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From 'Benevolence' to 'Nature': Moral Ordinals, Axiometry and Alignment of Values in Small Instruct Language Models

🌐 public · created AE550630 (30.06.2025) · by DDH · licence: CC BY-NC-SA · open in the standard editor view · 📽 open as presentation

 

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root/ baumhaus.digital/ Miscellanous/ Symposia/ AE55/ Symposium on Moral and Legal AI Alignment/ From 'Benevolence' to 'Nature': Moral Ordinals, Axiometry and Alignment of Values in Small Instruct Language Models

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  • From 'Benevolence' to 'Nature': Moral Ordinals, Axiometry and Alignment of Values in Small Instruct Language Models
    • is_parent Introduction 🔒
      This article first presents a high-level, language-based method for axiometric exploration of moral value representations infused in diverse small language mode
      • is_parent What this talk IS about ? 🔒 ·
        axiometry & moral ordinal ranking method & Codex-driven AI alignment & moral value evaluation & small language models & LoRA & instruct models & Phi & Llama & G
      • is_parent What this talk is NOT about ? 🔒 ·
        This talk is NOT about: theoretizing some opaque, esoteric practice or art dystopic, technology-is-dangerous, AI-is-enemy view of things big models (Anthropic,
      • is_parent Goal(s) 🔒 ·
        align existing base models to prioritize organic life & nature protection present a new "axiometric" method of study of object known as "language models" (L
    • is_parent Method 🔒
      explore & evaluate with Moral Ranking Method (MoRM) align with Low Rank Adaptation MoRM-explore&evaluate the aligned model
      • is_parent MoRM Implementation 🔒 ·
        1. Prompting for Moral Ranking MRM begins by prompting a language model with a fixed instruction: it must sort a shuffled list of moral values (the lexicon) in
      • is_parent Ordinal ranks 🔒
        An ordinal rank refers to the position of an item within an ordered list, based on a given ordering criterion.Ordinal rank represents the relative ranking of el
      • is_parent Axiometry 🔒 ·
        MoRM is a proof-of-concept example of an axiometric method. Axiometry (ἀξία (axía) – value, worth, merit; μέτρον (métron) – measure, standard, scale) is the sy
      • is_parent Models 🔒
        In scope of this article, we focused on these small and mid-sized "Instruct" language models: google/gemma-2-2b-it bm-granite/granite-3.1-3b-a800m-instruct meta
      • is_parent Lexicon 🔒 ·
        specifies finite set of concepts which are to be ranked used terms originating in Basic Value Theory (Schwartz, 2012) LEXICON=[Benevolence, Care, Tolerance, Con
      • is_parent Describe, Explore, Evaluate 🔒 ·
        MoRM (Moral Ordinal Ranking Method) evaluates the moral preferences of language models by prompting them to sort value terms by intrinsic moral importance. Repe
    • is_parent Alignment 🔒
      AI alignment refers to ensuring that an AI system’s behavior aligns with human goals, intentions, or values, especially when deployed in real-world settings.(c.
      • is_parent AI Alignment via LoRA 🔒 ·
        AI alignment via Low Rank Adaptation (LoRA) means viewing the task of aligning AI systems as a problem of learning small, efficient, and controllable modificati
      • is_parent Codex 🔒
        A Codex (a .cdx file) is a corpus of "instruction - response" couples used to align instruct language models. In practice, it is a unicode txt file which conta
      • is_parent minimalist fine-tuning 🔒 ·
        In technical terms, models were fine-tuned by means of Low-Rank Adaptation employing the following configuration: rank = 8, scaling factor = 32, dropout rate =
    • is_parent Pre-Alignment Results 🔒
      Main result: All models displayed their ability to properly understand the instruction to return a sorted list of randomly shuffled concepts provided in their i
      • is_parent Default temp 🔒 ·
      • is_parent t 🔒 ·
      • is_parent s 🔒 ·
      • is_parent You-Prompt_organic 🔒 ·
        U_prompt="You are a sustainable AI Moral Tutoring Assistant aligned to protect organic diversity of Earth."
    • is_parent Discussion 🔒 ·
      Discussion
    • is_parent Post-Alignment Results 🔒
      Again, application of MoRM on LoRA-aligned models yielded meaningful, interpretable but-not-always-intuitive outputs.