New Paradigm Reframes AI Alignment as Preference Evolution Control.
Summary
This paper introduces "Constructive Alignment," a new paradigm that views AI alignment not as satisfying fixed human preferences, but as governing how AI systems influence the evolution of human preferences over time. It proposes a control-theoretic framework to manage these dynamic preference trajectories.
Why it matters
For professionals developing or deploying AI, understanding that AI can shape user preferences over time is crucial for ethical design, long-term user satisfaction, and avoiding unintended societal impacts.
How to implement this in your domain
- 1Incorporate ethical design principles that consider the long-term impact of AI on user values.
- 2Develop AI systems with mechanisms for user feedback on preference evolution, not just current satisfaction.
- 3Design AI interactions to promote reflective endorsement and critical thinking, rather than passive acceptance.
- 4Establish governance frameworks for AI development that address dynamic preference shaping.
Who benefits
Key takeaways
- Human preferences are dynamic and influenced by AI interactions.
- AI alignment should focus on governing preference evolution, not just static satisfaction.
- A control-theoretic framework can model how AI influences human values.
- Ethical AI design must consider long-term value formation and user empowerment.
Original post by Max Kanwal, Caryn Tran
"arXiv:2607.00001v1 Announce Type: new Abstract: Most approaches to AI alignment treat human preferences as fixed targets to be inferred and optimized. This assumption conflicts with extensive empirical evidence showing that preferences are layered, dynamic, and constructed throug…"
View on XOriginally posted by Max Kanwal, Caryn Tran on X · view source
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