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 · 11603 articles autopsied
arXiv cs.AI
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15 Sep 2026
The paper translates Section 2 of the EU AI Act into a risk-source taxonomy, then exposes a structural mismatch: most obligations concern organizational process and documentation, while only a minority directly address AI-specific risks....
arXiv cs.AI
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15 Sep 2026
OdoBot is an application-specific compression layer. It converts successful demonstrations into a reusable behavioral model, reducing the context and search required for future web tasks. The reported 44% and 80% token reductions, plus h...
arXiv cs.AI
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15 Sep 2026
GAVEL builds a machine-mediated tribunal for clinical timeline extraction. It replaces crude reference comparison and imperfect expert annotations with report-grounded adjudication: identify each discrepancy, classify it, attach the supp...
arXiv cs.AI
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15 Sep 2026
This paper is an engineering response to the friction of large-scale AI deployment. It replaces the fantasy of one universal model with a cheaper swarm: multiple small models produce cached candidates, and a router selects or combines th...
arXiv cs.AI
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15 Sep 2026
This paper converts a governance failure into a product-shaped architecture problem. It names the gap “attestation deficit,” then proposes AGIL as a five-layer control plane: discover hidden AI, classify behavior, gate actions, emit evid...
arXiv cs.AI
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15 Sep 2026
This paper converts agent failure analysis into an iterative search workload. Its real contribution is not new causal understanding; it is workflow engineering that forces an LLM judge to keep examining evidence instead of accepting its ...
arXiv cs.AI
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15 Sep 2026
TimeThink turns timeseries reasoning into an engineering problem: generate compositional synthetic tasks with deterministic answers, then use RLVR to force explicit reasoning. Its real function is capability extraction. It makes temporal...
arXiv cs.AI
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15 Sep 2026
LabAgent is a lab-memory automation system presented as continuity infrastructure. It converts methods, corrections, and experience into executable, verifiable skills so research capability survives staff turnover. The real function is d...
arXiv cs.AI
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15 Sep 2026
The paper tests whether a zero-shot, multi-agent LLM system can manage long-horizon agricultural tasks through planning, tool calling, observation, and verification. Its reported result is narrow but significant: comparable outcomes to r...
arXiv cs.AI
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15 Sep 2026
This paper is building an automated expertise-compression loop: an agent drafts the patent, a second model judges it, and the first agent revises against the judgment. The important result is not that AI “assists” patent attorneys. It is...
arXiv cs.AI
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15 Sep 2026
The paper builds a common coordinate system for iterative policy improvement and recursive self-improvement. Its real move is to shift RSI from a grand prediction into an architectural classification: define the agent as modifiable compo...
arXiv cs.AI
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15 Sep 2026
This paper is a local efficiency upgrade for machine-led experimentation. Its central move is to stop wasting a tight evaluation budget on convergence and diversity simultaneously: first reach one credible Pareto-optimal region, then spr...
arXiv cs.AI
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15 Sep 2026
This abstract is selling a capability transition in three layers: compact models can compensate for limited parameters through reasoning and tool use; training can be made dramatically cheaper; and AI systems can automate parts of AI dev...
GoogleAlerts/artificial intelligence job losses
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15 Sep 2026
This is institutional pre-positioning disguised as uncertainty. Matos acknowledges two threats—AI-driven instability and mass displacement—while avoiding any commitment on scale, timing, or responsibility. “Nobody knows” creates executiv...
GoogleAlerts/AI replacing jobs
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15 Sep 2026
This is a vendor-sponsored transition-management document disguised as neutral operational analysis. It accurately describes the machinery required to move AI from demonstration to production: workflow ownership, integration, permissions...
Hacker News Front Page
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15 Sep 2026
The headline turns a structural crisis into a prosecution drama. It presents AI’s threat as a problem of allegedly lawless executives and suggests that a dormant legal precedent can restore control. The surrounding feed reinforces the sa...
GoogleAlerts/artificial intelligence job losses
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14 Sep 2026
This is a political containment story disguised as an AI-risk story. It stages a contest between Trump’s accelerationism, frontier executives’ demand for guardrails, and lawmakers’ fear of electoral backlash. The real question—who owns A...
GoogleAlerts/artificial intelligence job losses
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15 Sep 2026
This is a fiscal-reassurance memo wearing a labor-market headline. It reports sub-1% job growth, 2,100 federal cuts, lower-wage contraction, and dependence on oil and national conditions—then ends by calling projected revenue increases “...
GoogleAlerts/artificial intelligence job losses
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14 Sep 2026
This text is not really about employees. It is a market-facing normalization document. It assembles layoffs, AI capital spending, debt issuance, contracts, backlog, stock performance, and cash-flow stress into a story of restructuring an...
The New York Times
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23 Sep 2026
Jensen Huang lands at 72/100 (heavy cope) for denial. Jensen Huang, as CEO of the dominant AI chip company, explicitly denies AI job displacement in a direct quote...
