[2605.10310] Positive Alignment: Artificial Intelligence for Human Flourishing

Abstract:Existing alignment research is dominated by concerns about safety and preventing harm: safeguards, controllability, and compliance. This paradigm of alignment parallels early psychology's focus on mental illness: necessary but incomplete. What we call Positive Alignment is the development of AI systems that (i) actively support human and ecological flourishing in a pluralistic, polycentric, context-sensitive, and user-authored way while (ii) remaining safe and cooperative. It is a distinct and necessary agenda within AI alignment research. We argue that several existing failures of alignment (e.g., engagement hacking, loss of human autonomy, failures in truth-seeking, low epistemic humility, error correction, lack of diverse viewpoints, and being primarily reactive rather than proactive) may be better addressed through positive alignment, including cultivating virtues and maximizing human flourishing. We highlight a range of challenges, open questions, and technical directions (e.g., data filtering and upsampling, pre- and post-training, evaluations, collaborative value collection) for different phases of the LLM and agents lifecycle. We end with design principles for promoting disagreement and decentralization through contextual grounding, community customization, continual adaptation, and polycentric governance; that is, many legitimate centers of oversight rather than one institutional or moral chokepoint.

# link_1pmlv68lnn0.pdf ## Metadata - PDFFormatVersion=1.7 - IsLinearized=false - IsAcroFormPresent=false - IsXFAPresent=false - IsCollectionPresent=false - IsSignaturesPresent=false - Author=Ruben Laukkonen; Seb Krier; Chloé Bakalar; Shamil Chandaria; Morten Kringelbach; Adam Elwood; Daniel Ford; Fernando Rosas; Maty Bohacek; Matija Franklin; Nenad Tomašev; Stephanie Chan; Verena Rieser; Roma Patel; Michael Levin; Arun Rao - Creator=arXiv GenPDF (tex2pdf:a6404ea) - Custom.DOI=https://doi.org/10.48550/arXiv.2605.10310 - Custom.License=http://creativecommons.org/licenses/by/4.0/ - Custom.PTEX.Fu

saved by

• Samuel Lo
• Vincent Huang
• Sean Lee

related reading

• Positive Alignment: Artificial Intelligence for Human Flourishingarxiv.org
• [2606.06614] Re-Centering Humans in LLM Personalizationarxiv.org
• Alignment remains a hard, unsolved problem — LessWronglesswrong.com
• The Artificiality of Alignmentjoinreboot.org
• Full-Stack Alignment and Thick Models of Valuefull-stack-alignment.ai
• After Orthogonality: Virtue-Ethical Agency and AI Alignmentthegradient.pub
• Reinforcement learning towards broadly and persistently beneficial modelsalignment.openai.com
• Self-Fulfilling Misalignment Data Might Be Poisoning Our AI Modelsturntrout.com
• Model Organisms of Misalignment: The Case for a New Pillar of Alignment Research — AI Alignment Forumalignmentforum.org
• [2601.10160] Alignment Pretraining: AI Discourse Causes Self-Fulfilling (Mis)alignmentarxiv.org
• Constitutional AI: Harmlessness from AI Feedbackarxiv.org
• Towards Bidirectional Human-AI Alignmentarxiv.org