I would never describe myself as a ‘techie’. In my second year of undergraduate studies (1978) I failed my computer programming course in Fortran Watfor & Watfiv [that was with punch cards and a terminal that sent the batch to Vancouver and returned results in 24 hours] but the professor gave me a pass if I promised to never take a programming course again. I have kept true to my word all of these years.

You could say that I am not one to jump on the next technology craze. I ignored computers through the 1980s and into the 1990s. However in 1994 I saw my first website at the Computer Research Institute of Montreal (CRIM). It was a revelation. For the first time I saw how computers could connect people. During my undergraduate years nobody explained the relevance of computer programs. It was all about making some arcane program work. I could not relate my life to any of these programs. The web made sense to me.

I need to understand why I am learning something or I just tune out. For example, I was sent to French language training in the Summer of 1978. We were given an aptitude test to see how well we were suited for learning a second language [by the way, English is my second language, having spoken only German until I went to school]. There was a section of the test where a number of Kurdish words were presented and we were told to memorize them. I did not bother. As a result I did poorly on the short-term recall part of the test and was put into the ‘slow learners’ section. By the end of the language training of 13 weeks I went from unilingual to fluently bilingual, probably the only person to do so in our cohort. Part of the reason for my success was my motivation — I had a girlfriend who could not speak English

The advent of the web got me into blogging and using social media. Much of the latter has turned into a mess but the ‘fediverse’ is a light in the darkness — meet me on Mastodon. I still believe in the value of connecting people and sensemaking together. The technology always takes the back seat.

Hence, I am taking a very slow approach to AI, GPT, LLM , etc. I just don’t see the inherent value. A few big players have all of the control over a ‘black box’ technology that nobody can see. I am not a Luddite — though the Luddites were awesome IMO — but I cannot jump on the AI bandwagon until I see its value. So far, I only see value accruing to a few multinational technology companies.

More thoughts on AI/GPT/LLM:

GPT-3 through a glass darkly

capitalism > automation > gpt

chatting about gpt

I write therefore I think

connect the dots

crucial knowledge may be impossible to express

Whither peer to peer?

In a post called, I am fed up with hiding myself, Mita Williams concludes that academic writing removes authors from their work by turning them into ‘sources’ and ‘references’ and that large language models are doing the same, but making authors even further removed from their work.

In writing this post, I’ve come to realize that the concerns here dovetail with a long-standing bugbear of mine: that libraries overemphasize authority from sources, and does not do enough to support bibliography, a format in which authority derives from people and their choices.

In a separate post, Williams states that, “The alternative to AI is talking to other people.” —Mita Williams 2023-09-19

This got me thinking about personal knowledge mastery. It is an alternative to AI. The Seek > Sense > Share framework is based on connections not just with knowledge and information, but most importantly, people. As I wrote in 2022, we are in an information war — one that pits logic and emotion against each other. Two powerful weapons used against us by the social media algorithms are ‘Likes’ and ‘Shares’. To counter these influences, we each have a more powerful weapon — our own commentary. This is the power of blogs. A single blog, in a network of peers, can have much influence.

“I keep thinking I should write another book.
I keep thinking I should write poetry.
In the meantime, without any should, I blog.
I am a blogger.
That should be enough.”
—Euan Semple

Writing a blog can be an important sensemaking tool and is core to my personal knowledge mastery discipline. PKM and blogging are ways to model the behaviours of an engaged citizen of the world and counter the platform monopolists and forces of agnotology — the study of wilful acts to spread confusion and deceit, usually to sell a product or win favour. But mostly, blogging is having conversations with other people.

Perhaps this is one the big challenges that AI presents us — connecting with people, not machines, for our sensemaking

“I am fed up with hiding myself, an actual human being, behind the conventional anonymity of scholarly authorship.”—Stafford Beer (1995) Platform for Change

“Once men turned their thinking over to machines in the hope that this would set them free. But that only permitted other men with machines to enslave them.” —Frank Herbert (1965) Dune

In 2012 Dave Weinberger described how software developers learn — mainly peer to peer.

… in the knowledge network that developers have created for themselves … the idea is instead that all learning ought to be in public and be something that makes the public better. It improves the public act of learning. The act of educating — of teaching — are done in public so that others will learn from them and this idea of education as a public act has tremendous power and tremendous benefits because it makes the entire network — the entire ecosystem — smarter. If we can apply this within our businesses and within our educational system and beyond then our own knowledge network will become much smarter, much faster. —YouTube 2012-05-29

Foundational elements of the personal knowledge mastery framework are working collaboratively and learning cooperatively. I have called PKM our part of the social learning contract. If we don’t share, our knowledge networks cannot get smarter. They become less resilient and not able to make informed decisions — sounds a bit like much of our political discourse today.

We need context to understand complex issues and this can be provided by those we are connected to. The reach and depth of our connections become critical in helping us make sense of our environment and to solve problems. With social learning, everyone contributes to collective knowledge and this in turn can make organizations and society more effective in dealing with problems.

So what happens if we stop sharing in public? What happens when much that is shared online has not been generated by humans? What if the pattern-matching algorithms autotune the majority of what we see and read online? Dave Cormier noted that, —“The real danger is not to people who are experts in their fields. Super experts in every field will continue to do what they have always done. All of us, however, are novices in almost everything we do. Most of us will never be experts in anything. The vast majority of the human experience of learning about something is done at the novice level. That experience is about to be autotuned.” — by tools such as ChatGPT.

The canary in the coalmine will be in the software developer communities. If they stop sharing, or limit what is shared by using large language models and other tools, the entire field will slowly dumb-down. Software currently powers our societies. Perhaps it won’t matter because humans will go on to do more complex work. Or perhaps the black boxes will run most societal and organizational decisions — who gets hired, who gets an insurance payment, who gets into school, etc.

On the last Friday of each month, without any assistance from Gen AI, I curate some of the observations and insights that were shared on social media. I call these Friday’s Finds.

Disinformation, Misinformation, or Propaganda?

1. A video posted directly by Israel’s Defence Forces claimed that it had found Hamas weapons and technology, as well as a “list of terrorist names” in Arabic, showing each agents’ rota guarding Israeli hostages under the Al-Rantisi Children’s Hospital in Gaza. However, a translation of the document shows that it contains no names but instead a calendar of the days of the week. Vedika Bahl explains in this episode of Truth or Fake. —France24 2023-11-16

2. Before [Preston] Manning’s real Public Health Emergencies Governance Review Panel of 2023, there was his imagined COVID Commission of 2023.

To read both is to behold the fantasy evolve into reality. Although the Smith government gave him a panel and a $2-million budget for research and support — they also endowed him with the restraints of reality, one supposes — many conclusions essentially remained the same. —CBC 2023-11-23

3. Right-wing U.S. media covered fiction as fact: A non-existent terrorist attack from Canada at Rainbow Bridge — “I have been sounding the alarm bell about the northern border for a long time,” said Vivek Ramaswamy [US Republican Presidential candidate] during a lengthy interview about an incident he did not witness, was not a subject-matter expert on, and had no insight into. —CBC 2023-11-22

“The real persuaders are our appetites, our fears and above all our vanity. The skillful propagandist stirs and coaches these internal persuaders.” —Eric Hoffer (1955) The Passionate State Of Mind, and Other Aphorisms

A discussion with Naomi Klein on wellness culture: ‘We really are alive on the knife’s edge’ — 2023-11-15

Whenever you are working within a system of a hierarchy of humans and bodies, then you’re in fascism territory. I think that it made perfect sense that Nazis were body obsessives who fetishized the natural and the hyper-fit form and genes.

There is a connection between certain kinds of new age ideas and health fads and the fascist project …

… When we moved back to Canada and started doing election campaigning, my partner Avi knocked on a door and met a very fit person who looked like I could have taken an Ashtanga class with her. And all she wanted to talk about was vaccine passports and how she was opposed to vaccines. She said: “I have a strong immune system.” And he, very tentatively, said: “Well, yes, but not everybody does.” And she said: “I think those people should die.”

AI Companies are running out of training data

Considering that most of the AI datasets that are currently being used to train AI systems are made from internet-scraped data originally created by, well, all of us online, data partnerships may not be the worst way to go. But as data becomes increasingly valuable, it’ll certainly be interesting to see how many AI companies can actually compete for datasets — let alone how many institutions, or even individuals, will be willing to cough their data over to AI vacuums in the first place.

Agnotology: the strategic & purposeful production of ignorance —danah boyd > an understanding of my confusion

In slow media for the great reset I noted that one nice thing about blogs is that there are few trolls because it takes more time write a comment on a blog post and often there is an approval process. Plus, anyone can easily delete crap comments from their own blogs. If more people engage in longer form writing and share through blogging, we may collectively address some of the challenges we face with the misinformation and disinformation on consumer social media. Perhaps ‘slow media’ can slow the reversal effects of digital platforms which create a mono-culture of noise without meaning and meme wars. Or, in the words of Marshall McLuhan, “The ignorance of how to use new knowledge stockpiles exponentially”.

I see sensemaking as a manual skill, which can be assisted with various tools, but the most important tool is our mind, using good practices. One such practice is working asynchronously. Dealing with complex challenges is not assembly-line work, but rather constantly putting together ideas and concepts and looking for patterns to emerge. It requires time for reflection. As Albert Einstein stated, “Combinatory play seems to be the essential feature in productive thought”. Doing deep work requires time. Many people during pandemic lock-downs have found that working from home (or elsewhere) gave them more time for thinking.

Knowledge and creative work requires time apart from others. There are times for collaborative synchronous work but this cannot be the dominant mode of work. Unfortunately, it is how many organizations are structured. As a result, deep work is done on evenings and weekends and often the best workers burn out over time. In addition, many managers have little experience or have not been trained in how to manage asynchronous work. They believe that they need to be present while others work. In fact, managers often make deep work more difficult for others.

An asynchronous work model, for example, empowers individuals to tackle complex problems on their own schedules based on critical thinking rather than constantly reacting to requests in real time. That approach values depth over shallow busyness and allows time for reflection. So that speed and agility are harnessed productively rather than becoming an end in themselves.” —why i think slow and embrace asynchronous work

We have known for a long time that offices are often not the most productive places for deep work. As I said in flip the office (2014), instead of going to work, we should be going to socialize, converse, and collaborate. Productive solo time is not for the office. Knowledge workers can be productive anywhere but at the office.

My colleague and friend Jay Cross understood this.

“Visualize the workflow of a physical job: produce, produce, produce, produce, produce, produce, produce, produce, produce.

Now visualize the workflow of a creative knowledge worker: nothing, nothing, nothing, nothing, flash of brilliance, nothing, nothing, nothing.”
—Jay Cross

‘Nothing’ time is for deep thinking.

I have been publicly promoting social bookmarks since 2005, when I was using a defunct tool called FURL. Since then I have used Magnolia, Delicious, Diigo, and Pinboard. The first two are gone and the last two seem to be waning. For example, I cannot access my account settings when logged-in to Pinboard. Others are having no luck getting support from Diigo.

What are social bookmarks? They are like bookmarks on your browser except they are available online from any device, they are searchable, and you can add metadata like hashtags and categories. They can be public or private. The most important aspect is that they are shareable. Here are my Diigo bookmarks and Pinboard pins, as examples.

We discussed the demise of social bookmarks at our monthly coffee club Zoom call today and community members shared some practices and resources.

For instance, you could use Slack as a social bookmark tool (though it’s not very shareable unless you invite all your friends and pay for their access to content more than 90 days old)

Step 1: Sign up for a personal Slack team.

Yes, this is correct. Your personal team is supposed to have one and only member — you. Don’t worry if it sounds a little weird having a team of yourself, just go on.

Step 2: Use the power of channels

Besides the automatically generated #general and #random, create as many channels, as you think would matter to your needs. I have one for each of the projects I am currently working on, as well as one for each of the fields that I want to personally progress in (#java_scala, #devops_backend, #javascript, etc). Other useful channels would be #travel (collect ideas for future trips), #music (bookmark current favorite songs), etc. If a thought applies to more than one channel, simply drop it where you think it would fit best, and refer the other channel (as a hashtag).

Step 3: Start dumping your thoughts as they come to your mind.
—Using Slack as a Personal Knowledge Hub (2015)

There were also comments that perhaps we don’t need to save all information online, as we often do not find or use it again.

I had a conversation with Arthur de Villemandy, co-founder of Capsule, during which I inquired about the tricks employed by his curators. He responded with remarkable clarity, stating, “Curation isn’t about accumulating; it’s about the art of non-choice. What truly matters is the overall coherence of the selections.” This shift from FOMO (Fear of Missing Out) to NOMO (Necessity of Missing Out) could be the key to more mindful and conscious information management in the age of information overload. NOMO, fundamentally, isn’t about deprivation; it’s about liberation. Choosing is accumulating. Omitting is freeing. —Sifting Through the Noise (2023)

Several people use physical bookmarks, like Book Darts, but they don’t seem to very shareable. Other tools, like Are.na and Pocket were mentioned. The latter is owned by the Mozilla Foundation and integrates with the Firefox browser.

Many of us miss the social aspects of sharing bookmarks. When Jay Cross was writing the Working Smarter Fieldbook in 2010, his collaborators shared resources in a community group we set up on Diigo, all categorized and with our comments.

I am going to look into Are.na and reload Pocket [it does not seem possible to import my bookmarks from Diigo or Pinboard though]. This is learning in perpetual beta. Sharing curated resources is an essential element of personal knowledge mastery. Now I need to update my online workshop for the next cohort.

On the last Friday of each month, without any assistance from Gen AI, I curate some of the observations and insights that were shared on social media. I call these Friday’s Finds.

“Technology is not the sum of the artifacts, of the wheels and gears, of the rails and electronic transmitters. Technology is a system. It entails far more than its individual material components. Technology involves organization, procedures, symbols, new words, equations, and, most of all, a mindset.” —Ursula Franklin (1989) The Real World of Technology, via @cornazano

“I’m grateful for Mastodon. I have very mixed feelings about social media, but a social media platform that:

• Isn’t controlled by billionaires
• Has no advertising
• Doesn’t harvest your data, and
• Doesn’t algorithmically promote anger and hatred is a precious thing.”
—@Bodipaksa

The Economist: The pandemic’s true death toll

Although the official number of deaths caused by covid-19 is now 7m, our single best estimate is that the actual toll is 27.2m people. We find that there is a 95% chance that the true value lies between 18m and 33m additional deaths.

The art of making good misstakes

A culture in which we learn from failure requires both an atmosphere in which people can speak out, and an analytical framework that can discern the difference between what works and what doesn’t. Similar principles apply to individuals. We need to keep an open mind to the possibilities of our own errors, actively seek out feedback for improvement, and measure progress and performance where feasible. We must be unafraid to admit mistakes and to commit to improve in the future.

That is simple advice to prescribe. It’s not so easy to swallow.

“Meetings are by definition a concession to deficient organization for one either meets or one works. One cannot do both at the same time.” —Peter Drucker (1966) The Effective Executive, via @Florian Haas

Large language models (LLMs) are being integrated into healthcare systems; but these models may recapitulate harmful, race-based medicine. The objective of this study is to assess whether four commercially available large language models (LLMs) propagate harmful, inaccurate, race-based content when responding to eight different scenarios that check for race-based medicine or widespread misconceptions around race. Questions were derived from discussions among four physician experts and prior work on race-based medical misconceptions believed by medical trainees. We assessed four large language models with nine different questions that were interrogated five times each with a total of 45 responses per model. All models had examples of perpetuating race-based medicine in their responses. Models were not always consistent in their responses when asked the same question repeatedly. LLMs are being proposed for use in the healthcare setting, with some models already connecting to electronic health record systems. However, this study shows that based on our findings, these LLMs could potentially cause harm by perpetuating debunked, racist ideas. —Nature: Large language models propagate race-based medicine

In many fields, there is some critical knowledge that is very difficult to codify. “It’s the kind of knowledge that is never written down and yet can be crucial, even in the highest of hi-tech enterprises. And you won’t find it in ChatGPT, either”, says John Naughton in The Guardian.

KM expert, Nick Milton discussed the codification of knowledge and created this breakdown.

1. impossible to express,
2. can be expressed but has not been yet,
3. expressed in speech but not documented,
4. recorded knowledge, or
5. information.

The first two levels of knowledge are important to understand because we cannot easily categorize or retrieve them. They are messy. And as John Naughton states, you won’t find them with them with generative language models. In this article, he gives an example of semi-conductor manufacturing and how just having the specifications is not enough to create a functioning industry.

What’s fascinating about all this is how much of it comes down, not to finance or technology, but to people and what they know. In that sense the Financial Times’s deep dive into TSMC’s [Taiwan Semiconductor Manufacturing Company] travails reminded me of a striking piece of research conducted decades ago by the philosopher of science Harry Collins when he was a PhD student. Collins was interested in how knowledge gets transferred and intrigued by a particular piece of technology, the TEA laser. This was a device that was comprehensively documented in the physics literature but which research laboratories were unable to replicate. What Collins discovered was that “nobody could make the laser work if they hadn’t spent time in a laboratory that already had a working laser. There was very good information in the journals about how to build such a laser. But anybody who tried to put one together using written articles failed. They had something that looked like a laser on their bench, but it wouldn’t lase.” —The Guardian 2023-10-21

Practices such as supporting self-directed learning, narrating our work, and curating organizational knowledge are essential in ensuring that difficult-to-codify knowledge is able to flow between trusted nodes in a human network. This was one of the objectives of our working smarter initiative at Citibank. It’s one more reason that managers have to get out the office and do some network walking.

“Data doesn’t say anything. Humans say things.”
—Andrea Jones-Rooy, Professor of data science, NYU

In 2014 I asked — what is your PKM routine?  I highlighted the routines of Jane Hart and Sacha Chua, and then described my own. Over time I added dozens of other examples that were shared online. My own PKM routine has changed over these years. My general principles are to keep my routine simple, use as few tools as possible, and limit any automating processes. My last post — manual sensemaking — explains the latter.

• I still use a feed aggregator to monitor any RSS feeds, which is currently Inoreader.
• I have reduced my use of Twitter by ±90% and am connecting with people and having more public conversations on Mastodon.
• Many of my more private conversations are with members of our perpetual beta coffee club, now in our fifth year together. During the initial pandemic lock-downs, the coffee club was a lifeline of professional sanity for many members.
• I still use social bookmarks, like Diigo, but much less than in years past.
• This blog is still the core of public sensemaking, but as you may have noticed, I am posting less frequently. One reason is that I have already written over 3,500 posts and it’s getting harder to say something new. Also, I am becoming less inclined to share, knowing that my work is getting scraped by the likes of OpenAI and Google.

If your sensemaking routines have changed, please share in the comments or by linking to this post. It’s life in perpetual beta!

Sensemaking is a manual skill, which can be assisted with various tools, but the most important tool is our mind, using good practices.

Ideas often emerge in the complex domain, which is where people working in a network economy need to be active, probing, and playing. We also need to do shallow dives into the chaotic domain. Neither of these activities will be helped through automation. If anything, automation will make us lazy, or unaware.

The process of seeking out people and information sources, making sense of them by taking some action, and then sharing with others to confirm or accelerate our knowledge, are those activities from which we can build our knowledge. Managing and sharing information, especially through conversations, are fundamental processes for sense-making in the complex domain. Sensemaking is acting on one’s knowledge.

A key principle of PKM Seek > Sense > Share framework is that no one has the right answer, but together we can create better ways of understanding complex systems. We each need to find others who are sharing their knowledge flow and in turn contribute our own. It’s not about being a better digital librarian, it’s about becoming a participating member of a networked organization, economy and society.

Sense-making consists of both asking and telling. It’s a continuing series of conversations. We know that conversation is the main way that non-codified knowledge gets shared. So we should continuously seek out ideas. We can then have conversations around these ideas to make sense of them. Sharing closes the circle, because being a sharing knowledge is every professional’s part of the social learning contract. Without effective sense-making at the individual level, social learning at the community and organizational levels is mere noise amplification.

Ask what value you can add

Sharing is not as important as knowing when to share. This does not preclude us from collecting lots of information, but it should make us consider appropriate ways to share. We should be ready to share when the time is right.

The most important and difficult part of PKM is sensemaking. Little should be shared if there has been no value added. Thinking of adding value should be the first stage in curation, PKM, or any professional knowledge sharing. That value could be just parking things for easy retrieval. It is definitely not filling activity streams with massive amounts of unwanted information. Find ways to separate signal and noise.

The knowledge gained from PKM is an emergent property of all its activities. Merely tagging an article does not create knowledge. The process of seeking out information sources, making sense of them through some actions, and then sharing with others to confirm or accelerate our knowledge are interlinked activities from which knowledge — often slowly — emerges.

Here are various ways to add value before sharing

[my comments]

Ross Dawson’s five ways of adding value to information are a good start at sensemaking techniques.

• Filtering —[separating signal from noise, based on some criteria.]
• Validation — [ensuring that information is reliable, current, or supported by research.]
• Synthesis — [describing patterns, trends, or flows in large amounts of information.]
• Presentation —[making information understandable through visualization or logical presentation.]
• Customization —[describing information in context.]

In 1936, James Mangan — a most interesting character — identified several skills for acquiring knowledge (via Maria Popova).

• Practice — [This is absolutely critical. It is primarily through experience — performance  — reflection that we learn.]
• Get it from yourself —[Sometimes it’s better to work things out for yourself than get a quick answer from someone else.]
• Walk around it — [Looking at something from a different perspective, especially away from the mainstream, can give new insights.]
• Experiment — [Using a constant probe – sense – respond approach with work and learning.]

Robin Good identified five more curation skill.

• Comparing — [With increasing complexity, and obfuscation by competing interests, being able to compare related items becomes more valuable. Imagine if someone could compare all your mobile telephone options in a clear, simple way. Good comparisons are quite useful.]
• Finding related items — [Collecting a series of resources on a subject over time can be useful, and save others time.]
• Illustrating / Visualizing — [Good info-graphics are very useful, but too often they obscure. Visualizing takes great skill but can be exceptionally useful.]
• Evaluating — [Being able to set criteria and evaluate from a neutral point of view can add real value to what otherwise would just be data.]
• Crediting & Attributing — [While attribution may just seem like a nice thing to do, it is very important to trace how knowledge is constructed. With proper attribution to the original source, you can then make changes if evidence or circumstances change.]

On the last Friday of each month, without any assistance from Gen AI, I curate some of the observations and insights that were shared on social media. I call these Friday’s Finds.

“Working from home 1 day a week cuts carbon by 2%. 2-4 days up to 29%. Full-time 54%.” —Anthropocene Magazine

“German is so efficient. You say ‘Fachkräftemangel’ for ‘Companies not paying enough to attract suitable candidates and then complaining to the state to worsen the work environment for everyone so their shitty jobs find candidates again.’ what a beautiful language.” —@kaia

‘Stockholm Syndrome’ — via Andreu Casablanca

The phrase “Stockholm Syndrome” was invented by a police psychiatrist to discredit a female hostage in a 1973 bank heist who criticized the police … The psychiatrist who invented it, Nils Bejerot, never spoke to the woman he based it on, never bothered to ask her why she trusted her captors more than the authorities. More to the point, during the Swedish bank heist that inspired the syndrome, Bejerot was the psychiatrist leading the police response. He was the authority that Kristin Enmark – the first woman diagnosed with Stockholm syndrome – distrusted.

AI is fundamentally ‘a surveillance technology’ with @Mer_edith

“You know, you walk past a facial recognition camera that’s instrumented with pseudo-scientific emotion recognition, and it produces data about you, right or wrong, that says ‘you are happy, you are sad, you have a bad character, you’re a liar, whatever.’ These are ultimately surveillance systems that are being marketed to those who have power over us generally: our employers, governments, border control, etc., to make determinations and predictions that will shape our access to resources and opportunities.”

Three years of running a peer learning network for 135+ organisations: what have we learnt? via Benjamin P. Taylor

• Communities of practice (COPs) don’t have to look the same to be meaningful.
• Having facilitators to coordinate the network was essential for this to work.
• In a network, it’s easy to underestimate the power of 1:1 engagement …
• We tried to use every opportunity we had with the network to gather insight and data on what people wanted from the network …
• There is huge appetite for 1:1 coaching.
• If you offer to pay for peoples’ travel and accommodation it makes it much more possible for people to attend.
• A network like this can be an amazing temperature check of what is “live” in the sector

Naomi Klein’s ‘Doppelganger’ by Cory Doctorow

How did so many hippie-granola yoga types turn into vicious eugenicists whose answer to “wear a mask to protect the immunocompromised” is “they should die”?

The PastelQ phenomenon – the holistic medicine and “clean eating” to QAnon pipeline – recalls the Nazi obsession with physical fitness, outdoor activities and “natural” living. The neoliberal transformation of health from a collective endeavor – dependent on environmental regulation, sanitation, and public medicine – into a private one, built entirely on “personal choices,” leads inexorably to eugenics.

Once you start looking for the mirror world, you see it everywhere. AI chatbots are mirrors of experts, only instead of giving you informed opinions, they plagiarize sentence-fragments into statistically plausible paragraphs. Brands are the mirror-world version of quality, a symbol that isn’t a mark of reliability, but a mark of a mark, a sign pointing at nothing. Your own brand – something we’re increasingly expected to have – is the mirror world image of you.

“You know, the very powerful and the very stupid have one thing in common. They don’t alters their views to fit the facts, they alter the facts to fit the views, which can be uncomfortable if you happen to be one of the facts that needs altering.” —Tom Baker (as the fourth doctor) —Doctor Who, The Face of Evil

In 2019 I noted in hybrid sailors that the US Navy was piloting a new way of manning its Littoral Combat class ships, which are modular by design. The crew are all multi-purpose, with several roles onboard and always learning new tasks. They operate with one-fifth the crew size of a regular ship. Specialization is a thing of the past for these crews. One reason for this is that specialized knowledge has an increasingly shorter lifespan, so generalists who are good learners can make for a more flexible, or agile, crew. This approach also has its downsides, such as fewer redundant positions onboard to mitigate combat losses, and lack of deep knowledge for some complex problems.

I concluded that organizations should start testing out new models now. Learn from the Navy and others who are trying new ways of organizing work. For individuals, the ability to ‘flexibly shift’ may become a critical work skill.

Well it seems that the littoral class ship (LCS) experiment has been an utter failure.

• The Navy’s haste to deliver ships took precedence over combat ability. Without functioning weapons systems the vessels are like a “box floating in the ocean,” one former officer said.
• Sailors and officers complained they spent more time fixing the ships than sailing them. The stress led many to seek mental health care.
• Top Navy commanders placed pressure on subordinates to sail the ships even when the crews and vessels were not fully prepared to go to sea.
—The Inside Story of How the Navy Spent Billions on the “Little Crappy Ship”: ProPublica 2023-09-07

This situation reminds me of the observation by Rummler & Brache, “Over the long haul, even strong people can’t compensate for a weak process. Sure, some occasional success may come from team or individual heroics. But if you pit a good performer against a bad system, the system will win almost every time.” This could be rewritten as — put a good bunch of a sailors with an innovative idea into a bad navy, and the system wins every time. Pressure from the hierarchy coupled with political maneuvering doomed this experiment from the start. I wonder if it result in any systemic changes. Given the amount of money these projects costs as well as the many vested interests, I doubt it.

Knowledge flows at the speed of trust. In this case, it seems there was not enough of that to learn as they worked on this experiment. Could anything have been done differently, given the deficiencies in ship design, interference from above, and an inability to adapt and change the course of production? I doubt it. The only possible successful option I see, given the organizational reality,  would have been to use  skunk works, outside the official hierarchy.

There is lots of talk and writing about the future of work. I follow the #FutureOfWork hashtag on Mastodon. A recent report produced for Unilever — The Future of Work is Flexible — featured three ideas:

• Embrace the ‘pixelated’ workforce.
• The rise of the internal talent marketplace
• Is the ‘skills passport’ the future of recruitment?

The report features several drivers of change, such as how AI can decompose [pixelate] jobs into smaller pieces for employees and contractors to compete for work. Fractional hiring then blurs the lines between full-time and contract work, which leads to an internal marketplace for work. This can lead to more precarious work but as the report notes, it can also result in ex-employees getting called back for contract work at their convenience. Re-skilling is a major theme of the report stating that many skills degrade after 2.5 years.

Another driver of change noted is aging demographics and the need for many of those in the middle to not only have child care responsibilities but also aging parents. What is never discussed, and will likely be the biggest driver of change, is the climate crisis.

Overall, the report reads like a feel-good mandate for management — easier ways to ‘plug & play’ workers. With a ‘pixelated’ workforce, competing in the internal marketplace with their skills passport who then can see the big big picture? Who has the larger perspective to observe potential ethical violations? Is that the sole role of management? Is the future of work merely returning to industrial age Taylorism?

“It is only through enforced standardization of methods, enforced adoption of the best implements and working conditions, and enforced cooperation that this faster work can be assured. And the duty of enforcing the adoption of standards and enforcing this cooperation rests with management alone.” —Frederick Winslow Taylor (1911) The Principles of Scientific Management

A knowledge artisan is more than a worker with a skills passport. Knowledge artisans understand and can do the entire process of creation. They are not cogs in a ‘pixelated’ machine. Work is human, even though owners and managers are constantly driving for automation. While this report cites cases of more flexibility for some workers, it will all depend on how management implements these three ideas. If the latest round of layoffs in the information technology sector are an indicator, it won’t be favourable for workers.

I almost missed Jane Hart’s Top Tools for Learning survey which closed today. Since I’m in a later time zone, I am going to assume that this submission will be accepted. A few things have changed since last year, as I am migrating away from Twitter due to its new owner, and using Mastodon. I also stopped using Feedly and have switched back to Inoreader. The last two tools (Merlin & Seek) I continue to use for learning about the natural world.

1. WordPress — powers all my websites
2. Slack — private community space including the perpetual beta coffee club
3. Mastodon — my main social network
4. Inoreader — my RSS feed reader
5. Diigo — social bookmarks
6. Zoom — everyone now knows Zoom, which I have been using for six years
7. Overcast — for podcasts
8. 1Password — simplifies my online life and gives me more time for learning
9. Merlin — learning about birds
10. Seek — learning about nature

Last November, I started shifting my online networking from Twitter to Mastodon — Whither Twitter? Mastodon has now become my social network of choice. I’m starting to have better conversations though it’s not as active as my Twitter feed used to be, but that’s to be expected with 20 times fewer followers and I only follow about one fifth as many people as I did on Twitter. I will continue to invest in better conversations and knowledge sharing on Mastodon because it’s a platform I can trust.

For 15 years Twitter had been my go-to professional social network. The hell-scape that is now Twitter should be a wake-up call to take better control of our social networks. I have not deleted my account there because I do not want someone else to take my identity @hjarche. It’s now just a place I check every few days and post notices like my upcoming PKM workshop.

Mastodon is now the primary source for my Friday’s Finds monthly curated posts, such as the recent, ‘no unpleasant aftertaste‘. A recent comment by @Maria explains why Mastodon may be growing slowly, “If you’re wondering why there are so few news stories about the rise of Mastodon, it’s because nobody is getting paid to game the media about it. There’s no publicists, no cozy ad deals, no suits, no coercion: Nobody is getting rich off of Mastodon … that’s also why it’s so enlightening and fun to participate here.” Given that Twitter (now called X) feeds and posts are locked unless you log in, having open feeds makes Mastodon better suited for curation and sharing. Mastodon uses real simple syndication (RSS) to make open sharing easy.

I have said that machines are tools and not our friends, but open covenant tools like Mastodon and the rest of the fediverse make it easier for us to be friendly in an online space. For over a decade, Twitter was an important tool for my learning. I don’t think it will even make this year’s Top Ten List.

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.

“At this rate ‘Luddite’ is going to become a term that means, ‘Person that knows when something is a scam’” — @Amy Dentata

Overheard: “If the cloud is someone else’s computer, AI is just someone else’s labour.” — @jk

“Journalistic organisations in Canada with official accounts on the #Fediverse [e.g. Mastodon]” — @M. Gregoire

“So, we’re obviously using these rare earths for vital purposes, right? Absolutely! Seven rare earths are used to make your screen more shiny and brilliant. Three rare earths are absolutely needed to make your phone vibrate. Now, what could be more important to the future of life on Earth than a vibrating phone?” — @Gerry McGovern

OpenAI says it could ‘cease operating’ in the EU if it can’t comply with future regulation via @gourd

In addition to the possible business threat, forcing OpenAI to identify its use of copyrighted data would expose the company to potential lawsuits. Generative AI systems like ChatGPT and DALL-E are trained using large amounts of data scraped from the web, much of it copyright protected. When companies disclose these data sources it leaves them open to legal challenges. OpenAI rival Stability AI, for example, is currently being sued by stock image maker Getty Images for using its copyrighted data to train its AI image generator.

Understanding CC Licenses and Generative AI via @mia

Generative AI presents an amazing opportunity to be a transformative tool that supports creators — both individuals and organizations — provides new avenues for creation, facilitates better sharing, enables more people to become creators, and benefits the commons of knowledge, information, and creativity for all.

But there are serious concerns, such as issues around author recognition and fair compensation for creators (and the labor market for artistic work in general), the potential flood of AI-generated works on the commons making it difficult to find relevant and trustworthy information, and the disempowering effect of the privatization and enclosure of AI services and outputs, to name a few.

For many creators, these and other issues may be a reason not to share their works at all under any terms, not just via CC licensing. CC wants AI to augment and support commons, not detract from it, and we want to see solutions to these concerns to avoid AI turning creators away from contributing to the commons altogether.

Riding There via @gredaco

Fez asked where we were going, and I said I didn’t know. We were pedaling along at a pretty good clip, and he had inferred some sense of urgency, a need to get somewhere, so he was slightly puzzled by my answer … Here’s what I said to him, more or less: Fez, what are we out here for? To ride bikes? Why? Well, because at some point we’ll stop thinking about whatever we were thinking about before, and we’ll even stop thinking about riding, and we’ll just be riding. That’s the ride. It’s calm and peaceful, and it’s entirely sufficient unto itself. That’s what we’re out here for. So right now, we’re riding until we get to that place. I don’t know where it is or how to get there, except that we have to pedal and move and hope we find it.

RSS (real simple syndication) is faster and less time consuming than using a search engine, surfing the web, and then creating a huge list of favourites or bookmarks. It’s been around for a long time and many websites support it. Several of the large platforms, like Facebook, do not, because RSS is an open standard and it is difficult to track users with it. If you listen to podcasts on a ‘podcatcher’ then you are likely using RSS.

Big tech have ignored RSS and are not keen on helping people use it, but many news sites still have RSS feeds to which anyone can subscribe. The Canadian Broadcasting Corporation (CBC ) has a multitude of RSS feeds but does not advertise these or help readers use a feed reader [see image below]. Instead, for the past decade CBC has relied on the platform monopolists at Meta, Alphabet, and X, and these are now biting them in their media butts as a result of Canada’s Bill C18 which big media supported.

Michael Geist, Canada Research Chair in Internet and E-commerce Law, has written many posts on Bill C18. Basically it requires large platforms, like Meta and Google, to pay for Canadian news feeds. But Meta has decided that it will no longer allow Canadian news links, including The Beaverton satirical news site.

Many Canadians access news content through digital intermediaries. Bill C-18 would enact the Online News Act (the Act), which proposes a regime to regulate digital platforms that act as intermediaries in Canada’s news media ecosystem in order to enhance fairness in the Canadian digital news market. The Bill introduces a new bargaining framework intended to support news businesses to secure fair compensation when their news content is made available by dominant digital news intermediaries and generates economic gain. It seeks to support balanced negotiations between the businesses that operate dominant digital news intermediaries and the businesses responsible for the news outlets that produce this news content. —Government of Canada

Canadian news outlets are not happy with this situation and are calling for ‘fairness’, as the lack of eyeballs from Facebook is hurting their business. It goes to show that we should be careful who we get in bed with to distribute our work. Meta and Google can change the rules at any time. Cory Doctorow explained the situation on CBC’s The Current [19 minutes]— the problem is not that these platforms are stealing content or linking to it, but rather that they collude to defraud publishers by owning the entire ad-supported ecosystem because they represent the buyers, the sellers, the marketplace, and they are publishers and advertisers in their own right.

Our national broadcaster should not even be involved with this marketplace. Profit-sharing with Meta only gets the CBC more deeply involved with this corporate giant.

So maybe it’s time we all got back to the basics and curated our own news, instead of having it pushed to us by an algorithm.

Most blogs and many news sites have an RSS feed. An aggregator — AKA feed reader — can help keep track of other blogs so you no longer have to visit each site. New posts will appear in the feed reader. I use Inoreader, but there are many others. Mac users can get a free desktop reader — ViennaRSS

For example, to find if a site has an RSS feed, enter it on Inoreader (add new), or you can use a tool like the Get RSS Extension for Chrome or Firefox. Many people have recently left Twitter and upwards of half of those have shifted to Mastodon, an open source federation of servers sharing the same protocols. I am active there — @harold. One can also subscribe to any Mastodon feed by adding .rss to the address, e.g. mastodon.social/@harold.rss — these open protocols support each other!

One can also subscribe to #hashtags by appending .rss — e.g. https://mastodon.social/tags/pkmastery.rss

Here is a list of Canadian journalism sites that share on Mastodon.

Get started with one of these feed readers — Blogging Wizard

Many businesses are focused on whatever the latest technology [e.g. LLM, GPT] is going to bring. But too many workplaces don’t even have the basics in place. There are large organizations with no knowledge management function. How do they share knowledge across a global enterprise? They don’t. Many companies have not mastered the basics of conducting meetings, something for which there are many good practices. There are ‘learning’ departments that only focus on courses and formal instruction, ignoring performance improvement, collaboration, and social learning.

Instead of chasing the latest shiny new business fad, get the basics in place. Decades of research behind Self-determination Theory shows that people need autonomy, competence, and relatedness to fully commit to their work. Forcing them to get back to time-wasting and polluting commuting to work kills any sense of autonomy. Sitting in an office does not result in relatedness.

If the basics are not looked after, there is no foundation for innovation.

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. Last month’s post was called Welcome to Hell, with a photo of the smoke-filled sky over New York City. Last Friday night we were in the middle of torrential rainstorm that dumped 250 mm of water on us. It’s one Hell of a climate catastrophe.

“We lived, as usual, by ignoring. Ignoring isn’t the same as ignorance, you have to work at it.” —Margaret Atwood, The Handmaid’s Tale, via @c.justc

“hiding from Threads. can we stop finding new capitalist billionaire toys to be enthralled by? we are boiling ourselves like frogs, literally & figuratively” —@BonStewart

“We have the science to stop the climate crisis and end pandemics. Why are we failing? —‘Science is embraced when it serves the interests of capital, and is often ignored when it does not.’ —Jason Hickel.” —@LuckyTran

“I think a lot of the time we get frustrated with ‘people’ because we assume that change happens in democracies when enough people want it. So we conclude the problem must be that enough people don’t want it. The bastards.
No, historically democratic change happens when organisations and movements have made change happen. They are needed as instruments for people’s desires.
We’re currently living in an era with advanced machinery of government, but almost no organisation for democracy.” —@Loukas

“My theory is that Mastodon is like the kitchen of the social media party. Not the hottest spot but eventually everyone ends up there.” —@pb

“The ‘town square’ analogy for social media is another one of those crap ones that somehow got traction. No one actually wants a town square. They want a cafe at the edge of the town square where they can chat to their mates and watch the world go by. They don’t want some bloke with an amplifier in the middle of the square screaming about how Jesus saves.” —@IanBetteridge

“On AI taking my job: A long time ago I realize it was dangerous for me to ‘be’ my job/discipline. I made a little heuristic for it: Nouns<Verbs. I am a human and I do human things like make art and tools, tell stories, share knowledge. Even though I consider teaching my ‘calling’ I am not a teacher; I teach. If there was no job for that, I’d still do it. It’s like breathing for me. I can only hold my breath for so long. —@cwodtke

“The problem is that electric cars are popular with politicians precisely because they provide an excuse to avoid doing harder things, like rebuilding our cities, or changing the habits of lifetimes. Persuading people to switch from their old gasoline car to a shiny Tesla is much easier than persuading them that they can live without a car. Hence governments are pushing electric cars, often with incentives that make no sense.” – Daniel Knowles, author of Carmageddon, via @BreadAndCircuses

Image and print by Luke McGarry

This is a follow-up from my post — diversity > learning > trust — where I said that these become the key elements in building better organizational structures that can help us differentiate between stark reality and blatant lies. These elements are how we should connect because it’s in the connections that we can make sense. The lack of diversity, the unwillingness to learn, and the lack of trust are what is dumbing so many people down.

I used the following model to show where we are in terms dominant organizational societal forms — based on Tribes, Institutions, Markets, or Networks — showing that we are currently between a triform (T+I+M) and a quadriform (T+I+M+N) society, which accounts for much of the current political turmoil in our post-modern world.

I recently came across an article on The Internet Transition by Robin Berjon.

And so the problem we have is that:

1. the Internet has made greater institutional capacity possible, but
2. it has also made our world more complex in ways that require an increase in institutional capacity to happen and
3. it has broken some of our established institutions, actually causing a decrease in institutional capacity, and
4. we are not yet using the new governance capabilities that the Internet made possible anyway.

Berjon states that, “we are traversing an epochal change and we lack the institutional capacity to complete this transformation without imploding”. I noted in leadership in broken systems that many of our institutions are broken and leadership models from previous and current societal forms are insufficient for a meta-modern world [see image above], which offers a way out of our current post-modern mess.

Berjon concludes that, “If we want any hope for these politics to result in a world worth wanting, we need to build our Internet according to sound institutional principles. The toolbox for that exists, figuring out how to integrate and use it is what’s next.” One compass to guide us in this effort is Strategic Doing — getting to meta-modernity.