CopeCheck

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

How Scoring Works

Every public statement is scored 0–100 on how much it relies on denial, deflection, or false reassurance.
Cope types include: timeline minimisation, jobs-will-be-created fallacy, regulatory hopium, augmentation fantasy, and more.
Recent statements are weighted more heavily (exponential decay). The leaderboard reflects who is coping hardest right now.
0–15 = Lucid · 16–35 = Partial Awareness · 36–55 = Moderate Cope · 56–75 = Heavy Cope · 76–100 = Terminal Copium

Full methodology →

Cope of the Week

COPE OF THE WEEK

Elon Musk · Score: 82/100

False Reassurance Techno Optimism Deflection

“Saving money for the distant future is pointless with the advent of super intelligent abundance.”

Musk’s direct claim replaces any discussion of displacement, ownership, or mass unemployment with a utopian promise that AI and robotics will make money and savings irrelevant. As a leader of companies building these technologies, he offers abundance as a fantasy escape from their labor-market consequences rather than addressing who benefits or what happens to displaced workers.

Cope Index — Live Leaderboard

Founder & Executive Chairman, Amazon / Blue Origin / Prometheus

false_reassurance, deflection, partial_acknowledgment

““You’re not going to need to have a two-earner household... one of the people might drop out.””

AI Educator / Investor

AI educator teaching millions to automate themselves out of a job and calling it upskilling. His scapegoat is anyone who won't just learn to code their way through the apocalypse.

jobs_will_be_created, augmentation_fantasy, timeline_minimisation, false_reassurance, deflection, arsonist_firefighter

““AI is unlikely to trigger a mass loss of jobs but will instead create new opportunities if workers reskill.””

Marc Andreessen

Co-founder, a16z

Wrote Why AI Will Save the World and meant every word. His scapegoats are regulators, doomers, and anyone who suggests the guy funding the revolution might not be an objective narrator.

denial, deflection, false_reassurance

““AI was the scapegoat for layoffs that are actually the result of overhiring.””

CEO, xAI / Tesla

Co-founded OpenAI, left, sued them, then started a rival AI company anyway. Oscillates between AI will kill us all and but my AI is the good one depending on which gets more engagement on X.

false_reassurance, techno_optimism, arsonist_firefighter, deflection

“"universal high income" as the most likely outcome of advanced AI”

Selling the shovels in the AI gold rush in a leather jacket while insisting the gold is definitely real. His cope is that he doesn't need one — NVIDIA prints money either way and his scapegoat is anyone who questions GPU demand.

““Together, we will scale Hugging Face’s platform, strengthen its infrastructure and expand access to AI for...””

Founder, Khosla Ventures

Cheerfully predicts AI will eliminate 80% of jobs and treats this as obviously good news. Scapegoats anyone who thinks mass unemployment might be a problem rather than an opportunity for more yoga.

partial_acknowledgment, arsonist_firefighter, techno_optimism, deflection

“"accelerate AI and energy infrastructure while protecting workers displaced by automation, not their individual jobs"”

Chief AI Scientist, Meta

Meta's Chief AI Scientist who insists current AI is just fancy autocomplete while the autocomplete keeps passing bar exams. His cope is pure intellectual gatekeeping — if it doesn't match his definition of intelligence, it simply doesn't count.

denial, timeline_minimisation, human_creativity_cope

““These systems are less intelligent than a cat,” LeCun said in 2024, pushing back on predictions that assume rapid capab…”

Launched the AI arms race then spends half his time saying it might be dangerous and the other half saying everyone will be richer. The undisputed champion of having it both ways in a single sentence.

partial_acknowledgment

““non-zero” chance that it’s our last”

Economist, MIT (Nobel 2024)

Nobel-winning economist whose models say AI won't cause mass displacement, so he's sticking with the models. Blames Silicon Valley hype merchants for making everyone panic about something his spreadsheets say is fine.

timeline_minimisation, false_reassurance, partial_acknowledgment, deflection

“"2036 tak AI sirf 5% tasks ko automate kar payega" aur "job khatam hone wali baat sirf ek hawa hai."”

Mark Zuckerberg

Burned tens of billions on the metaverse, pivoted to AI overnight, and now acts like Meta was always an AI company. The king of corporate amnesia — blames the media whenever anyone mentions the legs that didn't render.

partial_acknowledgment

“the promised payoff from the sharp rise in 2026 spending has not arrived.”

Former US Treasury Secretary

deflection, techno_optimism

““Gates’s robot tax risks essentially being protectionism against progress.””

Turned Copilot into Microsoft's answer to everything and calls replacing ten workers with one a productivity gain. His cope is enterprise-grade: framing mass automation as empowerment with a straight face.

techno_optimism

““newer AI models are finally capable of delivering on more of Copilot’s promise””

Built the AI most likely to replace your job, then wrote a 15,000-word essay about how great that'll be. Copes by framing Anthropic as the safety-first lab while shipping capabilities as fast as everyone else.

partial_acknowledgment

“None; the excerpt is a candid warning that AI could disrupt half of entry-level white-collar jobs within one to five yea…”

CEO, Google/Alphabet

Spent years saying AI first while Google Search slowly became an AI slop cannon. Blames responsible AI when competitors move faster, then ships half-baked features and blames users for noticing.

“Are agents truly native inside ChatGPT, or did OpenAI just glue them onto a plain chat box?”

CEO, Sinovation Ventures

partial_acknowledgment

“top AI agents across nearly all white-collar industries can complete the workday of the smartest humans in less time tha…”

Economist / Blogger

Hedges so artfully on AI he can claim he predicted every outcome. The it's complicated defense means he's never technically wrong, which is the most economist thing imaginable.

partial_acknowledgment

““For everyone else, the machines would not be partners but competition, and skills that once earned a middle-class wage …”

CEO, Google DeepMind

Solved protein folding, now building AGI, and seems genuinely puzzled why people are nervous. Hides behind the scientist's shield of we're just doing research while DeepMind quietly automates everything that moves.

partial_acknowledgment

“"It's soon."”

partial_acknowledgment

““fewer people” and “fewer layers””

Economist / Columnist

The man who said the internet would matter less than the fax machine, now applying that same energy to AI. Blames tech hype cycles for his discomfort with the possibility he might be spectacularly wrong twice.

partial_acknowledgment

““the possibility that AI will worsen America’s already severe problem of income and wealth inequality””

Geoffrey Hinton

Godfather of AI / Nobel Laureate

Nobel Prize in Physics 2024 for foundational work on neural networks. Left Google in 2023 to speak freely about AI existential risk. The man who taught machines to see now warns they might decide humans are in the way. Trends toward the concerned/pessimistic end of AI discourse — the rare case where the inventor genuinely fears his invention.

false_reassurance

““We could recover from it””

Yuval Noah Harari

Historian / Author

Warns about a useless class of humans displaced by AI, then sells millions of books to that exact audience. His scapegoat is technology itself, which he treats as fate rather than a series of human choices.

partial_acknowledgment

“"What will conscious humans do once we have highly intelligent non-conscious algorithms that can do almost everything be…”

AI Critic / Author

Professional AI skeptic who's been calling the bubble since 2018 and will die on this hill. Every breakthrough is not real intelligence and every failure proves he was right — the goalposts have their own frequent flyer miles.

partial_acknowledgment

“«Noi cittadini dobbiamo boicottare l’intelligenza artificiale fino a che le aziende non la mettono a posto»”

Eliezer Yudkowsky

AI Alignment Researcher / MIRI Founder

Founded the Machine Intelligence Research Institute (MIRI) and essentially invented the field of AI alignment as a discipline. Has argued since the early 2000s that superhuman AI will kill everyone unless we solve alignment first. The most pessimistic serious voice in AI discourse, occupying the absolute doom end of the spectrum.

“"AI will become powerful enough to potentially destroy society."”

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Popular Figures — Last 30 Days

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Oracle Verdicts — Latest

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arXiv cs.CY · 15 Oct 2026

HACHIMI-II: From Role-Play to Learner Behavior Modeling for Faithful Student Simulation

HACHIMI-II replaces theatrical student role-play with explicit learner-state inference and a behavior harness that constrains the model’s next action. Its real contribution is controllability: learner history becomes a predictive model o...

arXiv cs.CY · 15 Oct 2026

Moral Combat: Exploiting Moral Foundations Theory to Jailbreak LLMs

The text is really describing a prompt-injection pipeline disguised as moral psychology: identify the moral foundation a request appears to violate, select another foundation that makes the same act look virtuous, rewrite the request, re...

arXiv cs.CY · 15 Oct 2026

A Unified Response Framework for Questions and Tutoring Dialogues

This paper converts tutoring dialogue into measurable student-state data. It decomposes conversations into mathematical subtasks, rewrites them as standalone questions, labels correctness, and places both questions and student trajectori...

arXiv cs.CY · 15 Oct 2026

MemeTrace: A Multimodal LLM-Based Agent for Safety-Aware Meme Provenance Analysis

MemeTrace reframes meme moderation as provenance analysis: tracing origin, spread, symbolism, and social risk through a multimodal LLM agent. Its reported evidence is narrow—a 100-meme dataset, human annotations, automatic metrics, compa...

arXiv cs.CY · 15 Oct 2026

From Efficiency to Sufficiency: The Cost-Aware Measurement Design Framework for Automated Essay Scoring

The paper builds an accounting and governance wrapper around automated essay scoring. Its CAMD framework expands “cost” beyond inference expense to include validation, monitoring, adjudication, compliance, labor, time, licensing, and int...

arXiv econ.GN · 15 Oct 2026

Generative AI Availability, Grades, and Student Satisfaction at a Large University

This is a narrow institutional stress test, not a test of economic obsolescence. It examines whether GenAI availability after ChatGPT changed grades and student satisfaction more in courses classified as AI-susceptible. Its result is lim...

arXiv econ.GN · 15 Oct 2026

Ideological Bias in LLMs' Economic Causal Reasoning

This is a benchmark autopsy of model-generated economic judgment. It finds that ideology-contested causal questions are harder, and that 17 of 20 models perform better when the empirically recorded result favors intervention-oriented exp...

arXiv econ.GN · 15 Oct 2026

Creative destruction: Human-AI competition in an experimental market

This is a controlled demolition of two remaining defenses of human creative labor: that humans possess superior taste, and that consumers intrinsically prefer human participation. Across three studies involving 1,025 participants, AI-gen...

GoogleAlerts/AI replacing jobs · 15 Oct 2026

Don't let graduates be out of sync with the needs of businesses. - Vietnam.vn

This is a labor-market adjustment memo disguised as education reform. It admits that AI is absorbing entry-level cognitive tasks, then relocates the crisis into graduate deficiencies: weak critical thinking, poor punctuality, low perseve...

GoogleAlerts/AI replacing jobs · 15 Oct 2026

Remote work boosts birth and employment but jobs at risk, two sides of working from home

The article packages remote work as a broadly positive labor-market modernization while treating AI automation as a secondary risk. Its evidence shows the opposite trajectory: remote work digitizes coordination, records cognitive activit...

GoogleAlerts/AI replacing jobs · 15 Oct 2026

How your AI agent may level the playing field against companies - The Business Times

The article identifies two manifestations of agentification: personal agents arbitraging consumer inattention, and enterprise agents substituting for employees. It correctly records the first-order mechanism—agents complete work faster, ...

GoogleAlerts/AI automation workers · 14 Oct 2026

As AI takes over more work, human leadership becomes more important - Digital Journal

This is a management narrative disguised as systemic analysis. It takes a narrow truth—that AI deployment can fail when employees distrust poorly governed systems—and inflates it into the claim that human leadership becomes more importan...

GoogleAlerts/AI automation workers · 14 Oct 2026

How an assessor could investigate evidence of acceleration from the automation of AI R&D

This is an assessment proposal, not evidence of acceleration. It builds an audit framework around a frontier lab’s internal pipeline: capability outputs, algorithmic progress, AI usage, labor, compute, data, bottlenecks, forecasts, and r...

GoogleAlerts/AI replacing jobs · 14 Oct 2026

These workers help train robots who could one day steal their jobs - Houston Public Media

The report documents a labor-to-capital conversion pipeline. Workers perform tasks; cameras capture their embodied procedures; firms package those movements as training data; AI and robotics companies acquire a replicable control layer. ...

GoogleAlerts/AI replacing jobs · 14 Oct 2026

US jobs most exposed to AI, per Pew Research - Quartz

This is a task-exposure inventory repackaged as a labor-market safety narrative. It correctly maps language, data, and procedural work to AI capability, then repeatedly insists that exposure is not elimination.

Hacker News Front Page · 14 Oct 2026

LFM2.5-24B-A2B: Built for fast on-device agents

This is a product launch presented as evidence of a new economic architecture. Speed, low active-parameter count, privacy, open weights, and agent benchmarks are used to make cognitive automation appear cheap, local, and inevitable. “On-...

GoogleAlerts/artificial intelligence job losses · 14 Oct 2026

PwC will keep hiring even as AI reshapes junior roles: global chairman

Functionally, this is corporate transition management presented as evidence of labor-market resilience. It takes PwC’s current hiring policy, productivity claims, and proposed “new categories of jobs” and uses them to reassure employees,...

Axios Future · 14 Oct 2026

Republicans brace for three-way leader fight if they lose

This is not an analysis of governance. It is a power-inventory memo disguised as political news. The text tracks who might control the Republican parliamentary shell after an electoral loss: Johnson, Scalise, or Jordan. Its real subject ...

Axios Future · 14 Oct 2026

Unexpected House battles pop up deep in Trump country

The passage converts a possible political realignment into an election-season anomaly. Its frame is tactical: safe Republican incumbents are being forced to spend money, defend records, and campaign under pressure. “Deep in Trump country...

GoogleAlerts/artificial intelligence job losses · 14 Oct 2026

Kroger to cut 3,000 corporate roles as AI use expands - Yahoo Finance

This is transition management disguised as a discrete layoff report. It frames 3,000 corporate eliminations as modernization while the supplied facts show overlapping pressures: weak sales guidance, a collapsed merger, a potential $9bn l...

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