Harold Jarche

“the total decoding and synthesizing of reality”

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A seminal moment in my work came when I saw my first web page on a computer at Montreal’s CRIM in 1994. I finally saw computers as things that connect people around the globe. From here I completed a Master’s degree focusing on how people learn at work with information technology.

The next significant moment arrived with social media. I started blogging and sharing online. When Twitter came along it changed my relationship with hundreds of people. Social media platforms became the great connectors. But now in 2023 we know that much of the web is comprised of surveillance and tracking tools that are designed to influence our behaviour, especially our purchasing behaviour.

In whither Twitter, I wrote that more important than any single platform is our collective ability to seek diversity, think critically, and learn socially. For now I am staying on Twitter and watching the show, muting and blocking with abandon. But we know that platforms like Twitter can undermine democracy and spread disinformation and propaganda. Perhaps that is why Musk bought the company.

I had another seminal moment when I watched The AI Dilemma recorded on 9 March 2023. It shook my understanding about the current state of machine learning, which I thought I sort of understood conceptually. Tristan Harris and Aza Raskin, from The Center for Humane Technology, present on the new force that has been unleashed by several global companies with no regulatory oversight — the Generative Large Language Multi-modal Model (AKA Gollem-class AIs).

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curiosity trumps knowingness

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“I put forward formless and unresolved notions, not to establish the truth but to seek it.” —Michel de Montaigne

The perspective of perpetual beta is to make sense of our experiences by formulating models to help our sensemaking while at the same time being ready to discard these beta models as new information is discovered. It may not be the most comfortable way to understand our world but it may be the most adaptive. This perspective informs the personal knowledge mastery (PKM) framework, which has evolved since 2004.

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adding human value

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In 2013 I posed this question — ask what value you can add — when it comes to sharing information and knowledge. Ten years later and what has increased is the noise, especially misinformation, disinformation, and propaganda. The release of tools like generative pre-trained transformers (GPT) will only increase the amount of noise online. It is becoming even more important to add value before we share information, especially confirming that the information is valid and reliable. As more machines create ‘answers’ to our questions, we should focus on adding human value.

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understanding the hype and hope

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I have been keeping an eye on the hype & hope around artificial intelligence (AI), especially:

  • ML — machine learning
  • GPT — generative pre-trained transformers
  • GAI — generative artificial intelligence
  • LLM — large language models

“I’ve long been a fan and found value in AI / ML and its capabilities. Learning and finding patterns and causal patterns that in time can lead to outcomes that are problematic (a large fleet of vehicles with hundreds of sensors feeding and AI / ML to detect early engine, transmission, or other failure to address before more expensive damage or at a human cost). Generative AI from large language models is missing core pieces still and had knock-on effects that are really problematic with its lack of understanding facts (or multitudes of facts and truths), but more problematic is it blunts human learning and cognition.”
—Thomas Vander Wal 2023-03-18

How Technology Influences Social Networks

Stewardship of global collective behavior —2021-06-21

“Human collective dynamics are critical to the well-being of people and ecosystems in the present and will set the stage for how we face global challenges with impacts that will last centuries. There is no reason to suppose natural selection will have endowed us with dynamics that are intrinsically conducive to human well-being or sustainability. The same is true of communication technology, which has largely been developed to solve the needs of individuals or single organizations. Such technology, combined with human population growth, has created a global social network that is larger, denser, and able to transmit higher-fidelity information at greater speed. With the rise of the digital age, this social network is increasingly coupled to algorithms that create unprecedented feedback effects.”

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looking in the mirror

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In a local op-ed I recently concluded that curriculum change in education is like fixing a plane in mid-flight especially when the first principles of public education are not clear while the curriculum is the same for everyone. Basically, standardized curriculum is the confinement of the human experience. It is a blunt tool that winds up bullying someone. But nobody can take the government to task on first principles when they do not exist. Much of the blame lies with the professionals managing the system. They have handed over this cobbled-together system to each successive government to do their political whims. And so it will continue.

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pilots and copilots

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Simon Terry has a short post on Microsoft’s new Copilot and how we should be careful in fully adopting some of these generative AI tools.

LLMs [large language models] are improvements on past tools but are hardly perfect. In a world where the volume of information means many people scan everything, we need to remain alert for the risks of the models false inferences or patterns gone awry.

In the history of aviation, it became apparent that pilot personal relationships are critical to avoiding dangerous incidents. Authoritarian cultures meant senior pilot mistakes went devastatingly unchallenged. —Microsoft Co-pilot

I mentioned pilot training on a post recently — experience cannot be automated. I concluded that automation, in all fields, forces learning and development out of the comfort zone of course development and into the most complex aspects of human learning and performance. On that post is also a quote by Captain Sully Sullenberger, the famed pilot who safely landed a passenger jet on the Hudson River. A movie was made about this, which included the subsequent safety investigation. Tom Hanks plays Sully and in this sequence of videos we see the difference between human cognition of experienced pilots versus the best software/hardware simulation of the day. There is no comparison.

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capitalism > automation > gpt

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In my last post I covered in detail how ideas become ideology.

“Ideas lead technology. Technology leads organizations. Organizations lead institutions. Then ideology brings up the rear, lagging all the rest — that’s when things really get set in concrete.”—Charles Green (2009)

Today, the underlying ideology is capitalism. It drives the actions of governments, such as claiming that companies are job creators.

“There is no such thing as a ‘job creator’. There are employers, who hire employees, *because they need them*. And then employers pay the employees less than the value they generate. That’s the system. How did we get to the point at which people behave as if the wealthy are giving a gift to working people? I realize it’s not a new attitude, but it remains proudly f’d up.” —Mark Sumner

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how ideas become ideology

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Several times I have referred to this observation about how ideas connect to ideology.

“Ideas lead technology. Technology leads organizations. Organizations lead institutions. Then ideology brings up the rear, lagging all the rest — that’s when things really get set in concrete.”—Charles Green (2009)

Here are some examples of these shifts.

Ideas lead technology

Hedy Lamarr invented spread spectrum technology in 1941 but its value as a technology accelerated half a century later as it would, “galvanize the digital communications boom, forming the technical backbone that makes cellular phones, fax machines and other wireless operations possible.”

Peter Senge’s book, The Fifth Discipline, ushered in the idea of the learning organization but it was only recently that organizations had the Web 2.0 technologies to enable distributed team learning or share systems-thinking across the enterprise.

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reflecting on a decade past

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Looking back on my blog posts from 10 years ago — March 2013 — here are some that remain valid [in my opinion anyway].

perpetual beta is the new reality

Work in networks requires different skills than in directed hierarchies. Cooperation is a foundational behaviour for effectively working in networks, and it’s in networks where most of us will be working. Cooperation presumes the freedom of individuals to join and participate so that people in the network cannot be told what to do, only influenced. If they don’t like you, they won’t connect. In a hierarchy you only have to please your boss. In a network you have to be seen as having some value, though not the same value, by many others.

we need to learn how to connect

Increasing connections should be a primary business focus. It should also be the aim of HR and learning & development departments. Connections increase as people cooperate in networks (not focused on any direct benefits for helping others). Diverse networks can emerge from cooperation that is supported by transparency and openness in getting work done. Basically, better external connections also make a worker more valuable internally. Fostering this perspective will be a huge change from the way many organizations work today.

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