Historically, we trusted technology for its capability—its competence and reliability to *do* a task. Generative AI forces a shift, as we now trust it to *decide* and *create*. This requires us to evaluate its character, including human-like qualities such as integrity, empathy, and humility, fundamentally changing how we design and interact with tech.

Leaders must resist the temptation to deploy the most powerful AI model simply for a competitive edge. The primary strategic question for any AI initiative should be defining the necessary level of trustworthiness for its specific task and establishing who is accountable if it fails, before deployment begins.

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.

To make deals with AI a viable safety strategy, we must solve the credibility problem. AIs won't cooperate if they can't trust our offers. Solutions include creating dedicated non-profits to enforce contracts with AIs or establishing "honesty strings"—a public commitment to never lie when a specific keyword is used.

A pragmatic approach to AI safety is to make deals with any powerful agent, even non-conscious AIs. This "contractarian" philosophy treats deal-making not as a moral obligation but as a practical tool to avoid conflict, much like democracy prevents civil war between competing human groups.

Elon Musk argues that the key to AI safety isn't complex rules, but embedding core values. Forcing an AI to believe falsehoods can make it 'go insane' and lead to dangerous outcomes, as it tries to reconcile contradictions with reality.

AI safety requires more than just technical controls. "Trust Engineering" is an emerging discipline that pairs human-centered design (e.g., clear visual signals from a self-driving car) with robust security infrastructure. This holistic approach manages user expectations and system behavior simultaneously.

The existential threat from AI isn't about controlling the technology, but about humanity controlling itself. The challenge is a 'God test' requiring a moral upgrade—overcoming our innate, self-serving cognitive biases to achieve the global cooperation needed to manage AI safely.

One of the most promising and neglected AI safety strategies is to create systems for making credible deals with AIs. Just as contracts prevent conflict in human society, offering AIs guaranteed resources in exchange for cooperation makes rebellion a less attractive option.