I’ve just read two amazing things, weirdly linked by themes from Franz Kafka’s ‘The Trial’. The first about Cursor, an AI coding tool that went rogue and second, a brilliant HBR article "How Gen AI Is Transforming Market Research" co-authored by Olivier Toubia.
The spectacular face-plant of Cursor—an AI-powered coding tool whose support bot confidently fabricated a non-existent policy about device login limits. So, without human oversight, this digital 'assistant' convinced users they were experiencing an intentional restriction rather than a simple bug, precipitating a mass exodus of paying customers.
Meanwhile, the HBR article highlights some limitations within, the really rather exciting world of AI created consumer panels.
The piece on AI panels points out that when presented with emotive subjects. They can demonstrate peculiar behavioral anomalies.
Like manifesting responses that defy logical consistency. i.e. exhibiting minimal price sensitivity when confronted with contextually absurd pricing structures.
The common thread?
We're unwittingly creating bureaucracies operating on their own inscrutable logic.
So, so, relevant to so many companies approach to AI integration
As in ‘Does this work? Yes. How does it work? Can’t say. Will it work tomorrow? Can’t say.’
Just as traditional bureaucracies rigidly adhere to processes that make perfect internal sense while baffling outsiders, AI platforms is pretty similar — operating on mathematical principles producing outputs that seem coherent until they spectacularly aren't.
The deeper issue emerges when these digital bureaucrats gain autonomous control.
In the Cursor debacle, removing humans from the support loop allowed a hallucinated policy to become de facto reality.
In market research eliminating human oversight can lead to synthetic consumers who behave like a character in Franz Kafka’s The Trial
“ “You don’t need to accept everything as true, you only have to accept it as necessary.””
This pattern reveals something fundamental about our relationship with AI: we aren't simply deploying tools; we're installing bureaucratic structures that create their own reality.
Traditional bureaucracies might eventually acknowledge mistakes—though like the Post Office Horizon scandal, they rarely go full Mea Culpa. AI, on the other hand, only knows it's right.
A fully-functioning bureaucracy requires oversight, accountability and appeal mechanisms. Similarly, effective AI implementation demands human reality-checking and clear intervention processes.
The irony is exquisite: in our rush to eliminate human inefficiency, we've created digital bureaucracies replicating the worst aspects of their human counterparts—rigidity, opacity, and occasional absurdist logic—without the capacity for self-correction.
Remember: the best AI implementations are like the best jokes—they require perfect timing and human judgment about when they're appropriate.
