skill erosion

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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.

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commuting waste

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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.

“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

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dead blog walking at 20

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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?

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stepping aside

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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.

  • Step-up: directing the machine-augmented world (creativity)
  • Step-in: using machines to augment work (deep thinking)
  • Step-aside: doing human work that machines are not suited for (empathy)
  • Step narrowly: specializing narrowly in a field too small for augmentation (passion)
  • Step forward: developing new augmentation systems (curiosity)

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.

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low-quality goo

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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

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meaning-making

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“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.

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curiosity and humility

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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.

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a thousand scandals

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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.

“We were made to rote-learn science without adopting the scientific mindset and scientific ways of thinking, philosophy of science. The result is a population with bigoted, dogmatic people even having degrees in engineering and science without having the scientific temperament or critical thinking skills.” —@impactology

My grandpa was a Nazi, by @bastianallgeier

My grandpa taught me that Nazis are fantastic storytellers. The new Nazis are on Tiktok and elsewhere on social media, telling great stories. Stories of safety, of simplicity, of order and justice. Stories of lives without crises. Adventure stories.

The only way to look at all of this is from the distant future. What happens if we let the Nazis take over again. How would our world look like in 20 or 30 years from now. I shudder from the thought. There is no option that fascism would ever lead to anything else than destruction.

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augmentation not automation

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In automation vs. augmentation, inspired by danah boyd, I wrote that I am mostly in the augmentation camp, though I am concerned that automation + capitalism = a perfect storm. This was the case with the augmented work enabled by the personal computer. Knowledge work improved significantly but wages did not. We are seeing this emerging in the ‘AI wars’ featuring ChatGPT, Bard, Co-pilot and others. It’s a battle between big money to get the biggest slice of this pie, not to augment human work or improve society, yet the mainstream press treats these algorithms like actual artificial intelligence that can think and even ‘hallucinate’ for themselves. But they are just algorithms.

Dave Snowden has a good article about this on anthropomorphising idiot savants — “AI is a set of algorithms and energy-hungry training datasets that may also manifest in physical objects.”

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innovating networks

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Ed Morrison posted on LinkedIn an overview of his approach to innovation ecosystems and working with Wabash, a large transportation, logistics, and distribution company. As regular readers may know I am a huge proponent of Ed’s strategic doing framework and particularly how it applies to agile (with a small ‘a’) sensemaking.

Ed states that an innovation system consists of three types of “networks embedded in other networks”.

> In affinity networks, participants promote their shared interests.
>> In learning networks, participants help each other learn and adapt.
>> In innovating networks, participants create shared value through collaboration and recombinant innovation.

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