Waiting for Hockney
The queue for his 2012 Exhibition at the Royal Academy.
Quote of the Day
“Genius creates, and taste preserves”
- Alexander Pope
Musical alternative to the morning’s radio news
Van Morrison | This Loving Light Of Mine
Bruch Springsteen did a footstomping version version in Dublin.
Long Read of the Day
The Mythical people-life
This is a wonderful riff by Timothy Burke on an idea first articulated by Fred Brooks in his Meisterwerk, The Mythical Man Month, a much-thumbed copy of which sits on my bookshelves as I write.
It took a long time for me to see the pattern that is now in hindsight clear to almost everybody my age, and to younger generations as well. As the advantages gained by the early adopters became clear, more people pushed voluntarily into those spaces. And then as the productivity increases jolted down the line, everybody else was pushed involuntarily. The advantage suddenly vanished. The noise was up, the signal was down. Everything was suddenly being done in email, and suddenly the speed of email dramatically increased the amount of information and communication you were expected to produce and conduct. You were suddenly answering questions from all over all day long. We were all working more and it stopped being magic.
If you’re as old as I am, you’ve now seen this cycle repeated multiple times. We are all in some sense the extra workers being added to a long-delayed project with the expectation that we will make it go faster and instead it gets slower and slower all the time. We are all bugs on the windshield in the race to get to full frictionless efficiency, splattering over and over again as that fictional, inhuman El Dorado shimmers in the distance, calling to those who dream of a world where they no longer have to hire human beings at all but who in the meantime are happy to make the people they pay do more and more work while pretending that in fact they are making it easier for us all.
In academia, this drive to nowhere takes on familiar shapes across campuses. We imitate one another, which provides a ready answer any time you ask “Why are we adopting this new system, this new process?” Answer: because it has become an industry-wide standard! Why did the first adopters do it, then? As well ask which came first, the chicken or the egg…
It’s long, but interesting, thoughtful and insightful throughout. Burke has been around long enough (as have I) to see how digital technology seeps into, and then pervades, an organisation. And, as he says,
In practice what happens is that the job formerly done by a person gets divided in a thousand tiny jobs and distributed to the entire workforce. In this act, it does not magically become less work. The sum remains the same. The hope is just that each person will be able to add it to their workflow and barely notice because it is just that one…tiny…wafer. The problem is that we are all the character from Monty Python’s Meaning of Life, being fed a mountain of tiny wafers until we are engorged to the breaking point.
When became a university lecturer way back in 1972 in the Open University, I was assigned a secretary, Viv, and she did much of the typing of draft course units. Sometimes, this led to charming errors. Once, in a text on economic modelling, for example, my scribbled reference to “exogenous” variables emerged as erogenous, to the great amusement of some of my colleagues.
And now? We’re all typists, and secretaries have become ‘Executive Assistants’ who are assigned only to senior executives.
From boom to bust, the AI bubble is only heading in one direction
Yesterday’s Observer column:
Are we really in an AI bubble,” asked a reader of last month’s column about the apparently unstoppable rise of Nvidia, “and how would we know?” Good question, so I asked an AI about it and was pointed to Investopedia, which is written by humans who know about this stuff. It told me that a bubble goes through five stages – rather as Elisabeth Kübler-Ross said people do with grief. For investment bubbles, the five stages are displacement, boom, euphoria, profit-taking and panic. So let’s see how this maps on to our experience so far with AI.
First, displacement. That’s easy: it was ChatGPT wot dunnit. When it appeared on 30 November 2022, the world went, well, apeshit…
My commonplace booklet
Think Slow
Lovely blog post by Scott Galloway on Daniel Kahneman who passed away the other day. I was pondering writing something about him, but Scott has done it much better than I could have.
Kahneman studied how humans make decisions, and the shortcuts our minds take, unbeknownst to us. These shortcuts are efficient; they foster a key skill for survival, the ability to make rapid decisions with incomplete information. We have to make thousands of decisions every day, and we couldn’t leave the house if we had to objectively analyze every choice: breakfast, outfit, route, music, etc.
Our efficiency comes at the cost of accuracy: Many instinctual decisions will be poorly calibrated (i.e., wrong). To facilitate the requisite speed, our brain buttresses our decisions with artificial confidence. Kahneman’s body of work demonstrates that we are often wrong but frequently confident. These shortcuts and mistakes are present in the structure of our brains, and impossible to avoid, but recognizing them helps us discern between trivial and important decisions and invest the appropriate intellectual capital. Put another way, take a beat and you increase the likelihood of making a better decision.
Though he was a psychologist by training, Kahneman got his Nobel Prize for economics. Before him, economists “relied on the assumption of a ‘homo œconomicus,’” as the prize committee wrote, a self-interested being capable of rational decision-making. But Kahneman “demonstrated how human decisions may systematically depart from those predicted by standard economic theory.” That dry language obscures an intellectual nuclear detonation. Expectations about human decisions — whether to work at a certain job, how much to pay for a specific good — are the foundation of economic theory. Kahneman showed those expectations were incorrect…
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