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Post-anthropocentric value alignment: beyond the human-set and human-centred

Post-anthropocentric value alignment: beyond the human-set and human-centred
Post-anthropocentric value alignment: beyond the human-set and human-centred
As autonomous systems (AS) are increasingly adopted for high-impact applications, concerns arise about these systems making morally concerning decisions and performing harmful behaviours. These concerns have charged research efforts in value alignment, or designing and training AS to act in a way which is consistent with a certain set of values. Current human-centred solutions include training AS to i) prioritise the wellbeing of humans or ii) adhere to descriptive human ethics.

This thesis investigates the prioritisation of human wellbeing as a normative grounding for AI ethics and value alignment. This thesis shows that anthropocentric accounts of moral value fail to motivate the claim that humans matter more than nonhumans. This thesis also examines the limitations of training AS to adhere to descriptive human values. Experimental results demonstrate that even when humans share moral intuitions, we struggle to translate these intuitions into a machine-readable format. Moreover, AS trained on human values often fail to align with relevant normative principles.

This thesis proposes an alternative non-human-centred approach to value alignment. Ecological ethics is introduced and defended as an alternative normative grounding for value alignment, broadening the kinds of things afforded moral consideration to include nonhumans, such as plants and animals, and entire ecosystems. This thesis also presents a novel technical contribution, `modelled ethics', where domain-specific quantitative models are utilized to capture normative ethics. Experimental results show that modelled ethics value alignment outperforms human-set reward functions in adhering to a both human-centred and ecological ethics.

This research de-centres the human in value alignment, offering a more inclusive AI ethics paradigm and creating more ethically robust AS.
University of Southampton
Rigley, Eryn
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Rigley, Eryn
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Chapman, Age
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Evers, Christine
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Mcneill, Will
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Rigley, Eryn (2025) Post-anthropocentric value alignment: beyond the human-set and human-centred. University of Southampton, Doctoral Thesis, 222pp.

Record type: Thesis (Doctoral)

Abstract

As autonomous systems (AS) are increasingly adopted for high-impact applications, concerns arise about these systems making morally concerning decisions and performing harmful behaviours. These concerns have charged research efforts in value alignment, or designing and training AS to act in a way which is consistent with a certain set of values. Current human-centred solutions include training AS to i) prioritise the wellbeing of humans or ii) adhere to descriptive human ethics.

This thesis investigates the prioritisation of human wellbeing as a normative grounding for AI ethics and value alignment. This thesis shows that anthropocentric accounts of moral value fail to motivate the claim that humans matter more than nonhumans. This thesis also examines the limitations of training AS to adhere to descriptive human values. Experimental results demonstrate that even when humans share moral intuitions, we struggle to translate these intuitions into a machine-readable format. Moreover, AS trained on human values often fail to align with relevant normative principles.

This thesis proposes an alternative non-human-centred approach to value alignment. Ecological ethics is introduced and defended as an alternative normative grounding for value alignment, broadening the kinds of things afforded moral consideration to include nonhumans, such as plants and animals, and entire ecosystems. This thesis also presents a novel technical contribution, `modelled ethics', where domain-specific quantitative models are utilized to capture normative ethics. Experimental results show that modelled ethics value alignment outperforms human-set reward functions in adhering to a both human-centred and ecological ethics.

This research de-centres the human in value alignment, offering a more inclusive AI ethics paradigm and creating more ethically robust AS.

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Published date: 2025

Identifiers

Local EPrints ID: 504003
URI: http://eprints.soton.ac.uk/id/eprint/504003
PURE UUID: 81f1479d-4170-49f9-af74-5256e183b24c
ORCID for Eryn Rigley: ORCID iD orcid.org/0000-0003-2475-6307
ORCID for Age Chapman: ORCID iD orcid.org/0000-0002-3814-2587
ORCID for Christine Evers: ORCID iD orcid.org/0000-0003-0757-5504
ORCID for Will Mcneill: ORCID iD orcid.org/0000-0002-3647-0720

Catalogue record

Date deposited: 21 Aug 2025 06:44
Last modified: 11 Sep 2025 03:24

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Contributors

Author: Eryn Rigley ORCID iD
Thesis advisor: Age Chapman ORCID iD
Thesis advisor: Christine Evers ORCID iD
Thesis advisor: Will Mcneill ORCID iD

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