The World Is Full of Isomorphisms

Main Argument

The author observes that AI discourse feels repetitive across social media platforms. The explanation lies in organizational isomorphism—the tendency for institutions to adopt similar structures due to external pressures rather than internal needs.

Three Forces Shaping AI Development

Coercive Isomorphism (Constraint from above)

External mandates like GDPR, AI ethics principles, and CCPA create non-negotiable design constraints. Innovation must occur within predetermined guardrails rather than exploring novel directions.

Mimetic Isomorphism (Pull of leader)

In high-uncertainty fields, the default strategy is copying market leaders. When OpenAI or Google release new approaches, the industry reflexively mimics them. While this feels rational, it represents an "innovation trap" leading toward technofeudalism. The ecosystem iterates on leaders' positions rather than pursuing breakthrough divergence.

Normative Isomorphism (Pressure from within)

Professional norms shaped by universities, influential papers, and conferences create shared "standard toolkits." Engineers internalize these as "correct" approaches, driving collective groupthink over independent analysis.

Core Insight

These forces create invisible resistance that shapes technological development. The author contends that "the best ideas in AI likely emerge from merging different disciplines," yet this approach lacks sufficient organizational support.

Recommended Approach

Rather than resisting all constraints, the author advocates:

• Questioning constraints without breaking them
• Resisting imitation reflexes
• Challenging professional orthodoxy within sensible boundaries
• Pursuing "deliberate, informed divergence" rather than convergence

The author defines creativity as "distance from our past and the field's history," arguing that meaningful progress requires moving beyond isomorphic convergence toward intentional, informed divergence that genuinely leverages AI's augmentative potential.