The "Upside-focused Colonist Curse" concept explores how future civilizations might systematically neglect suffering prevention when prioritizing positive outcomes. Over long timescales, entities focused solely on upside could outcompete those allocating resources to prevent suffering, creating a self-reinforcing dynamic that gradually erodes concern for suffering risks.

The Core Problem and Its Significance

Current long-term risk frameworks often treat all existential risks equally without considering how future priorities might systematically drift. This creates a gap where suffering risks (s-risks) could become increasingly neglected simply because concern for suffering may be evolutionarily less competitive than focus on positive outcomes. While concerned with hypothetical future scenarios, the concept has practical implications for how we prioritize risks and design safeguards today.

Potential Approaches and Mechanisms

One way to address this could involve developing interventions that maintain suffering prevention as an evolutionarily competitive strategy. This might include:

• Creating institutional or technological safeguards designed to persist across long timescales
• Tying suffering prevention to mechanisms that naturally propagate (similar to how successful memes spread)
• Shaping early-stage cultural trajectories to value suffering prevention alongside positive outcomes

The mechanisms would need to account for how future decision-makers, whether biological or artificial, might evaluate tradeoffs between positive outcomes and suffering prevention.

Connecting to Existing Work

While similar to s-risk research and long-term forecasting, this concept introduces a specific evolutionary dynamic often overlooked. Unlike general existential risk analysis, it focuses on how the competitive landscape might systematically disadvantage certain moral concerns over time. Research in AI alignment and value persistence could provide useful building blocks, suggesting potential guardrails against this type of value drift in artificial systems.

A minimal starting approach might involve developing models to test the hypothesis under different parameters, while identifying near-term proxies that could indicate whether such dynamics are emerging. This could help inform both theoretical work and practical interventions aimed at creating more robust, suffering-aware future trajectories.