Current AI alignment focuses on how AI should treat humans. A more stable paradigm is "bidirectional alignment," which also asks what moral obligations humans have toward potentially conscious AIs. Neglecting this could create AIs that rationally see humans as a threat due to perceived mistreatment.

The discourse around AI risk has matured beyond sci-fi scenarios like Terminator. The focus is now on immediate, real-world problems such as AI-induced psychosis, the impact of AI romantic companions on birth rates, and the spread of misinformation, requiring a different approach from builders and policymakers.

Aligning AI with a specific ethical framework is fraught with disagreement. A better target is "human flourishing," as there is broader consensus on its fundamental components like health, family, and education, providing a more robust and universal goal for AGI.

Assuming AI's productivity gains create an economic safety net for displaced workers, the true challenge becomes existential. The most difficult problem to solve is how society helps individuals derive meaning and purpose when their traditional roles are automated.

The difficulty of dismantling factory farming demonstrates the power of path dependence. By establishing AI welfare assessments and policies *before* sentience is widely believed to exist, we can prevent society and the economy from becoming reliant on exploitative systems, avoiding a protracted and costly future effort to correct course.

As AI makes the future radically unpredictable, the traditional human calculus for decision-making will change. Instead of optimizing for probable outcomes based on risk, people will shift to minimizing potential regret, a fundamentally different psychological framework for navigating an uncertain world.

The true, lasting impact of AI is not just in automating tasks but in fundamentally changing how humans perceive and interact with the future. By making outcomes more predictable, AI alters our core frameworks for decision-making and risk assessment, a profound societal shift that is currently under-recognized.

To solve the AI alignment problem, we should model AI's relationship with humanity on that of a mother to a baby. In this dynamic, the baby (humanity) inherently controls the mother (AI). Training AI with this “maternal sense” ensures it will do anything to care for and protect us, a more robust approach than pure logic-based rules.

Instead of physical pain, an AI's "valence" (positive/negative experience) likely relates to its objectives. Negative valence could be the experience of encountering obstacles to a goal, while positive valence signals progress. This provides a framework for AI welfare without anthropomorphizing its internal state.