Category: AI
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The age of the expert generalist
In 1936 a 20 year-old Claude Shannon came to MIT from the University of Michigan to work with Vannevar Bush on his differential analyser, an early, room-sized mechanical computer. This analog computing machine could solve differential equations through a series of rotating discs and shafts whose operations were governed by a bank of around a…
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Why AI fluency doesn’t scale
By the early 1980s the General Motors assembly plant in Fremont California was widely regarded to be the worst performing car manufacturing site in the U.S. The company had a huge employee engagement problem with absenteeism regularly running at over 20%, and sometimes approaching 50% on a Monday. When managers had too few people turn…
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Why AI shifts bottlenecks rather than remove them
In 1793 Eli Whitney invented a machine that could separate cotton fibers from their sticky seeds. The ‘Cotton Gin’ (short for ‘Cotton Engine’) mechanised what was previously a hugely laborious and inefficient manual process and it transformed the textile industry almost overnight. Suddenly mass-scale cotton production became not only more possible, but vastly more profitable.…
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The Great Unbundling of Work
On 4 May 1948, the US Supreme Court ruled in a landmark antitrust case that would change the way that Hollywood studios worked forever. Until that point the studios had owned everything, from the production lots, through to the cinemas that the films played in. Actors, Directors and writers were tied in to long-term, exclusive…
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Technology, inflection points and cascading impacts
In the late 19th Century sharpshooter Annie Oakley was one of the most popular acts within Buffalo Bill’s Wild West Show. Annie would demonstrate her skills performing tricks like shooting the flames off candles and her grand finale, shooting the end off a lit cigarette held in the mouth of a brave volunteer from the…
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AI and the OODA Loop
Most AI use today is open-loop. People prompt, get an output, use it, and move on, meaning that each interaction is consumed the moment it’s produced. Last week I wrote about AI as compounding capability in the context of agencies and operating models, but it’s a principle that has much broader application. Getting value from AI and…
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The New Agency Operating Model
I recently ran a morning session at the ICOM World Meeting in Porto on the new operating model for advertising agencies. ICOM is the global network for independent agencies and the room was full of agency founders and leaders from markets around the world. A big part of the session focused on a scenario modelling exercise where…
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Creating an AI Braintrust
Years ago, when I first read (Pixar co-founder) Ed Catmull’s brilliant book Creativity Inc, I remember really loving their ‘Braintrust’ idea. This is where a group of Pixar’s finest creative brains come together regularly to review outputs and provide candid, constructive feedback on films in development. Ed Catmull described at the time how the job of the…
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The AI Inevitability Trap
If there’s one phrase that best expresses the two-way nature of the relationship between humanity and technology it’s probably Father John Culkin’s quote (often attributed to Marshall McLuhan): ‘We shape our tools and thereafter our tools shape us’. Humans create the technology, but that technology later shapes human behaviour, culture, perceptions, norms, and even the physical…
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Why Every Company Needs an AI Philosophy
I’ve been thinking a lot this week about that MIT Sloan piece that I shared in FF686 on how ‘Philosophy Eats AI’. The piece argues that three branches of philosophy are already embedded in every AI deployment whether leaders recognise it or not: teleology (what should AI models achieve?), epistemology (what counts as knowledge?), and…