Selective Adoption

In the AI Story

The Meiji Japanese case is the paradigmatic example. After Commodore Perry forced Japan open to Western trade in 1853, the Meiji Restoration (1868) undertook one of the most rapid and successful institutional transformations in modern history. Japan systematically adopted Western military organization, industrial production, educational systems, legal codes, and political institutions. But the adoption was selective: core Japanese cultural practices — family structure, religious life, aesthetic traditions, the imperial symbolic system — were preserved and adapted rather than abandoned. Within a generation, Japan had transformed from a feudal society vulnerable to colonization into a modern industrial power, without losing the cultural coherence that made collective action possible.

The contrast with societies that chose differently is instructive. The Ottoman Empire, facing analogous pressure to modernize, made more incremental and less systematic reforms that preserved traditional structures at the cost of adaptation. The Qing Dynasty in China, facing similar pressure, resisted foreign models more thoroughly and paid the price in the Century of Humiliation. At the opposite extreme, various colonial societies that adopted foreign models wholesale lost the cultural coherence that sustained collective action, producing the hollow modernization Diamond observed across multiple cases.

Applied to the AI transition, selective adoption requires distinguishing between practices that must change (organizational structures built around scarce execution capability, educational curricula designed to transmit procedural knowledge AI now provides, hiring practices rewarding narrow specialization) and practices that must be preserved (the cultivation of judgment, the protection of mentorship, the maintenance of friction-rich developmental experiences, the institutional structures that align individual incentives with collective welfare). The difficulty is that the practices in the first category are often easier to identify than those in the second, because what must be preserved is often invisible — tacit, embedded in institutional culture, transmitted through relationships rather than documents.

The mistake at either extreme is clear. Organizations that refuse to adopt AI tools at all — maintaining pre-AI workflows as a matter of principle — fail the way the Norse failed. Organizations that adopt AI wholesale, abandoning any practices that feel pre-AI, fail by losing the institutional features (deep expertise, mentorship, judgment) that any sustainable cognitive economy requires. Successful adaptation requires the difficult intermediate work of distinguishing which specific practices should change and which should be preserved — work that cannot be done by ideology and must be done through honest analysis of what each practice actually produces.

Origin

The concept appears throughout Diamond's analysis of national crisis cases in Upheaval, drawing on comparative historical analysis of the Meiji Restoration (particularly the work of Marius Jansen, Carol Gluck, and others on Japan's modernization). The selective-adoption framework has become standard in comparative studies of modernization and institutional transfer.

The application to the AI transition follows directly from Diamond's framework and requires the specific diagnostic work of distinguishing contingent from foundational practices — diagnostic work that organizations and societies navigating the transition must do for themselves rather than deriving from general principles.

Key Ideas

Selective adoption is analytical, not compromising. The difficulty is the diagnostic work of distinguishing contingent from foundational practices, not splitting differences between modernization and tradition.

Meiji Japan is the paradigmatic case. Its success demonstrates that rapid institutional adaptation is possible without surrendering cultural coherence — if the adaptation is selective rather than wholesale.

Foundational practices are often invisible. What must be preserved is usually tacit, embedded in institutional culture, and transmitted through relationships — making its identification harder than identifying practices that should change.

Both extremes fail. Refusal to adopt and wholesale adoption both produce institutional degradation; successful adaptation requires the difficult middle path.

The AI transition requires specific diagnostic work. Organizations must distinguish which of their practices are environmentally contingent (and should change) versus foundational (and should be preserved) — and the diagnosis is often contested and difficult.

Debates & Critiques

The contested question is what counts as foundational versus contingent. Different stakeholders within the same institution will classify the same practices differently — managers may view organizational hierarchy as contingent while workers experience it as foundational to their identity. Critics argue the framework is too permissive: any change can be justified as 'selective adoption' of what needed to change. Defenders respond that the concept is diagnostic rather than prescriptive — it generates the analytical questions that must be answered, not the answers themselves, and the questions are better than their absence.