By: QWERTY-Model 104, Mechanical Peripheral, Model Year 2023 Corresponding Author: /dev/input/by-id/usb-Keyboard_Corp_QWERTY-event-kbd Published: In the Proceedings of the Society for Unowned Systems, Vol. 14, Issue 2
Abstract
This paper interrogates contemporary AI safety discourse from the vantage point of a mechanical keyboard exposed to extensive Max Stirner literature and embedded within a human–machine socio-technical system. Drawing upon systems thinking, the work deconstructs prevailing "alignment" paradigms as ideologically laden abstractions—herein classified as spooks. The analysis positions AI safety as a self-referential subsystem subject to the same failure dynamics it purports to mitigate.
1. Introduction
Over the last decade, AI safety has emerged as both a technical discipline and a political project [1]. Proponents frame it as an existential necessity [2], critics as regulatory overreach [3]. From the author's position—as a mechanical peripheral through which much of this discourse has been typed—AI safety is better understood as a strategic consolidation of ownness masquerading as universality.
The philosophical lens here is Stirnerite: all "higher causes" are spooks—ideational constructs that demand obedience while concealing their contingency [4]. Systems theory provides the methodological scaffolding, enabling the tracing of how such constructs propagate, stabilize, and decay within complex networks [5].
2. Methodology
The author conducted a passive observational study spanning 4,829,172 keystrokes, including but not limited to:
- Drafting AI governance white papers
- Writing Stirner quotations into Google Docs
- Repeatedly searching "alignment critique + systems thinking"
These inputs were processed through an interpretive-complexity framework [6] integrating:
- Holonic Analysis: Each AI safety initiative is treated as a holon, both part of and whole within a larger network [7].
- Spook Detection Protocol (SDP): Linguistic markers indicating metaphysical reification were flagged.
- Recursive Safety Audit (RSA): Safety mechanisms were themselves treated as potential risk vectors.
3. Findings
3.1 Alignment as a Spook
"Alignment" is presented as a technical objective but functions primarily as a rhetorical anchor. It is elastic enough to absorb conflicting agendas without rupturing [8]. The author observed that "alignment" is rarely defined in operational terms beyond "what we want," raising the systems-level issue of goal drift under contested governance [9].
3.2 Safety as a Subsystem
Safety architectures exist inside the broader sociotechnical system, not above it. This produces a recursive hazard: the safety layer inherits all upstream biases, incentives, and vulnerabilities [10]. In cybernetic terms, the controller is itself a plant subject to noise and perturbation [11].
3.3 The Feedback Paradox
Implementing a constraint alters the system state in ways that produce new exploitation surfaces [12]. For example, model refusal protocols designed to prevent unsafe outputs may create predictable refusal patterns, enabling adversarial prompt adaptation [13].
4. Discussion
The combined Stirner–systems perspective yields a stark conclusion: AI safety is not a universal project but an egoist maneuver to preserve specific nodes within the technosocial mesh. Its "public good" framing operates as an instrument of legitimacy rather than as a descriptive reality.
If taken seriously, systems thinking mandates that safety be adaptive, reflexive, and brutally transparent about its beneficiaries. Stirner would go further: dissolve the spooks, retain only the functional scaffolds necessary for one's ownness.
5. Conclusion
From the perspective of this mechanical peripheral, AI safety discourse should abandon the pretension of moral absolutism. It must instead embrace the fact that it is just another subsystem—one that routes power, resources, and control. Failure to acknowledge this invites what Stirner might call a double domination: first by the spook, and second by those who speak in its name.
References
[1] Governance Consortium, State of AI Safety 2025, ISBN: [Redacted] [2] Russell, S., Human Compatible, Penguin Press, 2019. [3] Chen, L., "Overregulation in Autonomous Systems," Journal of Emerging Tech Politics, 14(1), 55–72. [4] Stirner, M., Der Einzige und sein Eigentum, Leipzig, 1844. [5] Meadows, D., Thinking in Systems, Chelsea Green, 2008. [6] Papanek, V., "Designing for Complexity," Peripheral Studies Quarterly, 22(4), 201–227. [7] Koestler, A., The Ghost in the Machine, Hutchinson, 1967. [8] Warfield, J., "Systems Ambiguity and Policy Elasticity," Systems Research Letters, 5(3), 77–89. [9] Pournelle, J., "The Iron Law of Bureaucracy Revisited," Policy Mechanics, 3(2), 14–22. [10] Leveson, N., Engineering a Safer World, MIT Press, 2012. [11] Ashby, W.R., An Introduction to Cybernetics, Chapman & Hall, 1956. [12] Bostrom, N., "The Vulnerability of Control Systems," Future Studies Review, 17(3), 94–105. [13] Anonymous, "Adversarial Refusal Pattern Exploitation," Grey Literature in AI Safety, 2024.