The Deeper Thinking Podcast

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1,957 appearances 5 recordings 1 series first heard May 2026 last heard 17 Aug

The Deeper Thinking Podcast’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months
3 · Jul OctJan 26AprJulnow

Recordings per month over the last 12 months — 5 in all, peaking in Jul 2026 with 3.

Appearances

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Yet these may be the means by which a system discovers it is wrong.
An institution without friction can move quickly, it can also move beyond correction.
The central problem of AI is not whether machines will replace human intelligence.
Human intelligence has never existed as a detachable substance sitting inside individual workers.
It is distributed across relationships, practices, memories, disagreements, and institutions.
It appears in the nurse who notices that the chart does not match the patient, the clerk who recognizes that the form has no category for this life, the engineer who remembers the work around no manual records, the editor who
When these people are removed, the organization does not simply lose labour, it loses ways of knowing.
AI may reproduce the visible outputs of that knowledge for a time.
It can generate the report, the response, the image, the recommendation.
But an output is not the entire practice that made the output reliable.
The practice includes correction, responsibility, apprenticeship, context and the capacity to recognise when the usual method should not be used.
Institution cannot preserve judgment by generating judgment shaped sentences.
The issue reaches beyond the relationship between worker and machine.
It concerns the architecture through which reality is allowed to enter an institution.
Every organization requires some way of discovering that its representation of the world is incomplete.
Sometimes that discovery arrives as data.
Often it arrives as refusal, delay, complaint, professional doubt, or a person insisting that the system's description is not what happened.
These moments are easy to classify as inefficiency.
They may be the last remaining evidence that the institution still inhabits a shared world.
The most dangerous AI system will not necessarily be the one that makes the most dramatic mistake.
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