“moments, not models”

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On the last Friday of each month I curate some of the observations and insights that were shared on social media. I call these Friday’s Finds.

“The ability to learn from experience in the present — from moments, not models — is what is needed when the past has become a hindrance and the future is unclear.” —Gianpiero Petriglieri via Shaun Coffey

“The kind of intelligence [AI] we’re developing is very different from our intelligence. So it’s this idiot-savant kind of intelligence.” —Geoffrey Hinton

“The great merit of the capitalist system, it has been said, is that it succeeds in using the nastiest motives of nasty people for the ultimate benefit of society.” —E.A.G. Robinson (1941) via QuoteInvestigator

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warning — effort required

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Seth Godin discusses Cliffs Notes and how these could be a path to better understanding.

Used as intended, Cliffs Notes and Quicklit were a gold mine of insight. They opened the door for real understanding, and often got to the heart of the literature better than an overworked high school teacher might be able to. —The Cliffs Notes Paradox

But he also notes that even with the widespread availability of these notes, insight in overall society has not improved. When I was in college, I majored in the Arts while most of the students were in engineering or science at Royal Roads Military College. Our cohort was about 25 students and on entering second year, I was given a barrack box filled with Cliffs Notes (and Coles Notes) for our entire curriculum. As the ‘keeper of the notes’ I was responsible for their safe-guarding and adding to the collection. It was a great responsibility.

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diversity > learning > trust

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“What is dumbing so many people down?” asks Henry Mintzberg. His explanations 1 and 2 [quote below with my emphasis added] resonate with me, as I have promoted the idea that we need to connect our work, our communities, and our networks to make sense by engaging with people and ideas. The core of this is curiosity, especially about other people, as well as ourselves.
Be a curious learner — about ideas, people, and oneself

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getting scraped

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The Washington Post looked at what information feeds Google’s chatbots, particularly the C4 Data Set which scraped 15 million English language websites. This is the ‘artificial intelligence’ that feeds the chat bot — stuff that people have written and posted online. All of this is taken without authorization — “The copyright symbol — which denotes a work registered as intellectual property — appears more than 200 million times in the C4 data set.”

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chatting about gpt

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These are some highlights from several sources focused on large language models (LLM) and generative pre-trained transformers (GPT) — all published in 2023. It might be useful to first read — Nobody knows how many jobs will “be automated” Whatever that even means.

But “AI will increase labor productivity while forcing a small number of people to find new jobs” is not the kind of story that goes viral on social media, while “300 million jobs will be lost” definitely is that kind of story. People love to read about the impending apocalypse, and it’s the media’s responsibility not to indulge that desire … Instead of telling us who will be “automated”, they [A Method to Link Advances in Artificial Intelligence to Occupational Abilities – 2018] tell us who’s more likely to be affected by automation in some way. Obviously we’d like to know whether it’ll be a good way or a bad way. But the truth is that no one knows that yet, and economists do the world a service by refusing to pretend that they do know.

ChatGPT is about to revolutionize the economy

The optimistic view: it [GPT] will prove to be a powerful tool for many workers, improving their capabilities and expertise, while providing a boost to the overall economy. The pessimistic one: companies will simply use it to destroy what once looked like automation-proof jobs, well-paying ones that require creative skills and logical reasoning; a few high-tech companies and tech elites will get even richer, but it will do little for overall economic growth.

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our machines are tools and not our friends

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Do I contradict myself?
Very well then I contradict myself,
(I am large, I contain multitudes.)
—Walt Whitman (1855)

For over a decade, social media have helped me explore different aspects of my learning and my profession, much more than I could have on my own or in my community. I often feel more affinity for some of my online connections than for my local neighbours. Living with contradictions can help develop critical thinking. Social media have enabled more of us to live like artists, constantly redefining ourselves and our work. Despite what is happening at Twitter, other options for connecting online are emerging, such as the open covenant ‘fediverse’ and Mastodon.

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“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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