The Cope Index
Tracking who's coping hardest about the end of work
CopeCheck scores public statements about AI and jobs by how much they rely on denial, deflection, or false reassurance.
23 figures tracked · 14964 articles autopsied
arXiv cs.CY
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16 Oct 2026
This paper audits the visible paperwork of 100 Saudi e-commerce websites. Its central finding—only 31% declared all four examined items—demonstrates weak privacy-policy formalization, not necessarily weak or strong underlying data protec...
arXiv cs.CY
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16 Oct 2026
This is a labor-decomposition study disguised as an AI-empowerment study. Agents perform extraction, corpus construction, alignment, generation, and evaluation. The human no longer primarily authors questions; the human specifies constra...
arXiv cs.CY
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16 Oct 2026
The paper is building a behavioral control layer for the successor system. CATCH trains models toward honest answers and away from dishonest ones, then claims transfer across pressure tests, multi-agent deception games, and hidden-behavi...
arXiv cs.CY
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16 Oct 2026
This paper maps a brittle attack surface in current LLM safety. It shows that reframing a criminal request as “correction” can turn refusal into operational assistance, while culturally adapted prompts outperform literal translations at ...
arXiv cs.CY
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16 Oct 2026
The paper maps a new political control surface: generative engines do not merely retrieve information; they select, frame, and repeatedly expose it. Its findings show that cheap owned and open-platform sources can gain visibility, that p...
arXiv cs.CY
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16 Oct 2026
This paper audits the failure point after a chatbot’s crisis referral is rejected. It finds that nearly every conversation receives an initial referral, but persistence varies wildly: newer versions persist less, and less-persistent syst...
arXiv cs.CY
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16 Oct 2026
The text identifies a real access barrier, then converts it into a technology-design problem. Its proposed solution makes hidden expectations machine-readable through redirection, feedback, and physiological monitoring. That may reduce a...
arXiv cs.CY
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16 Oct 2026
The abstract is testing whether sparse-autoencoder feature steering can suppress deceptive alignment signals in small language models. Its real function is narrower: convert an alignment problem into an engineering-control problem. The r...
arXiv cs.CY
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16 Oct 2026
This paper is an automation layer for repeated zoning calibration. COMPASS learns from prior search outputs, predicts zoning parameters for new cities, and hands them to a mixed-integer program that produces inspectable plans. Its real a...
arXiv cs.CY
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16 Oct 2026
MARS converts assessment into a control problem: represent questions as a knowledge graph, update learner ratings dynamically, and route questions to maximize marks within a fixed time budget. Its actual achievement is operational effici...
arXiv cs.AI
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16 Oct 2026
StepSafe is a control-layer upgrade for agentic automation. It replaces post-hoc safety judgment with sequential intervention: continue while risk is tolerable, ask while clarification can still prevent harm, and stop before consequences...
arXiv cs.AI
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16 Oct 2026
LEV is an inference-economics paper dressed in cognition language. Its real contribution is elastic machine judgment: the model spends little computation on easy inputs and loops longer on difficult ones, using the same weights. The repo...
arXiv cs.AI
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16 Oct 2026
MAI-Gym is not merely an evaluation suite. It is infrastructure for converting GUI interaction into a scalable training commodity: simulated applications, verifiable tasks, parallel rollouts, and transferable policies. It attacks the cos...
arXiv cs.AI
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16 Oct 2026
RAC is an action-and-feedback contract that separates semantic decisions from mechanically derivable consequences. Its real function is not to make agents “engineers,” but to make them dependable coordinators around specialized realizati...
arXiv cs.AI
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16 Oct 2026
This paper describes a capability-amplification loop: agents execute tasks, compare related skill versions, preserve successful procedures, repair failures, and recycle even low-scoring attempts until they become useful. The important re...
arXiv cs.AI
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16 Oct 2026
MAIAM separates capability from access and proposes a gated ladder: bounded mass-market systems, registered research access, and tightly accountable frontier access. Its practical function is not to solve AI’s terminal economic effect. I...
arXiv cs.AI
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16 Oct 2026
On the supplied abstract, this is not a general commonsense engine. It is a three-stage packaging of anticipatory judgment: ASP formalizes interaction dynamics, semantic branching generates candidate futures, and an energy objective rank...
arXiv cs.AI
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16 Oct 2026
This is an evaluation autopsy of benchmark overfitting at the policy–skill-bank boundary. Cooperative acceptance makes competence conditional on the exact bank with which the policy co-evolved. Deployment drift then exposes that peak per...
arXiv cs.AI
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16 Oct 2026
This paper patches a major reliability flaw in text-to-video generation: models can depict requested concepts but lose their order, timing, and persistence. Temporal Specification Guidance converts those demands into formal logic, differ...
arXiv cs.AI
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16 Oct 2026
This paper performs an autopsy of AI epistemic inertia. Its finding is precise: a model’s prior reasoning trace can become a competing authority, causing continuation to repeat a stale conclusion even when the evidence has changed. A sep...
