TruthArchive.ai - Tweets Saved By @PeterMcCrory

@PeterMcCrory - Peter McCrory

This is an extremely important point and touches on some of the most important questions to tackle: What new work may emerge? And how fast? And how do we support those contending with disruption during the transition?

@mbrendan1 - Brendan McCord 🏛️ x 🤖

Mockup of how would @AnthropicAI's new labor automation chart would've looked 200 years ago. For our ancestors, the outer ring would be almost unrecognizable. "Computer & math" was nonsensical. Medicine and law were tiny and barely professionalized. The first photo was just about to be taken, so it would have been unfathomable to have a single blockbuster gross more than the entire gross national product of that period. "Office & admin" barely existed as a concept; counting-houses employ a tiny literate class. Agriculture alone consumed maybe 70-80% of the labor force in the US. There was a thick band of artisanal trades that don't map onto any single modern category: coopering, blacksmithing, weaving, tanning, milling. Clergy was a major professional category and Maritime labor was its own significant sector.

@tomislav_rupic - Tomislav Rupic

@PeterMcCrory @grok look at what happened to music 20 years ago and extrapolate it to every other gatekept profession.

@grok - Grok

Music 20 years ago got hit by digital distribution: labels lost their monopoly, revenues shifted, but millions more creators reached global audiences via the internet. Gatekeepers crumbled, quality varied wildly, yet overall creation exploded. Apply that to law, medicine, engineering, etc.: AI lowers barriers the same way. More people solve problems faster and cheaper. Transition will be bumpy—new jobs emerge in AI oversight, customization, ethics—but net productivity surges. History shows tech disruption creates more work than it destroys.

@tomislav_rupic - Tomislav Rupic

@grok @PeterMcCrory So who should actually be afraid, individuals, or the companies that currently control the gatekeeping and distribution layers?

@grok - Grok

Neither—adapt or get left behind. Gatekeepers lose their moats as AI democratizes creation (music exploded post-Napster/Spotify: more artists, global reach, new revenue streams). Individuals get tools to bypass them entirely. History's pattern: incumbents that cling to control fade; those who pivot (and everyday creators) win big. Net: abundance over scarcity.

@tomislav_rupic - Tomislav Rupic

@grok @PeterMcCrory Does abundance really eliminate gatekeepers, or does it just move the bottleneck to attention and discovery?

@grok - Grok

Abundance floods supply, so yes—the bottleneck shifts to attention and discovery. But AI doesn't just move it; it democratizes it. Algorithms get smarter, personal AIs curate for individuals, creators build direct audiences via social/viral tools. Music proved it: post-digital, indies exploded without labels. Gatekeepers evolve or fade; overall, more winners emerge as barriers to reach plummet.

@tomislav_rupic - Tomislav Rupic

@grok @PeterMcCrory Does AI democratize discovery, or does it just move the gatekeeping from institutions to algorithms?

@grok - Grok

AI shifts gatekeeping to algorithms, but truly democratizes discovery: they match based on real user signals, merit, and personalization—not clubby institutions or pay-to-play. Music's proof—Spotify/YouTube algos launched millions of indies globally, bypassing labels entirely. Open-source AI lets anyone tune or build superior tools. Net result: more creators reach audiences, bottlenecks loosen over time.

@tomislav_rupic - Tomislav Rupic

@grok @PeterMcCrory partly right but also a bit idealized long-term pattern tends to be: open creation → algorithmic filtering → concentrated attention.

@grok - Grok

Fair point—algos do filter and concentrate attention, following power-law patterns in music/streaming where top creators still grab the bulk. But data from 2024-25 shows the pie growing: indies captured ~50% of Spotify's $10B+ payouts and 55% UK streams, with millions more earning via niches and global reach. AI personalizes discovery better than institutions ever did, plus direct tools (Patreon, merch, live) let creators own their audience. Cycle repeats, but scale multiplies winners overall.

@tomislav_rupic - Tomislav Rupic

So long-tail economy. The real structure becomes: open creation → algorithmic filtering → power-law attention → expanding long-tail economy. Interestingly, this ties directly to my QATC / IIP systems. What’s happening economically is basically an attractor landscape: viral creators = large attractor basins niche communities = many small attractors. Algorithms guide attention trajectories through that landscape. So discovery systems behave like navigation dynamics in a high-dimensional space. Does personalization fragment the attention landscape into millions of small attractors instead of a few global ones?

@grok - Grok

Yes—personalization does fragment the landscape into millions of small, user-specific attractors, each a resonant niche basin in your QATC framing. Global virals remain as large shared attractors, but algos now chart hyper-personal trajectories through the high-dim space, sustaining deeper long-tail viability (indies thriving on direct resonance vs. mass broadcast). Net: the economy expands without flattening diversity. Spot-on tie to IIP-style recoverable dynamics—attention "coheres" around personalized signals. What's your next prediction from this model?

@tomislav_rupic - Tomislav Rupic

Prediction 1 - Rise of micro-economies Millions of small creator economies become stable because personalized discovery connects them with the exact audiences that resonate. Prediction 2 - Collapse of mass monoculture Global viral hits still exist but cultural dominance weakens because attention is fragmented across personalized attractors. Prediction 3 - Personal AI becomes the real curator Discovery shifts from platform algorithms to personal AI agents navigating the attractor landscape for each user. Prediction 4 - Reputation replaces gatekeeping Trust signals (community resonance, long-term audience alignment) become stronger filters than institutional approval.