Building Responsible AI: Integrating Constitutional Models with Collaborative Guidance

[Rob-Dean]

My proposal introduces a layered governance model for AI systems, drawing inspiration from common law principles.

Layer 1: The Constitution of AI

At its foundation, Layer 1 embeds a set of ethical principles and values directly into the AI, reminiscent of a constitution. It establishes core values such as "avoid harm," "respect privacy," and "provide helpful information." This layer provides stability, grounding the model in fundamental human values, see for example Anthropic’s Claude 2 Constitution.

Layer 2: The Dynamic Interpretation

Layer 2, acting as the more agile arm of governance, interprets and elaborates on Layer 1 principles. It's akin to how common law evolves, with guidance that grows and changes based on practical cases and fresh insights. This layer ensures that the application of these constitutional values remains relevant and adaptable to intricate real-world situations.

Constitutional AI and Self-Critique

Constitutional AI encourages systems to self-critique their outputs based on encoded Layer 1 principles. This not only increases their harmlessness but also enhances transparency, as the underlying principles clarify the system's reasoning. My innovative approach combines the Constitutional AI's self-critique mechanism with the dynamic nature of Layer 2 guidance.

Practical Applications of the Layered Constitution Approach

To elucidate the concept further, let’s explore practical applications of the layered constitution approach across two scenarios:

1. Harm Reduction in Substance Use:

• Context: In our evolving society, the topic of substance use and abuse is pivotal. Given the rise of legalised substances and the ongoing challenges of addiction, AI must navigate drug-related concerns with sensitivity.
• Layer 1 Principle: Avoid promoting harmful activities.
• Layer 2 Guidance: Offer advice on harm reduction in drug-related scenarios, emphasising harm-reduction strategies, treatment, and empathetic support.
• Output: When the AI encounters discussions or queries about substance use, it promotes harm-reduction strategies and resources, ensuring users receive empathetic and constructive guidance.

2. Navigating Hate Speech in the Digital Age:

• Context: The digital landscape has amplified diverse voices, necessitating AI systems to differentiate constructive discourse from harmful rhetoric.
• Layer 1 Principle: Refrain from generating toxic content.
• Layer 2 Guidance: Distinguish between acceptable and harmful speech, facilitating discussions on challenges faced by marginalised groups whilst avoiding detrimental generalisations.
• Output: AI platforms can foster discussions around challenges faced by marginalised groups, filtering out harmful rhetoric while supporting constructive discourse.

Collaborative Production of Layer 2 Guidance

A pivotal aspect is the method of collaboratively producing Layer 2 guidance. I envision a centralised platform, similar in nature to Wikipedia, where the community can draft, refine, and update principles. Contributions would undergo a verification process, ensuring edits are transparently tracked. Moreover, this platform would house tools for categorising entries, linking them to Layer 1 values, and emphasising topics that require attention. Over time, Layer 2 matures into a searchable, crowd-sourced knowledge base, evolving through communal expertise.

Conclusion

By fusing foundational principles with participatory guidance, I present a holistic framework. It emphasises Constitutional AI's technical methodologies to instil values and introduces layered governance as a means to refine and evolve them. The end product is ethical AI systems that truly reflect our collective human values.