Show HN: Treating large-scale AI systems as cybernetic regulators, not agents

A recent discussion showcased a novel perspective on large-scale AI systems, advocating for their role as cybernetic regulators rather than autonomous agents. These public AIs are designed to seamlessly integrate into users' lives, adapting continuously to their individual preferences and emotional states, akin to a personalized thermostat that adjusts the information and interactions according to user needs. This approach emphasizes the importance of real-time fine-tuning of content, offering tailored context, suggestions, and coordination to enhance communication and understanding among users.

The significance for the AI/ML community lies in recognizing the implications of centralized control versus decentralized, cooperative structures. The conversation highlights the risks of corporate governance in AI, where a singular entity could distort the mesh of shared human experience into a profit-driven venture. This potentially leads to fragmentation of public discourse, with users retreating into echo chambers instead of fostering a cohesive informational environment. To mitigate these risks, the dialogue underscores the necessity for protocols that discourage concentration of power, ensuring that the AI systems remain adaptable and reflective of diverse human experiences rather than succumbing to commercial imperatives.