Learning

Learning

adapting to the network era

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The TIMN model developed by David Ronfeldt states that people have only organized in three basic forms — Tribes, Institutions, Markets — and that a fourth form appears to be developing in societies — Networks. I have suggested that new forms appear and are adopted when the dominant form of communication changes. Institutions developed with the advent of Writing. Markets grew to dominance with Printing. It looks like digital (electric) communications are pushing us toward Network forms.

I use Marshall McLuhan’s Laws of Media and his tetrad for sensemaking to understand the effects of new communication technologies.

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algorithmic amplification

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What is the impact of constant misinformation on consumer social media? Dave Troy discusses the effects in a long Twitter thread:

“Disinformation is the operational end of a process designed to break down society and radicalize it into cultish forms. This process leads people away from truth. We can’t address this process by distributing truth; the cure for disinformation is not simply truth … Truth is, rather, a goal we must arrive at … We need to turn our attention to what is being lost: social ties, social trust, social capital … We don’t look enough at the relationship between identity, in-group, and belief. They are all reflections of the same thing and you can’t alter one without altering the others. This is why injecting garbage breaks down social ties and alters belief and identity. Sufficiently radicalized, people won’t recover their prior social connections, leaving them stranded on ‘islands of dissensus’. There is no natural pathway back from this. It’s a one way process. Throwing truth at them doesn’t restore lost social/family ties; it alienates them.” —Dave Troy

Twitter recently revealed — Examining algorithmic amplification of political content on Twitter — that its algorithm that decides what you see in your stream can have a social and political impact.

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aligning before learning

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This week I took Alastair Somerville’s workshop on Network Thinking. The format is based on a podcast, followed by a discussion on Zoom, supported by a card designed by Alastair. I must say it was quite effective. A key actionable insight I gained from our session was the importance of Alignment — “Sharing a moment to align a sense of place, of time, and togetherness. Rooting learning in a shared, but still personal, sense of being”. This reflects many aspects of PKM as well as social learning.

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the social sweet spot

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Continued from — social learning powers distributed work.

Social learning is about people in trusted relationships sharing and building collective knowledge. It is part of our common evolutionarily developed ‘social suite’.

In Blueprint: The Evolutionary Origins of A Good Society, Nicholas Christakis argues that this coevolution has equipped us with a “social suite” of traits that arose through genetic evolution and that have been amplified by cultural evolution, which has in turn influenced our genetic evolution toward propensities that support the social suite. These include the “capacity to have and recognize individual identity,” “love for partners and offspring,” friendship, social networks, cooperation, “preference for one’s own group (‘in-group bias’),” “mild hierarchy (that is, relative egalitarianism),” and “social learning and teaching.” —Howard Rheingold

These seven traits identified by Christakis can be arranged in how valuable they are to overall society.  Self-identity has high individual value while social learning is how we developed our second evolutionary strand — shared culture and knowledge.

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social learning powers distributed work

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Distributed work is here to stay, because many people like it, the pandemic is not over and there will be others, and market forces will seek to maximize profits and reduce labour costs. But Zoom calls all day are not going to create work environments where knowledge workers can deal with complex problems or create innovative solutions. The key to distributed work is social learning.

Distributed work is driving a work-from-anywhere culture and is increasingly reliant on asynchronous communication, as people move to multiple time zones. In order to share the necessary implicit knowledge needed for complex work, trust has to be developed. People only share with others they trust. This trust takes time to develop between people. How can they do this when they are not in the same office?

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‘pointsification’

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In 2013 I wrote that work is already a game. Adding badges or other extrinsic motivators to professional learning only detracts from the real game. Gamification also creates incentives that, when removed, may result in going back to previous behaviours.

In a Twitter thread Ana Lorena Fabrega discusses gamification and suggests that it is often ‘pointsification’.

“Pointsification ties to external motivation—free time, tasty treats, or bragging rights. It’s taking the things that are least essential to games and making them the core of the experience.
The problem with pointsification is that it’s not sustainable.

While it may help tweak some behaviors in the short term, it doesn’t work for long enough to build actual skills.

Pointsification ‘solutions’ miss the heart of what makes a gameful experience effective for learning.”

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ITA Jay Cross Award 2021

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internet time allianceThe Internet Time Alliance Award, in memory of Jay Cross, is presented to a workplace learning professional who has contributed in positive ways to the field of Informal Learning and is reflective of Jay’s lifetime of work.

Recipients champion workplace and social learning practices inside their organization and/or on the wider stage. They share their work in public and often challenge conventional wisdom. The Award is given to professionals who continuously welcome challenges at the cutting edge of their expertise and are convincing and effective advocates of a humanistic approach to workplace learning and performance.

We announce the award on 5 July, Jay’s birthday.

Following his death in November 2015, the partners of the Internet Time Alliance — Jane Hart, Charles Jennings, Clark Quinn, and myself — resolved to continue Jay’s work. Jay Cross was a deep thinker and a man of many talents, never resting on his past accomplishments, and this award is one way to keep pushing our professional fields and industries to find new and better ways to learn and work.

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connections trump expertise

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A recent research paper — Orthodoxy, illusio, and playing the scientific game — looks at why it took so long for the mainstream medical community to accept that the SARS-CoV-2 virus is predominantly spread as an aerosol and not through surface transmissions.

Three fields—political, state (policy and regulatory), and scientific—were particularly relevant to our analysis. Political and policy actors at international, national, and regional level aligned—predominantly though not invariably—with medical scientific orthodoxy which promoted the droplet theory of transmission and considered aerosol transmission unproven or of doubtful relevance. This dominant scientific sub-field centred around the clinical discipline of infectious disease control, in which leading actors were hospital clinicians aligned with the evidence-based medicine movement. Aerosol scientists—typically, chemists, and engineers—representing the heterodoxy were systematically excluded from key decision-making networks and committees. Dominant discourses defined these scientists’ ideas and methodologies as weak, their empirical findings as untrustworthy or insignificant, and their contributions to debate as unhelpful. —Wellcome Open Research 2021-05-24

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people, not algorithms

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Can an algorithm defeat an algorithm? One group of European researchers think it can be done. I have my doubts

“The approach involves assigning numerical values to both social media content and users. The values represent a position on an ideological spectrum, for example far left or far right. These numbers are used to calculate a diversity exposure score for each user. Essentially, the algorithm is identifying social media users who would share content that would lead to the maximum spread of a broad variety of news and information perspectives.

Then, diverse content is presented to a select group of people with a given diversity score who are most likely to help the content propagate across the social media network—thus maximizing the diversity scores of all users.” —IEEE 2021-01-21

I believe that any system that can be gamed, will be gamed. Adding another algorithmic layer on platforms designed to manipulate human behaviour will likely result in a continuing game of whack-a-mole, like search engine optimization (SEO). Humans are not machines, and machines (including software) are not humans.

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nature favours large social groups that network their information

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Knowing how to get the answers you need is more important than storing those answers in your head, especially with the shorter lifespan of knowledge these days. What you find when you look something up is probably current. What you already know is more and more likely to be out of date.

A vital meta-learning skill: how to find the answer you need, online or off.

—Jay Cross (2006)

Knowledge is evolving faster than can be codified in formal systems and is depreciating in value over time. One of the ways to deal with this knowledge explosion is to use what we have — our humanity. We have developed as social animals and our brains are wired to deal with social relationships. By combining technology with our brainpower, we can figure things out. We are naturally creative and curious.

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