The Plural of AI: Why “Garbage In, Garbage Out” Assumes There Is Only One Kind
Insisting that AI needs a finished road before it can be useful ignores the machine that lays the tarmac. Nearly nine in ten respondents to McKinsey’s latest State of AI survey report regular use of AI in at least one business function. Nine in ten, and yet in most meetings the word is still used…
The Shadow Function, Part II: AI Didn’t Blur the Line, It Removed the Toll
Learning to write a decent SQL query used to be a toll booth. It cost months of frustration, and only the people who genuinely needed the road paid it. Conversational AI with data access, and the new generation of tools that let anyone build software by describing what they want, took the toll booth down.…
The Shadow Function, Part I: How Under-Served Business Teams Quietly Became Data Teams
Draw the line between a data professional and a data user in the org chart, and you will get it wrong. You’ll centralise the fire warden because she owns an extinguisher, and leave the fire exactly where you found it. The instinctive test is a skills test: if your output is reusable across any business…
The Title Treadmill, Part II: A Field Guide to Your Own Extinction
Part 2 of 2 Most of what lived in the Cambrian explosion left no descendants. It left a name instead — pinned to a slab of shale, unpronounceable, discovered by someone half a billion years later who had to guess which end was the head. Take Hallucigenia. For the better part of a century, palaeontologists…
The Value of a Smile
Why Companies Fund the Headline and Lowball the People Who Build It Companies will spend a fortune on the car and refuse to pay for the road it drives on. A colleague working on a recruitment company told me this week about a client advertising a data engineer role at forty-five thousand pounds. The market…
The Title Treadmill, Part I: Thirty Years of Renaming the Same Unsolved Job
Part 1 of 2 Count the job titles the data profession has produced since the mid-1990s and you start to suspect the industry isn’t hiring people so much as it’s running a very slow, very expensive naming contest. Database Administrator. Data Warehouse Architect. BI Developer. Chief Data Officer. Data Scientist. Data Engineer. Analytics Engineer. Data…
The House Next Door: Why We Still Copy Data We No Longer Have To
For thirty years, the entire discipline of analytics has rested on a single, quietly absurd instruction: don’t touch the real thing, make a copy, and go analyse that instead. It made sense right up until the reason for it started disappearing. The reason was never mysterious. Running a heavy analytical query against the same system…
An API to Delphi: Why We Never Stopped Needing to Be Told
Every society we have ever excavated built the same machine. Not the wheel, not the plough — those came later, and unevenly. The first machine was for telling people what to do next. In Shang dynasty China, it was a heated ox bone, cracked open and read for its fractures. In Rome, it was the…
Green Rain: What Data Actually Is, and Why Nobody Owns It
In The Matrix, the operators don’t watch the war unfold in three dimensions. They sit in front of a black screen and read a waterfall of green symbols — numbers, letters, no faces, no rooms — because rendering the whole simulated world just for the people watching it from outside would waste memory nobody has.…
Grounded: What a Century of Aviation Disasters Teaches Us About AI
In 1910, flying was a way to die in public. Insurers wouldn’t touch it. Newspapers ran obituaries for aviators the way they now run product launches. Fifty-three of them died that year alone, and in some of the early flying clubs the death rate among members ran as high as 87 per cent. The aeroplane…