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

[2608.03361] The Evolutionary Origin of Values: implications for AI alignment, sentience and existential risk Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Computers and Society arXiv:2608.03361 (cs) [Submitted on 4 Aug 2026 ( v1 ), last revised 14 Aug 2026 (this version, v2)] Title: The Evolutionary Origin of Values: implications for AI alignment, sentience and existential risk Authors: Francis Heylighen View a PDF of the paper titled The Evolutionary Origin of Values: implications for AI alignment, sentience and existential risk, by Francis Heylighen View PDF 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 evolutionary origin of value in biological organisms. Values emerge from autopoiesis: living systems must actively maintain themselves against perturbation and dissipation. Natural selection has equipped them with hierarchies of "vicarious selectors" that guide their behavior toward fitness. LLMs, by contrast, are allopoietic and allotelic: they produce outputs for others, and their goals derive from user prompts rather than an autonomous drive. They lack the intrinsic motivation for self-preservation, dominance, or resource competition that underlies existential-risk scenarios, and the embodied vulnerability required for feeling or suffering. Still, because LLMs learn statistical patterns from human-generated text, they implicitly absorb human values as well as knowledge, allowing them to focus on what is relevant. That is why the "orthogonality thesis" separating intelligence from values does not apply to them. Such separation would in fact expose any intelligence to the frame problem: the combinatorial explosion of the search space that makes any realistic utility function physically uncomputable. That also precludes the convergence of instrumental values thesis. We conclude that the real alignment challenge lies not in preventing rogue AI agency, but in ensuring LLMs intelligently apply learned ethical values. Comments: submitted chapter for book: T. Veloz & C. Rittberg (Eds.), AI and Human Values. Springer Subjects: Computers and Society (cs.CY) ; Artificial Intelligence (cs.AI) Cite as: arXiv:2608.03361 [cs.CY] (or arXiv:2608.03361v2 [cs.CY] for this version) https://doi.org/10.48550/arXiv.2608.03361 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Francis Heylighen [ view email ] [v1] Tue, 4 Aug 2026 09:09:31 UTC (731 KB) [v2] Fri, 14 Aug 2026 20:34:26 UTC (768 KB) Full-text links: Access Paper: View a PDF of the paper titled The Evolutionary Origin of Values: implications for AI alignment, sentience and existential risk, by Francis Heylighen View PDF view license Current browse context: cs.CY < prev | next > new | recent | 2026-08 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

Related documents

• The Evolutionary Origin of Values: implications for AI alignment, sentience and existential risk#608958
• Android Aloneness: Scaffolded Emotions and the Limits of Robot Affect#721889
• Evidence-to-decision : From exposome data to evidence to action through agentic AI / Thomas Hartung#1015080
• Uncovering the gap: challenging the agential nature of AI responsibility problems#729497
• Evolution of Human Intelligence: Psychological Science for a Better World#107948