Work is learning. Learning is the work.
As we get inundated with new knowledge and information regurgitated by large language models and generative pre-trained transformers — time for meaning-making becomes critical.
Meaning-making is the process by which we interpret situations or events in the light of our previous knowledge and experience. It is a matter of identity: it is who we understand ourselves to be in relation to the world around us.” —Dave Gurteen
Are we swimming in a world of meaninglessness?
Marshall McLuhan has influenced much of my work and I have used the tetrad from the Laws of Media many times to understand emerging technologies. A recent article in The Free Press by Benjamin Carlson was a refreshing read by someone who had just discovered McLuhan. I started reading McLuhan’s work in 1995.
I first stumbled upon Marshall McLuhan a year ago on YouTube. Within a minute or two of watching a clip, I was amazed: here was a man who, in 1977, seemed to be describing the dislocating experience of living in 2023, and he did so with more insight than people living today. That the words were coming from a craggy, mustachioed man in a rumpled suit only enhanced the eerie feeling. Here was a professor-as-prophet. McLuhan says, in part, to his TV host … I shared the clip on Twitter and it went viral with more than 6 million views —The Prophets 2024-03-02
This blog turned 20 last month — dead blog walking. One of the big challenges that the growth of AI [GPT, LLM, etc.] presents us is connecting with people — not machines — for our sensemaking. A personal blog is a human way to connect. There is no algorithm to filter what others read. They can subscribe, on their terms, and with their chosen technology thanks to real simple syndication (RSS). The great thing about blogging is that there are few rules. You can write as you like, when you like, and as often as you like.
If you don’t use it, you will lose it. Automate what was once a skill-developed process and those skills will decline.
“Cognitive automation powered by advanced intelligent technologies is increasingly enabling organizations to automate more of their knowledge work tasks. Although this often offers higher efficiency and lower costs, cognitive automation exacerbates the erosion of human skill and expertise in automated tasks. Accepting the erosion of obsolete skills is necessary to reap the benefits of technology—however, the erosion of essential human expertise is problematic if workers remain accountable for tasks for which they lack sufficient understanding, rendering them incapable of responding if the automation fails.” —The Vicious Circles of Skill Erosion (2023)
One key factor in understanding how we learn and develop skills is that experience cannot be automated. Increasing automation requires that the Learning and Development (L&D) field must get out of the comfort zone of course development and into the most complex aspects of human learning and performance. To understand learning at work, L&D must understand the work systems. Now they also have to understand skill erosion.
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.
“Everything that needs to be said has already been said. But, since no one was listening, everything must be said again.” —André Gide (1869-1951)
“You steal from one person and you’re a thief. You steal from everyone and you’re an AI company.” —Aral Balkan
“I’m going to exaggerate slightly, but it seems like one of the first applications of any new technology is making things even shittier for artists.” —Neal Stephenson, on generative AI
Twenty years ago I started writing this blog. Over 3,600 posts later, it’s still my main tool for making sense of my work and the world.
Only a few months after I started blogging, I heard Tod Maffin, a Canadian digital journalist, on CBC radio state that blogging was dead — already! But I saw my blog as a tool for work, and not necessarily a way to make money, so I marched on — dead blog walking.
What has my blog been good for?
In Only Humans Need Apply, the authors identify five ways that people can adapt to automation and intelligent machines. They call it ‘stepping’. I have added in parentheses the main attributes I think are needed for each option.
There is a lot of talk and media coverage about stepping-up, stepping-in, and stepping-forward. I have previously discussed stepping-in and concluded that anyone affected by these technologies [AI, GPT, LLM] needs to understand their basic functions and their underlying models. These tools will be thrust into our workplaces very soon. So let’s step-in to working with machine learning but with a clear understanding of who needs to be in charge — humans. I stand by this position today.
The race toward an AI-driven society is not only costly in terms of electricity and water use with the current AI data centre boom, but the longer-term impacts on how we communicate may be significant.
“This is the AI Grey Goo scenario: an internet choked with low-quality content, which never improves, where it is almost impossible to locate public reliable sources for information because the tools we have been able to rely on in the past – Google, social media – can never keep up with the scale of new content being created. Where the volume of content created overwhelms human or algorithmic abilities to sift through it quickly and find high-quality stuff.
The social and political consequences of this are huge. We have grown so used to information abundance, the greatest gift of the internet, that having that disrupted would be a major upheaval for the whole of society.” —Ian Betteridge 2024-01-24
“The ignorance of how to use new knowledge stockpiles exponentially.” —Marshall McLuhan
For the past decade I have promoted the idea that a job is not the same as meaningful work. Most jobs are refillable and replaceable. One worker leaves, another one fills the job position. Our work can help to define us, but our jobs should never define us.
I think the only way we are going to address the many complex challenges that face society today are through curiosity and humility. Sparking curiosity is possible, with the right supports and environments. In addition, curiosity trumps knowingness — already knowing and not looking for disconfirming data. Curiosity and humility combine to make us better learners, and better leaders.