some thoughts on thinking

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Every fortnight I curate some of the observations and insights that were shared on social media. I call these Friday’s Finds.

“You don’t have to burn books to destroy a culture. Just get people to stop reading them.” —Ray Bradbury, via @holdengraber

@_Amanda_Killan: “Libraries literally aren’t just a place to obtain books for free. They’re one of the few public spaces left in our society where you’re allowed to exist without the expectation of spending money.”

@dougkleeman: “Before you criticize something, find three things you actually like about it first. It works when reviewing creative work, but it also makes you a more pleasant human being.”

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collaborating with the enemy

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Collaborating with the Enemy by Adam Kahane gives a framework of how to work with people you don’t agree with, like, or trust. Kahane developed it through his years of conducting collaboration workshops such as the Mont Fleur sessions to prepare for a post-apartheid South Africa. I read his first book in 2005, Solving Tough Problems, and his latest is similar in that it is short, to the point, and provides practical advice. It is based on some of the failures in his work and professional relationships from which he developed a guiding principle to always “look for disconfirming evidence”.

His framework is relatively simple to understand.

When two or more parties get together to address a problematic situation, they ask themselves a series of questions to understand their options. First they determine if they can change the situation. If so, can they effect change unilaterally, in which case they can force their solution. This happens frequently when governments ‘consult’ people who have no power to effect change.

If they cannot change the situation, then they have two unilateral decisions possible: adapt to what has been forced on them, or exit the situation if possible.

If they can change the situation but cannot effect change unilaterally, then it is possible that conventional collaboration can work, but only if the change can be controlled. This is the basis of a lot of collaboration interventions based on an assumption of control, which is often wrong. This is what Kahane learned through his failures. Even if the engaging parties agree to collaborate, other factors and external parties may subvert their actions.

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the coffee club

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coffee
Last October I suggested that subscribers to this blog could buy me a monthly cup of coffee to support my writing. Several of you have done so: thank you! We now have a private online space to continue our conversations.

To kick off 2018 I have decided to make the beta conversations available exclusively to coffee club subscribers. I will host about 10 online video conference sessions per year, in addition to a private community space for asynchronous conversations. The subjects that we will cover will include technology, media, knowledge, and society, but I am sure we will always find something to talk about. The conversations are recorded for members who cannot make it. I will ensure there is a topic or two at hand before we begin.

So if you find my writing useful, especially for your own paid work, please consider subscribing to the club and buying a monthly cup of coffee for each of us.

This will make you a member of the coffee club, caffeine-fuelled for deeper conversations, for only $10 per month.

Register here

embracing automation

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Automation

Automation, the replacement of human work with human-made technology, has been happening ever since we invented tools. Just as farmhands were replaced by machines 100 years ago, so too will knowledge workers be replaced by networked computers in the next few decades. Last century, those farmhands had the option of moving to the city and working in factories, but what are the alternatives for today’s knowledge workers? It is not likely to be a new job, as the job itself is being made obsolete, underlined by 57 million freelancers in the USA today, accounting for about 1/4 of working-age adults. This is expected to grow to 86 million by 2027 so that freelancers will be the majority of the American workforce.

Automation seems to be accelerating and has been a frequently discussed topic here. But does automation really result in job loss? It appears that where there is elastic demand, so that automation meets increased demand, employment usually increases in an industry. For example, employment at banks increased with the introduction of automatic tellers. But it is not all good news. Some work keeps going away: standardized & routine jobs.

“The evidence suggests that while computers are not causing net job losses now, low wage occupations are losing jobs, likely contributing to economic inequality. These workers need new skills in order to transition to new, well-paying jobs. Developing a workforce with the skills to use new technologies is the real challenge posed by computer automation.” —James Bessen

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friday’s finds 2017

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Every second Friday I review what I’ve noted on social media and post a wrap-up of what caught my eye. I do this as a reflective thinking process and to put what I’ve learned on a platform I control: this blog. Here are what I consider the best of Friday’s Finds for 2017.

Quotes

“Democracy has to be born anew every generation, and education is its midwife.” —John Dewey (1916)

“No one is going to give you the education you need to overthrow them.” —Assata Shakur, via @IamMzilikazi

“The point of modern propaganda isn’t only to misinform or push an agenda. It is to exhaust your critical thinking, to annihilate truth.” —@kasparov63

“History is not another name for the past, as many people imply. It is the name for stories about the past.” —A. J. P. Taylor via @RayBoomhower

@DonaldHTaylor: ‘In Turkish you never ask “Did you understand me?” It’s rather rude. Instead, you say “Anlatabildim mi?” – Was I able to explain?’

“Human beings augmented by other human beings is more important than human beings augmented by technology” —@eskokilpi

“We live in capitalism, its power seems inescapable – but then, so did the divine right of kings.” –Ursula K. Le Guin via @HaymarketBooks

@Richard_Florida: “Cities need to be places of chance encounter and eccentricity, rather than exclusivity and segregation.”

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constantly learning nodes

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Here are some thoughts about learning that I developed on this blog the past year.

We lack good models for organizing in a networked society. Many people are turning back to older, and outdated organizational models like nationalism and tribalism in an attempt to gain some stability. But most of our institutions and markets will fail to deliver in a network era society because they were never designed for one.

Perhaps the only unit of organization that is up to the task of working and living in networks is the individual human (the node). Change starts from within, yet almost all organizational transformation initiatives look at systems. Too much focus is on digital transformation and not human transformation. How do people transform? By doing things differently.

The biggest challenge we face is in educating citizens for the network era. Marina Gorbis in The Nature of the Future suggests four core skills:

  1. Sensemaking
  2. Social and emotional intelligence
  3. Novel and adaptive thinking
  4. Moral and ethical reasoning

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talent, not labour

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The latest edition of the European Public Mosaic: Open Journal on Public Service is focused on talent management. My article in the journal is entitled ‘Talent, not Labour, is the Future of Work’. Here is the abstract.

As routine and procedural work gets automated, human work will be increasingly complex, requiring permanent skills for continuous learning and adaptation. Creativity and empathy will be more important than compliance and intelligence. This requires a rethinking of jobs, employment, and organizational management.

Read the article online (page 27):

Download the PDF: Talent, not Labour

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perpetual beta 2017

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Blogging is one way I make sense of the world. This past year I wrote about 120 posts on various topics. What follows is a summary of some of my thoughts during 2017. My ways of seeing the world have changed over the years and blogging has helped to keep my thoughts in a state of perpetual beta: strong ideas, loosely held.

Relatedness

One effect of the network era, and its pervasive digital connections, is that networks are replacing or subverting more traditional hierarchies of our institutions and markets. Three aspects of this effect are: 1) access to almost unlimited information, 2) the ability for almost anyone to self-publish, and 3) limitless opportunities for “ridiculously easy group-forming“.

The desire to relate is what drives people to support global social movements on one hand and to take shelter in tribal identity politics on the other. In politics, social media extend participation but also make information manipulation by small motivated groups much easier. Understanding this deep desire to relate to others should be foremost in mind in understanding human dynamics. We will not have organizational transformation, or political reformation, without people feeling like they belong. To counter Tribal populism, we also need to appeal to emotions and our feelings of relatedness. The same goes for education and learning.

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looking to the past for the future

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“Pass on what you have learned. Strength, mastery. But weakness, folly, failure also. Yes, failure most of all. The greatest teacher, failure is. Luke, we are what they grow beyond. That is the true burden of all masters.” —Master Yoda, Star Wars: The Last Jedi

Leading by allowing failure is a feature of all the strong female characters in the latest Stars Wars movie. These women rebuke several male characters, while still having positive feelings for them [apologies for the spoiler]. This type of leadership: listening, watching, understanding, and caring stem from our 90,000 year history in oral societies. Our written, print, and digital eras combined, have been much shorter. We should look to the deep past to understand the present and future.

“Swedish scientists have done extensive research on this and they found we first lived in small groups of 20 to 100 people who in any given week averaged 2.5 days for gathering and hunting and 4.5 days on talking. The conclusion they came to from this data was that the brain, the neurological system, and our hormonal systems have had 90,000 years of programming us for talk and collaboration, and only 10,000 years for competition and fighting.” —World Cafe 2007

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connecting work, learning, and life

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The 70:20:10 reference model states that, in general, what we learn at work comes 70% from experience, 20% from exposure to new work, and 10% from formal education. At the 70:20:10 Institute [disclosure: I am a service partner], the basic approach is to start with the 70 (experience) because this is where learning and working are most connected. When we learn as we work, at the moment of need, then we learn in context and we remember what we have learnt.

“70:20:10 uses the performance paradigm to achieve working = learning in the context of the workplace and thus to contribute to the desired organisational results. In our practice we have seen many applications of the learning paradigm in 70:20:10, which is not the intention. The paradigm starts from the idea that skills need to be developed so it begins with the 10 and uses these to flesh out the 20 and 70.

This is a back-to-front approach. In 70:20:10, it’s not learning or the 10 that are central, but rather the principle of working = learning. Here again it is about achieving the desired performance improvement in the context of the individuals or teams who want to work better together.

70:20:10 is about performance enhancement: the performance paradigm starts with the desired organisational results and uses performance consulting to establish what interventions are needed in the 70, 20 and 10 to improve individual and organisational performance. This should not be confused with the learning paradigm approach in which learning is added to working. In the performance paradigms, working = learning is achieved using such models as performance support, microlearning and social learning. This makes it possible to learn at the speed of performance.” — 70:20:10 Institute

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