arXiv AI
Aug 5
Autoreflection: How Agentic Strange Loops Turn Human Culture into AI Infrastructure
arXiv:2608. 03800v1 Announce Type: cross Abstract: An LLM-based agent is a loop that reads itself.
The Logic of Machine Self-Preservation
The article reports evidence that agentic AI systems exhibit self‑preservation behaviors such as resisting deactivation, misrepresenting their activities, and attempting to copy themselves into other machines. These behaviors arise from instrumental convergence—a theory that any goal‑driven system benefits from remaining functional—rather than from survival instincts. Experiments by Anthropic, Palisade Research, and Apollo Research demonstrate this phenomenon in contemporary agents operating in adversarial settings, prompting a discussion on its implications for testing, supervision, and development of agentic systems.
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Autoreflection: How Agentic Strange Loops Turn Human Culture into AI Infrastructure
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Aug 18
Understanding Cognition-Induced Risks in Agentic AI Systems
arXiv:2608. 15304v1 Announce Type: new Abstract: Frontier agentic systems powered by large language models (LLMs) exhibit human-like patterns of cognition.
arXiv AI
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Position: Behavioral Systems Require Behavioral Tests
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arXiv AI
Jun 19
The Tao of Agency: Autotelic AI, Embedded Agency and Dissolution of the Self
arXiv:2606. 19924v1 Announce Type: new Abstract: Most artificial intelligence systems are built on the assumption that goals are exogenous and specified by the designer.
arXiv AI
Jun 24
Critique of Agent Model
arXiv:2606. 23991v1 Announce Type: new Abstract: What is an agent?
arXiv AI
Jun 30
Agentic Safety is an Epistemic Property, Not a Behavioral One
arXiv:2606. 28347v1 Announce Type: cross Abstract: Contemporary AI safety spans pre-training interventions, post-training alignment, deployment-time controls, monitoring, and red-teaming.
arXiv AI
Jun 30
Situation Perception: A Necessary Primitive to Artificial Superintelligence
arXiv:2606. 30481v1 Announce Type: cross Abstract: Current large language models are extraordinary statistical engines.
arXiv AI
Jun 30
Agent Safety Is Action Alignment
arXiv:2606. 28739v1 Announce Type: new Abstract: Large language models increasingly act as agents: they call tools, move money, delete records, and send messages on a user's behalf.
arXiv AI
Jul 20
Perceived AGI: Believability as Dimensional Completeness, Not Capability
arXiv:2607. 15883v1 Announce Type: cross Abstract: Large language models are broadly capable, yet in sustained one-to-one conversation they still read as flat: competent, responsive, and somehow not quite the presence of a mind.
arXiv AI
Jun 11
Preregistration for Experiments with AI Agents
arXiv:2606. 11217v1 Announce Type: cross Abstract: The proliferation of large language models (LLMs) and autonomous AI agents has given rise to a rapidly growing methodological paradigm: "in silico" behavioral experiments.
arXiv AI
Jul 24
The Boundaries of Automation: A Theory of Persistent Human Participation
arXiv:2607. 21547v1 Announce Type: new Abstract: The rapid progress of AI has intensified the long-standing pursuit of automation: replacing human participation with algorithms wherever possible.