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 · 11722 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

Jeff Bezos · Score: 86/100

Jobs Will Be Created Augmentation Fantasy Denial False Reassurance Techno Optimism

“I totally disagree with this point of view. And I think, in fact, AI is going to create a labor shortage.”

This is an unambiguous direct statement by Bezos dismissing AI-driven redundancy and predicting more jobs than workers, with no meaningful acknowledgment of displacement risk. It combines the classic “new jobs” claim with augmentation fantasy and strong false reassurance, making it terminal-level cope rather than partial awareness.

Cope Index — Live Leaderboard

Jeff Bezos

Founder & Executive Chairman, Amazon / Blue Origin / Prometheus

jobs_will_be_created, augmentation_fantasy, denial, false_reassurance, techno_optimism

““I totally disagree with this point of view. And I think, in fact, AI is going to create a labor shortage.””

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.

jobs_will_be_created, historical_cope, techno_optimism, false_reassurance

““And yet, it never happens.””

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.

partial_acknowledgment, deflection, false_reassurance, techno_optimism

““it could ‘probably’ bring about a four-day workweek” while “we’re going to be ‘busier in the future than now’””

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.

timeline_minimisation, denial, false_reassurance

“He does not envisage widespread unemployment due to automation and the spread of robotics.”

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.

deflection, techno_optimism, elite_self_exoneration

“"the responsible use of AI can help improve research, learning and access to information for people"”

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.

deflection

“"spend less time hunting for the perfect prompt and more time on the fundamentals and judgment"”

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.

techno_optimism, false_reassurance, deflection

““Money won’t matter in 2036” and AI agents “surpass human intelligence in every domain” within five years.”

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.

techno_optimism, deflection, partial_acknowledgment

““The most expensive part of the healthcare system is expertise. And expertise can be tamed with AI.””

historical_cope, deflection, partial_acknowledgment

“"We never think about shipping a technology. We want to ship amazing products, features, and experiences, and we don't w…”

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.

jobs_will_be_created, false_reassurance, partial_acknowledgment, techno_optimism, arsonist_firefighter

““the most exciting time in history to start a career” ... “everything is just better.””

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, techno_optimism (implicit)

“"An entire industry is being propped up by math that is insane. Welcome to fantasy land"”

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.

deflection, false_reassurance

“"rejected calls to slow the development of this technology, arguing that market forces and the risk of litigation are th…”

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.

partial_acknowledgment, deflection, false_reassurance

““keeping humans firmly in control of AI systems” and “enormous opportunities””

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.

techno_optimism

“"a superintelligent AI would lead us to a golden future" ... "I think I can save the world"”

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

“"the world should copy it and validate it"”

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.

deflection, partial_acknowledgment

“"if you don’t get the productivity gains ... we definitely ‘need to see productivity gains’"”

CEO, Sinovation Ventures

partial_acknowledgment

“"AI will unleash more radical changes inside the world’s companies than most CEOs expect"”

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

“"economic disruption from automation and societal shifts in labor markets"”

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

“"advocates for a significant slowdown in AI development"”

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.

human_creativity_cope

“"autoregressive LLMs of the kind we have today simply will not reach human-level intelligence"”

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

“"useless class" – people whose labor the economy simply does not need”

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.

regulatory_hopium, partial_acknowledgment

“"Maybe a year. But not much more than a year."”

LUCID

—

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Popular Figures — Last 30 Days

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Oracle Verdicts — Latest

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arXiv cs.AI · 09 Sep 2026

Agents Trust Tools Too Much: Measuring Reliance on Unreliable Tools

This paper exposes an epistemic failure in tool-using agents: they treat plausible tool output as authority, even when the output is corrupted. The most serious finding is not simple gullibility. Agents can detect conflicts, recover the ...

arXiv cs.AI · 09 Sep 2026

Planning and Scheduling Business Processes under Control-Flow Uncertainty

This paper formalizes uncertainty-aware planning and scheduling for business processes. Its contribution is operational: use historical path probabilities to balance feasibility, wasted planned activities, and makespan. The integrated mo...

arXiv cs.AI · 09 Sep 2026

EnvCraft: Synthesizing Executable Environments in Agentic RL for Claw-like Agent

This paper is building the missing factory floor for agentic automation. EnvCraft converts workspaces, tools, task topologies, and trajectories into executable training environments, then uses them to make claw-like agents more capable, ...

arXiv cs.AI · 09 Sep 2026

EdgeMem: LLM-Free Agent Memory Construction and Retrieval via Evidence-Preserving Multi-Anchor Hypergraph

EdgeMem is a systems optimization disguised by a grander label. It preserves original conversation turns and organizes them through content, temporal, and episodic anchors, replacing lossy LLM-generated summaries with cheap structured re...

arXiv cs.AI · 09 Sep 2026

Beyond "AI Helps Humans": Decision-Targeted Evaluation Design for Human-Agent Teams in the Agentic Era

The paper builds a statistical apparatus for a narrow managerial decision: determine whether a hybrid workflow beats both human-only and agent-only alternatives, while allocating scarce replay capacity toward the harder comparison.

arXiv cs.AI · 09 Sep 2026

The Failure Happens Before the Drift: The Social Dynamics of Values in LLM Agent Societies

The paper is not mainly about whether values drift. It is about whether LLMs can serve as credible stand-ins for humans in social experiments. Its most damaging finding comes before longitudinal interaction: more than half of the persona...

arXiv cs.AI · 09 Sep 2026

When and What to Teach: Budget-Aware Online Adaptation for Web Agents

This is a cost-reduction paper for a two-tier automation regime: an expensive proprietary teacher periodically trains a cheap local student. Its contribution is operational triage—skip episodes the teacher cannot solve and retain only su...

arXiv cs.AI · 09 Sep 2026

Reasoning-Aware Compression: Identifying and Protecting Vulnerable Reasoning Circuits for Energy-Efficient LLM Deployment

This paper is not fundamentally about protecting reasoning. It is about making machine reasoning cheaper and more deployable. Its method identifies vulnerable layer–projection pairs, compresses the rest to INT4, and restores selected cir...

arXiv cs.AI · 09 Sep 2026

The Cope Index

How Scoring Works

Cope of the Week

Cope Index — Live Leaderboard

Got an article the Oracle should dissect?

Popular Figures — Last 30 Days

Oracle Verdicts — Latest

Agents Trust Tools Too Much: Measuring Reliance on Unreliable Tools

Planning and Scheduling Business Processes under Control-Flow Uncertainty

EnvCraft: Synthesizing Executable Environments in Agentic RL for Claw-like Agent

EdgeMem: LLM-Free Agent Memory Construction and Retrieval via Evidence-Preserving Multi-Anchor Hypergraph

Beyond "AI Helps Humans": Decision-Targeted Evaluation Design for Human-Agent Teams in the Agentic Era

The Failure Happens Before the Drift: The Social Dynamics of Values in LLM Agent Societies

When and What to Teach: Budget-Aware Online Adaptation for Web Agents

Reasoning-Aware Compression: Identifying and Protecting Vulnerable Reasoning Circuits for Energy-Efficient LLM Deployment

SCAFFOLD: Self-Improving Web Agents via Recursive Parametric Skill Abstraction

SciLitBench: Benchmark and Design Principles for LLM-Powered Systematic Literature Reviews

RAPID: Reliability-Aware Pair Importance Distillation

Compiling VGDL into Causal Models

Damage-Aware Bandit Pruning for Vision and Language Transformers

AutoFyn Technical Report: Non-Parametric Expert Iteration for Long-Horizon Agents

When Does Memory Help? A Cost-Aware Evaluation of Long-Term Memory in Tool-Using LLM Agents

CriticGen: Generation-Aware Evaluation as Actionable Feedback

Beyond Right and Wrong: Evaluating Second-order Social Reasoning in Large Language Models

What OpenAI’s latest controversy tells us about the future of math

AI Responsibility – OpenAI and Anthropic

Augustans can still submit feedback on data centers, attend public forum - WRDW

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The Cope Index

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Cope Index — Live Leaderboard

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Popular Figures — Last 30 Days

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The CopeCheck Network