mapping the crazy AI world

Institutions are misaligned from human flourishing at precisely the moment when AI alignment dominates public discourse. We pour billions into ensuring that machines serve human values, while the human institutions those machines operate inside, the workplaces, the institutions, the healthcare systems, the housing markets, continue to optimise for... See more

AI’s learning benefits are strongest when the learning is volitional, when the person chooses difficulty because they want to grow, not because an institution requires a deliverable. Inside formal education, where assessment structures reward outputs rather than understanding, AI becomes a shortcut. Outside those structures, where no grade is at... See more

When should you deliberately exclude AI? When does efficiency destroy the experience?

Expertise isn’t just another word for education—it captures the specialized knowledge required for specific tasks within an occupation, regardless of formal credentials.

What makes us human is not about doing routine, uncreative work that only reproduces what others have done before. What makes us human is our ability to do things which are not-yet-understood, which require us to be able to create meaning where there wasn’t meaning before. The meaning of “meaning” here is specific: Deciding or recognising that a... See more

Traditional measures of AI power such as compute, data, chips, and innovation ignore the deeper metric: the capacity of a society to integrate technological change without tearing itself apart.

The real competition is therefore not who builds the largest language models first. It is who can integrate AI into society while preserving legitimacy,... See more

a huge societal adjustment to “refactor” the basis of identity in a world without the structure and incentives provided by work.

A key question for forecasting future demands for expertise is identifying where AI-human collaboration will offer enduring value and where it represents only a brief waystation between machine-human complementarity and full automation.

As the expertise framework also highlights, automation—the reallocation of tasks from labor to capital—can have nuanced impacts on wages and employment. Automation that eliminates expert tasks makes remaining work simpler and more accessible. Automation that eliminates routine tasks typically increases specialization and amplifies the value of... See more