Complexity

Complexity

watch the machines

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I wrote the next two paragraphs in a blog post last year — we have met the enemy.

A long time ago — pre-pandemic and pre-9/11 — I was flying on a commercial passenger aircraft. The flight was over-booked and as I was wearing my Army uniform, I was offered to sit in the jump seat, just behind the pilots. Yes, these things happened in the ‘before times’.

It was a short flight but I had a chance to speak with the pilots. The captain told me that many civilian pilots had a military background but their training and experience resulted in some differences. He mentioned that if there was an observed incident on take-off, most of the civilian-trained pilots would make small adjustments to the throttle speed, aware that fuel costs money for the company. On the other hand, many of the military-trained pilots might react to an incident by slamming the throttles forward and getting out the situation and in the air as fast as possible. This of course costs more fuel, but from a military operational perspective would probably be the best default action.

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hierarchies, experts, and dogma

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Dogma — prescribed doctrine proclaimed as unquestionably true by a particular group — a settled or established opinion, belief, or principle.

In 2021, research concluded that medical orthodoxy, such as ‘droplet dogmatism’, blocked the acceptance that the SARS-CoV-2 virus was mainly transmitted through the air, in spite of knowledge from fields outside infectious disease.

Three fields—political, state (policy and regulatory), and scientific—were particularly relevant to our analysis. Political and policy actors at international, national, and regional level aligned—predominantly though not invariably—with medical scientific orthodoxy which promoted the droplet theory of transmission and considered aerosol transmission unproven or of doubtful relevance. This dominant scientific sub-field centred around the clinical discipline of infectious disease control, in which leading actors were hospital clinicians aligned with the evidence-based medicine movement. Aerosol scientists—typically, chemists, and engineers—representing the heterodoxy were systematically excluded from key decision-making networks and committees. Dominant discourses defined these scientists’ ideas and methodologies as weak, their empirical findings as untrustworthy or insignificant, and their contributions to debate as unhelpful.
Conclusion:
The hegemonic grip of medical infection control discourse remains strong. Exit from the pandemic depends on science and policy finding a way to renegotiate what Bourdieu called the ‘rules of the scientific game’—what counts as evidence, quality, and rigour. —Orthodoxy, illusio, and playing the scientific game

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there is a crack in everything

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As the pandemic emerged in 2020 I sought credible information and advice first from institutions and authorities and later from a network of expertise — encouraged to do-your-own-research — in view of growing misinformation and disinformation, even from authorities like the CDC and WHO. I am not the only person to turn to a networked solution — Twitter pandemic list — for my sensemaking in this pandemic.

The People’s CDC is a networked alternative source of credible information that bypasses the corridors of institutional power.

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“the future cracked open”

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Race Bannon sees AI (or really machine learning) changing many jobs, such as technical writing, in the near future.

“I believe within 5-10 years much of technical documentation will be written by AI. Certainly, the basic procedural stuff (Step 1, Step 2, and so on) will be written by AI, but even the contextual stuff surrounding the procedural documentation (use cases, examples, and implementation tips) will be written by AI eventually too.” —The Future of Technical Writing

In The Atlantic, Derek Thompson thinks that creativity will not save our jobs from AI.

We may be in a “golden age” of AI, as many have claimed. But we are also in a golden age of grifters and Potemkin inventions and aphoristic nincompoops posing as techno-oracles. The dawn of generative AI that I envision will not necessarily come to pass. So far, this technology hasn’t replaced any journalists, or created any best-selling books or video games, or designed some sparkling-water advertisement, much less invented a horrible new form of cancer. But you don’t need a wild imagination to see that the future cracked open by these technologies is full of awful and awesome possibilities. —The Atlantic 2022-12-01

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an agile sensemaking framework

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Agile sensemaking could be described as how we make sense of complex challenges by interacting with others and sharing knowledge. More diverse and open knowledge flows enable more rapid sensemaking. I discussed the idea of agile sensemaking in 2018 and later created a sensemaking model (framework). This week on Twitter [yes, it’s still there], Ismael Peña-López shared how the framework resonates for him.

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culture eats sanity for breakfast

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Last year I came across a book — All for Nothing — about the collapse of the German Army in Prussia during the Second World War. It is written from the perspective of a young boy and the characters are mostly civilians. My mother, as a young girl, lived through this.

People in the book for the most part cannot comprehend a Soviet invasion or the defeat of the German Army. These are impossible concepts for them. Everyone in the book sees events from their unique, egocentric bubble. But then people start dying randomly and everyone becomes focused on survival. There are some acts of generosity, especially at the end of the book, but for the most part it’s everyone for themselves.

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leadership in chaos

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In our wake up call I wrote in mid-2020 that complexity and chaos are the new normal as climate change drives more crises our way — pandemics, refugees, environmental disasters, and the overall degradation of our environment. To prepare for chaos, we need people who can act. Identify these people and give them experiments or skunk-works to play with. We will need leaders who can also deal with complexity. They will have to be constantly experimenting and probing their ecosystems. Organizations who are serious about surviving any ‘post-covid’ normal will have to take a hard look at their leadership and management structures. The time to change is now, not when the next crisis strikes.

By early 2021 I identified our crisis in network leadership and asked how many organizational leaders today are in the same situation as the inadequate officers in the Canadian Army who were unfit for post-invasion reality in June 1944. By the end of August of that year, two brigade commanders and five commanding officers had been removed as they were deemed unsuitable for leadership.

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navigating complexity

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The Cynefin framework can help us connect work and learning, especially for emergent and novel practices, for which we do not have good or best practices known in advance. When we want to create a conducive learning environment for knowledge workers, the Cynefin framework helps us see the inherent weakness of instructional systems design (ISD) — designed for formal learning — which works from the premise of predetermined learning objectives and activities, usually based on good and best practices observed in the workplace.

I discussed learning in the complex domain last year and used the following visual to describe some ways that teams, communities, and networks can organize to improve knowledge sharing and sense-making.

The image below takes the basic PKM model — with teams in blue, communities in red, and networks in green — along two axes: high & low structure, and low & high abstraction. These are split in half — one for the Complex domain, and the other for the ordered domains (Complicated & Clear). The Chaotic domain has unique conditions and requires a different approach, beyond this post.

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Dee Hock 1929-2022

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Dee Hock, founder and CEO of VISA, died last week at the age of 93. VISA’s success was based on its chaordic structure.

chaordic [kay-ordʹ-ic], adj., fr. E. chaos and order. 1. The behavior of any self-organizing, self-governing, organ, organization, or system that harmoniously exhibits characteristics of both order and chaos. 2. Patterned by chaos and order in a way not dominated by either. 3. Blending of diversity, chaos, complexity and order characteristic of the fundamental organizing principles of evolution and nature. —Dee Hock

In the early 1990s, Hock looked into how to create more democratic companies, a mission he never achieved.

Not so long ago, says [Peter] Senge, Hock was addressing an audience full of CEOs. And he really had them pumping: “Great! This is how to create a learning organization that can grow at 20% per year! He’s found the keys to the kingdom!” That is, until the end, when he told them about the one little problem: “You’ll never be able to justify paying a CEO $1 million a year to run this kind of corporation.” —FastCompany 1996-10-31

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analyzing automation

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Several years ago I recommended one small change that could have a major impact would be to look at everyone’s work from the perspective of standardized versus customized (non-standardized) work. Every person in the company, with the help of some data and peer feedback, should be able to determine what percentage of their time is spent on standardized work.

If the percentage is over a certain threshold —perhaps 50% — then it becomes a management task to change that person’s job and add more customized work. The company can be constantly looking at ways to automate any standardized work in order to stay ahead of technology, the market, and the competition. While automation is pretty well inevitable, it does not have to decimate a workforce.

Looking at the overall company balance between standardized and customized work should be an indicator of its potential to succeed. By visualizing the Labour/Talent split, people in the company can take action and make plans before the inevitable shift. This also means that jobs and roles have to become more flexible and open to change.

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