AI Safety

Steven Byrnes proposes aligning AGI using human-like social drives

Can we code AGI with innate social instincts like humans? A new 51-minute analysis.

Deep Dive

Steven Byrnes, a researcher focused on brain-like AGI safety, published a comprehensive 51-minute read on the AI Alignment Forum titled 'Notes on technical alignment via human-like social drives'. He argues that if humans can steer toward a good future, sufficiently human-like AGIs could too—provided they have good prosocial motivations. The challenge is writing code that yields such motivations.

Byrnes examines human innate social drives as a template, discussing three key failure modes: the AGI developing the wrong 'moral circle', norm-following collapsing without a balance of power (relevant to superhuman AI), and consequentialist desires overriding norm-following. He also explores two pathways for how virtues become internalized: 'person-first' (adopting traits of admired individuals) and 'desire-first' (deep personal passion shaping identity). The post is a raw dump of interconnected ideas, calling for scrutiny and deconfusion from the community.

Key Points
  • Proposes using human innate social instincts (e.g., pride, shame, norm-following) as a foundation for AGI alignment
  • Identifies three failure modes: wrong moral circle, balance-of-power mismatch with ASI, and consequentialist desires overriding norms
  • Distinguishes 'person-first' (emulating role models) vs 'desire-first' (passion-driven identity) as pathways for cultivating AGI virtues

Why It Matters

Offers a concrete, biology-inspired framework for coding prosocial motivations into future AGI systems.

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