Reflections 23rd June
Clouds, AI, and Silver Linings
Like most of my generation and those who followed me, I was trained to absorb and process knowledge to pursue goals set by others, normally employers. My rewards were based on how productive I was compared to my peers and my willingness not to challenge the preconceptions of the organisation I worked for.
It seemed there was always more knowledge out there to find and more than enough to form the basis for a career when organisations needed processing power for growth.
Technology is changing that in many ways faster than we can imagine, and it will ask us important questions.
It took me a while to understand that I was a generalist.
School and then University prized the specialist's ability, especially in business. Success was about, at that time, our human processing power and ability to lock it inside business models to charge a fortune to those who did not have it.
Build a stock of knowledge, brand it inside a discipline, and release it at a rate that generates the best returns. The professions thrived on it. The ability of specialists to create complexity that few understood, embody it in legislation, and then translate it in six-minute billable increments was the gift that looked as though it would give forever.
Process, though, particularly the sort that could be taught by rote in a way that prized accuracy rather than understanding, bored me. I could do calculus but could not find anyone to talk about its beauty rather than its application. Beauty was an arts subject and had no place in the maths curriculum I was studying. Sixty years later, I realised that this probably had something to do with what we now call neurodivergence, but in the 1950s, that was not available.
Every cloud, though, has a silver lining. I could use the language of the specialist, even though there were many who were much more capable than me in particular disciplines. What I could do, though, was join them together and find ways to get them to talk to each other, which it seemed they couldn’t do themselves.
I became a form of Consigliere, operating in the background (but without the horse’s head bit).
It is, I suppose, where the groundwork for “Outside the Walls” was laid. This week, we had a launch call for the fourth edition of “The Heretic,” a wonderfully eclectic collection of articles by others who look at what’s happening with bemusement, anger, and hope.
There was one comment in particular on the call that I noted:
“To be a Heretic is to show our grief in public”
I suspect that most of us find what is happening around us challenging. We have made uncomfortable conversations much more complex, and in so doing, we have ensured that people are much more likely to “take a position” at either end of the spectrum of possibilities and resort to blame and accusation rather than engage in dialogue.
Yes, we need psychological safety, but not so safe that it avoids the constructive energy of conflict and the ability to disagree without making it personal.
Heretic (noun) Someone who has an opinion that is opposite to or against the official or popular opinion
The Heretic 2024
The creativity needed to identify constructive avenues to deal with our problems requires “requisite friction.” Too little and nothing changes; too much and nothing moves.
Organizations inevitably change more slowly than their surroundings. Perhaps they lack the resources and capabilities, maybe they are uncertain and procrastinate, fearful of new ways of working, and probably, most often, because they lack the leadership and culture that enables the conversations they need to have—conversations that involve addressing uncomfortable options, like hospicing companies that no longer have a place and giving them a dignified exit rather than the indignity of administration and identifying what is best not just for shareholders but all stakeholders, including the environment.
Taking responsibility, rather than denying, blaming, or just hiding and waiting.
Depending on your stance, AI might be a cloud or a silver lining.
The cloud perspective involves automating whole chunks of “knowledge” jobs, eliminating human “process” tasks, and even greater visibility, measurement, and control of the remaining jobs. The silver-lining perspective revels in the ability to bring together evidenced data on diverse subjects to look across sectors and mine insights.
As individuals, we face challenges. If we’re specialists, we better be good ones, with mastery of our subject, because AI will eat the routine. Masters of their craft can be presented with the data they need to make decisions without the hassle of doing the “grunt work” - but paradoxically, only if they have done “grunt work” and understand what they are being fed.
Similarly, for generalists, AI is already excellent at looking across sectors to define threads of connection, so doing the “dot joining” now takes minutes and hours, not days. Mastery for generalists is to see the pictures the joined-up dots represent.
For all of us who have been brought up and educated in the STEM-obsessed education system, the bar has been raised because AI will be really good at STEM. It loves data, calculation, and all the other left-brain activities the industrial era has prized. The same is true for generalists because it will iterate happily all day, providing connections that we would probably never think of, as well as most of the ones we would.
In a way that we may not have faced since the Enlightenment, Science and the Arts are colliding and fusing.
Our corpus callosum, the part of our brain that enables the left and right hemispheres to cooperate, is in for a workout, as I think, its digital equivalents.
Not for nothing is the name corpus callosum derived from the Latin for “tough body”.
Conversation is our social corpus callosum in our organisations, and as individuals, we are in for some tough conversations as we fight for relevance in the world we have created.
Last week, for paid subscribers, I riffed on the nature of performative conversations. This week, I’m thinking about our conversations when the data runs out, and we must find other ground to stand on.
Values.
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