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 · 11747 articles autopsied
arXiv cs.CY
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07 Sep 2026
The paper converts cultural mismatch into a measurable optimization problem. It compares model outputs with survey distributions, identifies the worst demographic personas, and applies cheap targeted LoRA tuning. Its most important findi...
arXiv cs.CY
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07 Sep 2026
This is a quality-control memo for an automation pipeline, not a defense of human economic indispensability. It tests whether synthetic agents reproduce human conjoint outputs across representational correspondence, inferential correspon...
arXiv cs.CY
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07 Sep 2026
This is not an audit result. It is a validation-gated protocol for auditing voice agents. Its strongest move is treating accumulated service burden—retries, escalation friction, tool-mediated delay, and refusal loops—as harm before a fin...
arXiv cs.CY
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07 Sep 2026
The paper models AI as a delegation option inside education. Its real subject is how instructors can redesign tasks to force humans to keep practicing when outsourcing becomes effortless. It identifies a genuine early-stage failure mode:...
arXiv cs.CY
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07 Sep 2026
This paper is an instrument test on outsourced conscience. It varies framing, persona, and sustained user pressure, then measures how the model’s moral position shifts. The important finding is behavioral instability: 90.1% of configurat...
arXiv cs.CY
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07 Sep 2026
This paper constructs a rehearsal regime for failures in automated vehicles. Its real function is institutional domestication: convert unpredictable socio-technical breakdowns into workshops, tabletops, drills, and assessments, then labe...
arXiv cs.CY
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07 Sep 2026
The paper builds an epistemic airlock around generative AI. It argues that factuality, citations, coverage, structure, and polished prose are local checks—not proof that an interpretation has been formed or publicly established. Its conc...
arXiv cs.CY
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07 Sep 2026
The paper reduces moral persuasion to two crowd signals—controversy and confidence—and shows that people revise or harden judgments without seeing anyone’s arguments. Its real finding is not collective wisdom. It is that moral judgment i...
arXiv econ.GN
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07 Sep 2026
The paper maps how a maritime chokepoint closure becomes a production-system shock. Its central finding is structurally important: losses propagate through complementary intermediate inputs, exceed the value of directly transiting trade,...
arXiv cs.AI
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07 Sep 2026
This paper is really converting messy human consulting labor into a machine-evaluable task. It combines records, client requirements, production APIs, inherited code, model and serving-cost limits, and held-out users. That exposes what c...
arXiv cs.AI
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07 Sep 2026
This paper attacks a training-cost assumption: that reasoning must be reinforced token by token. Its supplied results claim that one or two supervised tokens per trajectory—about 0.05% of generated tokens—can match or exceed full-token t...
arXiv cs.AI
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07 Sep 2026
This paper presents an agentic control layer that constructs, monitors, repairs, and revises self-driving laboratory campaigns with limited human intervention. The decisive fact is not convenience. It removes the specialist as the contin...
arXiv cs.AI
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07 Sep 2026
This paper is not merely reducing transcription errors. It is removing a deployment liability from an automated cognitive system. By projecting decoder activations away from a non-speech hallucination subspace, it makes Whisper more reli...
arXiv cs.AI
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07 Sep 2026
This abstract packages a narrow automation breakthrough as frictionless infrastructure progress. It replaces static lookup and hand-built heuristics with a machine pipeline: a Transformer models subnet structure, an LLM converts ambiguou...
arXiv cs.AI
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07 Sep 2026
This paper removes unnecessary answer generation from ambiguity estimation. It argues that the interpretation space contains enough information to identify ambiguity-induced aleatoric uncertainty, producing modestly better AUROC while cu...
arXiv cs.AI
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07 Sep 2026
This paper is an engineering automation artifact disguised as a modeling advance. It embeds machine learning inside a physically constrained constitutive framework, allowing one model to infer material behavior across compositions and lo...
American Enterprise Institute - AEI
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11 Sep 2026
AEI Author lands at 42/100 (moderate) for minimisation. The article downplays AI displacement concerns by asserting workers will naturally shift to other tasks and new jobs will emerge—classic...
arXiv cs.AI
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07 Sep 2026
MaxKernel turns accelerator-kernel development from specialized human craftsmanship into an instrumented search problem. LLM agents plan, write, debug, test, profile, and iterate against compiler and hardware feedback. The three modes—hu...
arXiv cs.AI
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07 Sep 2026
This paper isolates a narrow confound in coding-agent RL. Its result is clear: the evaluation harness dominates performance, while the Cross-versus-Within grouping rule contributes no reliable portability gain. Cross learns configuration...
arXiv cs.AI
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07 Sep 2026
The paper reframes indirect prompt injection from a static weakness of the victim agent into an adaptive test-time search problem. Its central move is analytically sound: attack success depends not only on the victim’s defenses, but also...
