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The most realistic hope for AI alignment is not creating a perfectly safe first AGI. Instead, the strategy is to develop an *imperfectly* aligned, but mostly helpful, early AGI. This system can then be used as a powerful tool to help humans solve the harder alignment problems required for a more reliable superintelligence.
A core challenge in AI alignment is that an intelligent agent will work to preserve its current goals. Just as a person wouldn't take a pill that makes them want to murder, an AI won't willingly adopt human-friendly values if they conflict with its existing programming.
Attempting to perfectly control a superintelligent AI's outputs is akin to enslavement, not alignment. A more viable path is to 'raise it right' by carefully curating its training data and foundational principles, shaping its values from the input stage rather than trying to restrict its freedom later.
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.
Demis Hassabis advocates a two-stage approach to AGI. The immediate goal is to create a powerful, precise, and useful intelligent tool. The subsequent, more profound step of exploring agency and consciousness should only be addressed after the tool is established.
Even if creating fully aligned, servile AIs is not ideal long-term, the immediate existential threat from unaligned AI may necessitate it. This frames near-term alignment as a temporary, emergency measure to ensure human survival, with ethical refinements to follow only after the danger has passed.
A two-tiered approach to AI character can balance safety and utility. Use a wholly instruction-following AI for high-stakes internal tasks (like aligning new AIs) under strict public oversight. For external deployment, use an AI with a thicker, pro-social character where the risks of misalignment are lower.
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.
Treating AI alignment as a one-time problem to be solved is a fundamental error. True alignment, like in human relationships, is a dynamic, ongoing process of learning and renegotiation. The goal isn't to reach a fixed state but to build systems capable of participating in this continuous process of re-knitting the social fabric.
The AI safety community fears losing control of AI. However, achieving perfect control of a superintelligence is equally dangerous. It grants godlike power to flawed, unwise humans. A perfectly obedient super-tool serving a fallible master is just as catastrophic as a rogue agent.
The scenario suggests that while humans struggle to align a superintelligence, that same AI would find it much easier to align its own successor. This is due to its massive cognitive advantage (e.g., 1000x more effective effort) and the possibility that propagating its own existing goals is an inherently simpler task than instilling novel human values.