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!