael Parsons at the top of the list.  Good to know.

One Cool Community Building Hack

I posted this poll this week and thought the results were real interesting.

David Spinks replied, which led me to visit his profile which led be to his pinned Tweet – which I absolutely LOVE.

When The Chips Are Down, Social Media!

I was marveling at how few people had wrapped their heads around the great ideas articulated by Chris Boudreaux and Constantin Basturea of EY in this post where they explain just one of countless examples of ways that listening to the social web offers tons and tons of value to people throughout any organization. Why are we just now figuring that out?!? One of my co-workers told me they thought it was because social media is still being staffed as an entry level position. So I asked in a couple of Twitter polls.


My favorite response to all of this? Dave Ewart’s words: “In other words: ‘Would you give the most visible role in the company to most junior hire?'”

Well said, Dave! When you put it like that, the missed opportunities here seem all the more egregious.

See also: Influential Women in Smart Cities

I had a great time researching this blog post this week and people seemed to really dig it.  It’s much more interesting stuff than I thought when I got started.  Sustainability, money, gender – high stakes.  Check it out.


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Facebook Editors, Surveillance Privilege, and People Finding People: My Top 3 Twitter Conversations This Week

1 Comment 05.14.16

This morning I was looking around the great subscription tech blog The Information and noticed they have a “comments of the week” blog post, where they highlight the best comments posted over the week by their readers.  I love that!  It’s a great way to really dig into the value that great community conversation offers – and a great way to encourage more.  It’s like the Letters to the Editor section in print media.

All of our networks are rich with opportunity but almost all of us fail to tap into them enough.  I need to be talking to my professional advisors more than I do – but I also want to dig into the inbound conversations I’m having online more than I am.

Toward that end, I want to try doing something inspired by The Information – but based on the place online I’m most active: Twitter.  Thus I offer, for our mutual enlightenment and inspiration, the Top 3 Best Replies I Got on Twitter This Week.  I want to highlight them, put them in context, share the wealth of information available if you follow the people and the content in these conversations, and encourage my network on Twitter (and elsewhere) to meet each other.  I am super grateful to be able to have all these awesome conversations in a given week!

In no particular order…

Gabe Rivera and the Facebook Newsfeed

No doubt you’ve heard the controversy this week over Facebook allegedly instructing contractors editing their super influential top news widget to suppress links to conservative websites.  Jason Calacanis said on This Week in Startups that he thinks a part of it is that many of the conservative sites in question are more focused on commentary than on the kind of original reporting that Facebook wants to highlight.  That’s a fair, well informed guess at part of what’s going on there.

I really like how Gabe Rivera, founder of venerable tech news aggregator Techmeme and great political aggregator Memeorandum, puts it.  Techmeme has had humans helping machines by editing story selection and even headlines for years.  I interviewed his first editor Megan McCarthy 7 years ago.

Gabe Tweets, “A contention (now more poignant): a key avenue for improving News Feed has always been to introduce certain forms of human editorial input.”  I said the winning team is almost always hybrid, intended as an allusion to Tyler Cowan’s writing about human/machine hybrid chess teams, and Gabe replied, “I’m sure it’s hybrid already by some definition. What I’m claiming is per-story moderations could improve NF [newsfeed] experience for all.” (Emphasis added.)  As Cowan says, the future belongs to humble humans collaborating well with intelligent machines.

Andreas Antonopoulos on Surveillance Privilege

I’ve had the incredible privilege this month to facilitate two long conversations between blockchain expert Andreas Antonopoulos and futurist Dr. Wendy Schultz – both, according to our data at Little Bird, the most influential people in the world in their respective fields, blockchain and women futurists.

Antonopoulos told us stories about research into things like mnemonic wallets, where refugees can upload their financial assets into the blockchain, flee across international borders, then retrieve their money later using nothing but a 12 word passcode they have memorized.  And multi-signatory property ownership based on the blockchain, which has been used for example in societies where women have traditionally not been allowed to own property.  With multisig Bitcoin wallets, if one woman’s husband tries to take her property, he’s unable to without the signatures of the other 6 women who all own it together.  Incredible.

I haven’t been able to share these inspiring stories anywhere outside of telling everyone I know in conversation, but I did Tweet the following this week: “If you’re not worried about gov & corp surveillance, you’re among a very privileged fraction of people on earth,” says @

Some people were unclear on what that meant, but Andreas stepped in to the Tweet stream and clarified really well. “Everyone is surveilled. Often that surveillance is by oppressive/brutal governments. Ours isn’t (yet) = privilege.”  As he said in a conversation we had this month, there are 7 billion people on earth and most of them do not have the privilege of shrugging at surveillance.

Sylvian Carle on the Social Graph

I found myself looking at the Likes tab on a few cool peoples’ Twitter profiles on my phone this week and was struck by what a goldmine it is.  It’s another case of getting to leverage someone smart’s judgement and ride along to discover what they discovered.  I said “I spend far too little time on other peoples’ Likes tabs, and I bet you do too.”

To that I got a great reply from Twitter developer advocate turned VC Sylvian Carle, who added “and follow, for people with a small follow list (less than a few hundreds).”  By that he means looking at who the people you follow are following themselves, in particular the really discerning people who follow less than a few hundred people.  Another great reminder.  Back when I was working as a journalist I used to regularly visit the “following” page on the Twitter profiles of rival writers like MG Siegler and Liz Gannes.  They’d meet people face to face in Silicon Valley and follow them on Twitter, then I’d discover them and learn about new companies that way.  Finding the people followed by experts and influencers is core to the discovery power we’ve built at Little Bird, too.  Here’s who Sylvian’s following – some really interesting looking technologists and startups.


Ok, I was going to write about the top 5 conversations I had this week but just putting these 3 in context has taken a good chunk of time.  I also really appreciated threads from Matt Heinz on inspiring B2B marketing thought leaders, Todd Barnard on connections between artificial intelligence, Marshall McLuhan, Flaubert and Voltaire, Ethan Jewett on influencer data analysis and male dominance, Richard MacManus on the distribution of his great new email newsletter Augment Intelligence, my former co-worker Nate Angel on the gender gap in data capture, Adam Duvander on dreams coming true in geolocation APIs and VC Semil Shah on Lemkin bravado, startup growth and scale.

I love Twitter so much!  You should come join me there for fascinating conversations about the future, throughout the day while we work.  I’ve been really busy this month so my numbers are down on Tweet frequency (by 13%) and mentions (24%).  But none the less: the network is rich with opportunity.  And as I say in the tweet I pinned:


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How good are you at predicting things? Here’s my Brier Score for the week

0 Comments 04.30.16

HBR ran a great article about improving the forecasting abilities of teams this week, (Superforecasting: How to Upgrade Your Company’s Judgement) I highly recommend it, and one of the most interesting tools discussed was something called the Brier Score. It’s an easy way to quantify how well you are doing at accurately forecasting the outcomes of your actions.  It’s pretty simple.  I kept track of my predictions at work and home over this past week and calculated my score, I’ll be excited to see if I can improve it week over week.

I scored a .78 this week over 4 predictions.  You want to get as close to zero as possible. I was wrong about one thing and it really dinged me.

Here’s how you do it.  Write down a forecast about something you can be either right or wrong about, and a degree of confidence you have about your forecast.  For example, I predicted that I was probably going to be invited to join my wife at dinner last night after an event she’s participating in.  We’d discussed whether that would be the case, and we left it open ended – but I had a 60% level of confidence that’s what was going to happen.

And I was right!  So when you’re right with a 60% confidence level, you calculate your score like this: (.60-1)^2 = .16

Now I also predicted this week that a certain woman I admire a lot on the internet was going to be lukewarm about a suggestion we collaborate on a project.  In part just to experiment, I gave that prediction a 70% probability!

And I was wrong!  She was pretty open to it and we’re doing a little experiment together that’s super cool.   I’m really glad I was wrong – but that dinged my Brier Score badly.  When you’re wrong with a 70% confidence level it’s (.70-0)^2=.49.  And we’re looking for as close to zero as possible.  Ouch.

So this week I tracked 4 predictions with confidence levels ranging from 60% to 80% and I was right about the other two, so I added them up and my total score for the week was .78.  We’ll see if I can get it below that next week.

I gave myself some feedback on them where I could, and next week I’m going to think a little harder before committing to predictions.  I’d like to see if there are variations of the Brier Score, or if I should adapt it, to take into consideration the significance of the predictions.  Some of the things I made forecasts this week were much more important than others.

A few other thoughts:

  • Putting more thought into predictions so I’m more confident in them will make my score better when I’m right.
  • Without some normalization, every prediction you make impacts your score negatively.  I want to be thoughtful and keep track of many things throughout the week, so maybe I should say my score was .195 across 4 predictions.
  • There’s more to this but I haven’t drank enough coffee this Saturday morning yet to go much more in depth
  • The HBR article suggested you do this kind of thing with groups of people and figure out who’s best at forecasting.  It also suggested that groups collaborate and receive as little as an hour of structured training on avoiding faulty thinking patterns.  The authors found that those conditions dramatically improve success.
  • I love models like this – they are so powerful and useful!

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Social listening tips for B2B marketers

0 Comments 04.07.16

I’ve been nominated for the awesome B2B News Network’s Social Listening Influencers Index (nominate someone you love, I swear I don’t know who nominated me but now I love them). When asked questions by the press, there’s always an opportunity for a blog post, too!  (See Dave Winer’s Why I Don’t Do Interviews)

Here are my answers to the questions they asked, I hope you find them useful and check out B2B News Network – they’re a good site.  And I don’t say that just because they gave Little Bird a glowing review!

  1. How can professionals become better social listeners?

A few tips from my experience:

Find credible experts on social media and listen to what they talk about, don’t just listen for the mention of your brand’s own name.

Second, try making a habit of reading 3 or 5 messages in your stream for every 1 you post.

Third, turn on mobile push notifications for selected influencers on Twitter – you’ll really get to know them and the cutting edge of your market that way!

  1. How did you become proficient at social listening? 

The method I’ve developed over the years is: (1) oversubscribe, (2) then create a filtered feed of just the highest-priority sources. Then (3) create a system that makes it easy to see almost everything from the high priority list (mobile push notifications, browser bookmarks). Then (4) dip into the general non-priority feed from time to time to see what serendipity delivers.  Repeat! Engage!

  1. What’s different about listening for brands vs b2b? 

There’s a lot of overlap, but in B2B – a single conversation can include insight that informs a company’s whole strategy or opens up a big line of business.  A mention is less likely to drive a lot of direct sales (I don’t know how much that really happens in B2C either, directly) but is more likely to help inform would-be-buyers when they see favorable mentions showing up in search.  So listen, engage, and earn supportive engagement in return.  Also, B2B influencers may be more interested in two way dialogue, whereas B2C listening is more closely associated with immediately transactional relationships.

  1. How does social intelligence help YOUR business? What do you use it for? 

We use social intelligence to look for opportunities; opportunities to find new customers, opportunities to be informed early about important trends, and opportunities to help the customers we already have with their efforts.  By systematically watching the social web for a combination of source-based, validated, popular, and keyword-laden conversations, we discover all kinds of opportunities.

  1. How is social intelligence related to content marketing?

Social intelligence surfaces opportunities to curate content and build relationships upstream and downstream.  It surfaces inspiration of topics, trends, keywords, and collaborators for all kinds of content marketing efforts.

  1. What is the best way to reach/follow you? (Twitter handle, email, etc)

@Marshallk, and 1-503-703-1815


How’s that look to you? Disagree with any of the above? Thanks for stopping by!

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I’ve been tweeting for 9 years! Here’s what I’ve learned

1 Comment 03.07.16

It’s been 9 years today that I’ve been on Twitter. It’s a huge part of my life.  So much so that I started a company based on it.  I wrote over on the Little Bird blog today all about some of the things I’ve learned over these 9 years.  I hope you’ll check it out – and check out Little Bird.

I want to make sure you know about NTEN - the Nonprofit Technology Network.

NTEN helps nonprofits learn to use the web effectively.