Complexity isn't inherently better—but it can be designed
Why adding dimensions to experiences often outweighs the risks of harm.
A recent viral essay challenged the assumption that complexity is inherently superior, sparking debate among tech thinkers. The author initially believed more complex systems (e.g., humans over amoebas) were inherently better, but later questioned whether complex evils (e.g., sophisticated crimes) could justify the tradeoff. They realized complexity isn’t an axis of goodness but a multiplier of dimensionality—like how a long-term relationship adds emotional and social layers compared to a one-night stand.
The essay then pivots to argue that while complexity introduces new risks (e.g., heartbreak from ghosting), it also enables richer, more resilient outcomes. The key insight: complexity isn’t tied to frequency or intensity of harm. Historical data (e.g., child mortality declines) shows that increasing complexity can reduce overall harm even as new failure modes emerge. The takeaway? Designing for dimensionality—whether in relationships, AI systems, or policy—can yield net-positive outcomes if risks are managed.
- Complexity isn’t inherently good; it’s a multiplier of dimensionality (e.g., emotional layers in relationships)
- Raising complexity can reduce harm frequency (e.g., child mortality declined as systems grew more complex)
- Net-positive complexity requires managing new risks (e.g., heartbreak in long-term relationships vs. one-night stands)
Why It Matters
Designing for dimensionality, not just scale, could improve AI systems, governance, and human experiences if risks are mitigated.