SocialLearning

Social learning

constant doubt and outrage

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When I was visiting Rome in 2012 I met a fellow tourist, an older gentleman from Australia, who told me that he had stopped a pick-pocket on the train who was trying to lift his wallet. He had cried out and grabbed the thief’s hand. As the train came to a stop, the locals on the train created a human wall and forced the thief out, while at the same time calling for the police. They then apologized on behalf of their city. Rome is a 2,750 year-old community that keeps on trying, in spite of its challenges, because its people believe in the city. This is how most humans act — cooperatively — most of the time, as this is part of our common social suite.

The Internet of Beefs (IoB)

But we are also influenced by our social networks and when these become what Venkatesh Rao calls the Internet of Beefs (IoB) then we collectively drag ourselves down. Rao defines two groups — Knights and Mooks — who continuously do battle on digital social media. Each Knight has many follower Mooks, and these Mooks do battle in the Knight’s name. Rao says that one such Knight is Nassim Nicholas Taleb.

“And in one corner by himself, of course, is Nassim Taleb beefing with all comers on all topics … Taleb muddying the factional boundaries of the culture war is one of the few genuinely amusing theaters of the conflict on the IoB. The blast radius around his twitter feed is not a safe space for anyone besides members of his own cult of Mesopotamian personality.”  —Venkat Rao

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solving problems together

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Most situations at work can be considered from the perspective of — is this a known problem or not? If it’s known, then the answer can be looked up or the best person can be found to deal with it. The answer may even have been automated or outsourced. Known problems require access to the right information to solve them. This information can be mapped, and frameworks such as knowledge management help us to map it. We can also create tools, especially performance support systems to do the work and not have to learn all the background knowledge in order to accomplish the task. This is how complicated knowledge continuously gets automated.

But if it’s a new problem or an exception, then the worker has to deal with it in a unique way. The main job of most knowledge workers is to solve problems and deal with exceptions. Exception-handling is becoming more important in the networked workplace. While software can handle the routine stuff, people — usually working together — are needed to deal with the exceptions. Exceptions require cooperation and collaboration to solve.

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mapping stories

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This past week I have been reading interview transcripts for a client. After reading several of these 20-page documents it became clear what was able to hold my attention — stories, especially first person accounts. I also remember the stories much better than the general discussions or advice given. One of the simplest definitions of storytelling is by Jonathan Gottschall in The Storytelling Animal — Story = Character + Predicament + Attempted Extrication.

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reflecting on the future of knowledge

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I started my independent consulting practice in 2003 and one of the first books I purchased was — The Future of Knowledge: Increasing Prosperity through Value Networks by Verna Allee (2002) Butterworth-Heinemann (ISBN: 0750675918). The topic of value network analysis and the leading role that Verna Allee played came up in some recent discussions in one of my online communities of practice. So I decided to re-read the book that planted so many ideas in my mind. Here are some of the highlights, almost 20 years after Verna started writing The Future of Knowledge.

LESS COLLECTION, MORE CONNECTION

One of the primary requirements for supporting knowledge work is to ensure that people have the tools and information they need to complete their everyday tasks. But, another equally important goal is to provide appropriate technologies for collaborative work in a complex global environment. The more complex modes of knowledge cannot be turned over to databases and automation. They are accomplished by people through active and immediate conversation and interchanges. Connective technologies enable us to link up with our peers so that we may weave the threads of our understanding together into new synthesis and insights.

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from training to learning

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While social learning may be one of the currently hot new trends in the education and training fields, we have known for a while “why tried-and-true training methods don’t work anymore”, as discussed by Brigitte Jordan (1937-2016) in the mid-1990’s while working at the Institute for Research on Learning. Here are the highlights — From Training to Learning in the New Economy.

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connecting the curious

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Why do students often ask — will this be on the test? It’s because they have figured out the game called education. They are told what to study, what is important, and for how long. Each school year they play the game anew.

Why are some — a significant percentage — employees not motivated to work? They too have figured out the game. Venkatesh Rao, in The Gervais Principle describes this large base of most companies — the losers.

“The Losers are not social losers (as in the opposite of ‘cool’), but people who have struck bad bargains economically – giving up capitalist striving for steady paychecks. I am not making this connection up … The Losers like to feel good about their lives. They are the happiness seekers, rather than will-to-power players, and enter and exit reactively, in response to the meta-Darwinian trends in the economy. But they have no more loyalty to the firm than the Sociopaths. They do have a loyalty to individual people, and a commitment to finding fulfillment through work when they can, and coasting when they cannot.”

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adding value with teams

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In working collaboratively & learning cooperatively I noted that team collaboration requires the transparent sharing of knowledge — using enterprise social networks and other technologies — so that everyone on a team knows what is going on and why. Decisions, and why they were made, are shared. New processes and methods are co-developed to create emergent practices. This method of work has to be supported by management by enabling — innovative and contextual methods, the self-selection of the most appropriate tools and work conditions, and willing cooperation between workers.

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co-learning is better than marketing

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Work is learning, and learning is the work. Marketing, for the most part, is about learning. What’s interesting is that ” … the content developed by most marketing departments is used in less than 7 percent of all buying decisions”, according to McKinsey, as cited in The Hypersocial Organization. So it’s not about the content. It’s all about the human connections.

As the Cluetrain Manifesto (1999) began with its first of 95 theses, “Markets are conversations”. Cluetrain continued with thesis #11 — “People in networked markets have figured out that they get far better information and support from one another than from vendors. So much for corporate rhetoric about adding value to commoditized products.” We learn best from each other in trusted relationships.

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more than re-skilling

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Here is the advice of the co-founder of Degreed on a ‘workplace self-training paradigm‘.

First, encourage them to think of reskilling as a game — one they now have more control over winning …

Next, help workers manage their skills with regular checkups to evaluate their current expertise against market conditions …

Finally, work with employees to pinpoint opportunities to put their new skills into action.

It reminded me of advice that Lilia Efimova gave fifteen years ago — on which I based I my own PKM framework — which is a broader approach to workplace learning than merely looking at work from a training or re-skilling perspective.

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relatedness for knowledge sharing

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In the HBR article Why Employees Don’t Share Knowledge with Each Other the authors find three main reasons [research paper behind a paywall]. First, people share knowledge when they are autonomously motivated, and not directed to do so, or pressured by peers. Second, cognitively demanding work is shared more frequently. Third, knowledge is shared best between equal peers and not with those who are dependent on the sharer. While this research was done with 394 Australian workers at various locations, as well as 195 Chinese workers at one company, it is reflective of older research — self-determination theory — conducted by Edward Deci and/or Richard Ryan from 1971 to 2018.

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