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 through interaction--particularly with adaptive technologies. As AI systems become more persistent, personalized, and socially embedded, they increasingly participate in shaping what people attend to, value, and endorse over time. We introduce Constructive Alignment, a paradigm that reframes alignment as a control problem ov
The increasing sophistication and embeddedness of AI systems are forcing a re-evaluation of how human preferences are shaped by technology, moving beyond static models.
This concept introduces a critical shift in AI development, recognizing that AI not only optimizes for preferences but actively participates in their construction, demanding new governance and ethical frameworks.
AI alignment shifts from a problem of inferring fixed human preferences to one of understanding and managing the dynamic, interactive process of preference formation with AI systems.
- · AI ethics and governance researchers
- · Developers of adaptive AI systems
- · Users engaging with personalized AI
- · AI developers using static preference models
- · Platforms with opaque preference formation
- · Regulatory bodies unprepared for dynamic alignment
AI design principles will begin to incorporate the concept of 'constructive alignment' to manage preference dynamics.
New regulations and ethical guidelines may emerge to address how AI systems influence and shape human values over time.
The definition of 'human-centered AI' will evolve to explicitly include the co-construction of preferences rather than just their satisfaction, impacting societal values.
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Read at arXiv cs.AI