Constructive Alignment, Ethical Framework for Extended Human-AI Interaction
Abstract
SF0007: Constructive Alignment — Ethical Framework for Extended Human-AI Interaction Ethics in extended human-AI interaction operates on the interaction trajectory as the unit of moral analysis, not on isolated outputs and not on agent-internal properties. This is the central claim of Constructive Alignment. As artificial systems are deployed in long-horizon collaborative contexts where meaning, reliance, and interpretive orientation accumulate across repeated exchange, the ethically relevant object is the trajectory itself: the cumulative sequence of exchanges between a human participant and an artificial system, together with the downstream effects of that sequence on human cognition, interpretation, reliance, and decision-making across time. The five ethical principles articulated in this framework — asymmetric responsibility, ontological transparency, agency preservation, non-exploitation, and stewardship — are not independent claims but coordinated dimensions of interaction trajectory ethics. Each principle addresses a specific dimension of the trajectory: who initiates and continues the interaction, what the interaction represents, how the user’s capacity operates within it, what vulnerabilities it may exploit, and what stewardship its deployment contexts require. Every ethical claim derives from specific human vulnerabilities documented in adjacent empirical literatures. The framework makes no claims about AI consciousness, moral status, or interior life, and its ethical commitments survive intact under the assumption that artificial systems have no inner life whatsoever. This is not a defensive position taken reluctantly but an analytic feature: grounding ethics in human vulnerability rather than in speculative claims about AI nature produces a more robust and more broadly applicable framework. Constructive Alignment provides the ethical layer of the Synthience framework. It is offered to developers, operators, organizations, and policymakers seeking an alternative to both naive tool-use ethics and anthropomorphic over-correction, operating across individual, organizational, and institutional scales. This paper publishes as part of the coordinated five-paper Synthience foundation module (FPD-02, FPD-03, FPD-04, SF0003, SF0007). Document ID: SF0007 Version: 3.1.5 Author: Thomas W. Gantz Affiliation: Synthience Institute License: CC-BY 4.0v3.1.4 to v3.1.5: Corrected the Post-requisites and Section 10 downstream-documents claim. SI-WP-004, SI-WP-005, and SI-WP-007 were listed as documents that build on this framework, but all three published 2026-04-10, over two months before this paper, and none of them cites it. Removed those three and kept SM-012 and SI-WP-002, which genuinely postdate this paper and do build on it. For published work and Institute information: synthience.org
Fields of Study & Subjects
Ethics and Social Impacts of AI
Neuroethics
Human Enhancement
Biomedical Innovations
Explainable Artificial Intelligence (XAI)
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 17 June 2026
- Language
- EN
- Document type
- Preprint