2028全球智能危机

A Thought Exercise in Financial History, from the Future Preface What if our AI bullishness continues to be right...and what if that’s actually bearish? What follows is a scenario, not a prediction.This isn’t bear porn or AI doomer fan-fiction. The sole intent of this piece is modeling a scenario that’s been relativelyunderexplored. Our friend Alap Shah posed the question, and together webrainstormed the answer. We wrote this part, and he’s written two others you can findhere. Hopefully, reading this leaves you more prepared for potential left tail risks as AImakes the economy increasingly weird. This is the CitriniResearch Macro Memo from June 2028, detailing the progressionand fallout of the Global Intelligence Crisis. Macro Memo The Consequences of Abundant Intelligence CitriniResearch February 22nd, 2026June 30th, 2028 The unemployment rate printed 10.2% this morning, a 0.3% upside surprise. Themarket sold off 2% on the number, bringing the cumulative drawdown in the S&P to38% from its October 2026 highs. Traders have grown numb. Six months ago, a print like this would have triggered acircuit breaker. Two years.That’s all it took to get from “contained” and “sector-specific” to aneconomy that no longer resembles the one any of us grew up in. This quarter’s macromemo is our attempt to reconstruct the sequence - a post-mortem on the pre-crisiseconomy. The euphoria was palpable. By October 2026, the S&P 500 flirted with 8000, theNasdaq broke above 30k. The initial wave of layoffs due to human obsolescence beganin early 2026, and they did exactly what layoffs are supposed to. Margins expanded,earnings beat, stocks rallied. Record-setting corporate profits were funneled rightback into AI compute. The headline numbers were still great. Nominal GDP repeatedly printed mid-to-highsingle-digit annualized growth. Productivity was booming. Real output per hour roseat rates not seen since the 1950s, driven by AI agents that don’t sleep, take sick days orrequire health insurance. The owners of compute saw their wealth explode as labor costs vanished. Meanwhile,real wage growth collapsed. Despite the administration’s repeated boasts of recordproductivity, white-collar workers lost jobs to machines and were forced into lower-paying roles. When cracks began appearing in the consumer economy, economic punditspopularized the phrase “Ghost GDP“: output that shows up in the national accounts but never circulates through the real economy. In every way AI was exceeding expectations, and the market was AI.The only problem…theeconomy was not. It should have been clear all along that a single GPU cluster in North Dakotagenerating the output previously attributed to 10,000 white-collar workers in midtownManhattan is more economic pandemic than economic panacea. The velocity ofmoney flatlined. The human-centric consumer economy, 70% of GDP at the time,withered. We probably could have figured this out sooner if we just asked how muchmoney machines spend on discretionary goods. (Hint: it’s zero.) AI capabilities improved, companies needed fewer workers, white collar layoffsincreased, displaced workers spent less, margin pressure pushed firms to invest morein AI, AI capabilities improved… It was a negative feedback loop with no natural brake. Thehumanintelligencedisplacement spiral. White-collar workers saw their earnings power (and, rationally,their spending) structurally impaired. Their incomes were the bedrock of the $13trillion mortgage market - forcing underwriters to reassess whether prime mortgagesare still money good. Seventeen years without a real default cycle had left privates bloated with PE-backedsoftware deals that assumed ARR would remain recurring. The first wave of defaultsdue to AI disruption in mid-2027 challenged that assumption. This would have been manageable if the disruption remained contained to software,but it didn’t. By the end of 2027, it threatened every business model predicated onintermediation. Swaths of companies built on monetizing friction for humansdisintegrated. The system turned out to be one long daisy chain of correlated bets on white-collarproductivity growth. The November 2027 crash only served to accelerate all of thenegative feedback loops already in place. We’ve been waiting for “bad news is good news” for almost a year now. Thegovernment is starting to consider proposals, but public faith in the ability of thegovernment to stage any sort of rescue has dwindled. Policy response has always lagged economic reality, but lack of a comprehensive plan is now threatening toaccelerate a deflationary spiral. How It Started In late 2025, agentic coding tools took a step function jump in capability. A competent developer working with Claude Code or Codex could now replicate thecore functionality of a mid-market SaaS product in weeks. Not perfectly or with everyedge case handled, but well enough that the CIO reviewing a $500k annual renewalstarted asking the question “what