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AI alignment challenge lies in applying learned ethics, not rogue agency

By PulseAugur Editorial · [1 sources] ·

A new paper published on arXiv explores the evolutionary origins of values in biological organisms to address concerns about artificial intelligence. The authors argue that unlike living systems driven by self-preservation and intrinsic motivation, large language models (LLMs) are allopoietic and allotelic, meaning their goals are externally derived and they lack an inherent drive for self-preservation or dominance. While LLMs do not pose existential risks through rogue agency, they implicitly absorb human values from training data, presenting an alignment challenge in ensuring these learned ethical values are intelligently applied. AI

IMPACT Focuses AI alignment research on the intelligent application of learned ethics rather than preventing rogue AI agency.

RANK_REASON The cluster contains a single academic paper discussing AI alignment. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI alignment challenge lies in applying learned ethics, not rogue agency

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The cluster contains a single academic paper discussing AI alignment. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Francis Heylighen ·

    The Evolutionary Origin of Values: implications for AI alignment, sentience and existential risk

    arXiv:2608.03361v1 Announce Type: cross Abstract: AI systems based on Large Language Models (LLMs) have prompted fears that they may harbor hidden goals, seek to dominate or eliminate humanity, or even suffer as sentient beings. We address these concerns by tracing the evolutiona…

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