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The same evidence read against both worldviews. Each row is a published indicator; the two middle columns say what AI as Normal Technology and AI 2027 (with the lab timelines that share its premise) expect it to show, citing the sourced claims on the prediction ledger. The last column is not an opinion: it is derived from the indicator's current status. Faster than normal leans AI 2027; consistent with normal or slower leans Normal Technology; emerging, unclear or unmeasured is open.
8 lean Normal Technology · 2 lean AI 2027 · 5 open
| Indicator | Normal Technology expects | AI 2027 expects | Leans |
|---|---|---|---|
| METR 50% time horizon faster than normal17.4 h(8.5 h–55.1 h)⚑disputedas of 2026-04-07 | Capability can move fast; the paper's speed limits sit downstream of methods. A short doubling time does not contradict Normal Technology on its own. | Doubling every four months or faster from 2024, continuing to shorten, is the premise of the superhuman-coder timeline. | AI 2027 |
| METR 80% time horizon faster than normal3.1 h(1.6 h–6.6 h)as of 2026-04-07 | The 80% horizon is the number that matters for products; it should lag the 50% horizon by years because reliability fixes are application-specific. | 80% reliability on tasks taking humans years by March 2027 if the trend keeps accelerating. | AI 2027 |
| 50%/80% horizon ratio consistent with normal6.34×as of 2026-03-05(2 obs) | The capability-reliability gap stays wide (ratio of five or more); benchmarks are false summits. | The gap collapses toward two as agents become reliable enough to run unattended. | Normal Technology |
| Developer productivity uplift (METR RCTs) consistent with normal-4.0%⚑disputedas of 2026-02-24 | Modest, setting-dependent developer uplift; AI has not replaced software engineers and will not. | Broad, large uplift as coding agents take over; most of what software engineers do, end to end, within a year (Amodei). | Normal Technology |
| Enterprise pilots with measurable P&L impact consistent with normal5.0%⚑disputedas of 2025-06-30 | The proof-of-concept-to-product gap keeps most pilots from measurable P&L impact for years. | Agents that work reset the pilot economics; production share rises quickly. | Normal Technology |
| Share of work hours assisted by generative AI consistent with normal6.3%as of 2026-06-30 | Single-digit share of work hours in year three, like PCs and the web at the same age. | A fifth or more of work hours assisted as agents diffuse through white-collar work. | Normal Technology |
| US firms using AI (Census BTOS) consistent with normal22.4%(21.7%–23.1%)as of 2026-08-09 | Under a third of firms in year three; organisational speed, not capability speed. | More than half of firms as agents remove the integration cost. | Normal Technology |
| US businesses paying for AI (Ramp AI Index) emerging56.1%as of 2026-08-31 | Paid adoption saturates early among tech-forward firms and flattens as the hard integration work begins. | Paid adoption keeps rising toward universality as agents pay for themselves. | open |
| US labour productivity, year on year consistent with normal2.2%as of 2026-06-30 | Productivity at trend for years; the Solow paradox repeats (paper's entries 28, 29, 61). | Productivity prints above 3.5% sustained as automation compounds. | Normal Technology |
| US total factor productivity, private nonfarm business consistent with normal0.8%as of 2025-12-31(2 obs) | TFP invisible at annual resolution; Acemoglu's 0.66% over a decade is the normal reading. | TFP a point or more above trend by the late 2020s. | Normal Technology |
| US labour share of income, year on year emerging-3.4%as of 2026-06-30(2 obs) | Labour share moves within its cyclical range; no AI-attributable break before 2028. | Labour share falls from about 60% toward 45% by 2030 on the extreme path. | open |
| Entry-level employment shortfall in AI-exposed occupations emerging19.0%as of 2026-06-30 | No broad AI-attributable employment decline for years; canaries stay within youth-employment swings. | Entry-level exposed employment breaks first and keeps widening. | open |
| Cross-tracker concordance (labour) consistent with normal0as of 2026-07-31(4 obs) | The four monthly labour trackers agree on a null. | The trackers converge on a decline in exposed occupations. | Normal Technology |
| Agent-workdays per human workday in frontier research (self-reported) emerging3.10×as of 2026-08-15 | Agent effort inside labs can rise without escaping external bottlenecks; self-reports do not resolve the question. | Agent effort passes human effort inside labs by 2026 and the R&D multiplier compounds from there. | open |
| Human interventions on 4–8 hour agent tasks (self-reported) emerging50.0%as of 2026-07-31 | Humans keep steering most long agent runs; unreliability compounds over steps (entry 4). | Long runs go unattended as reliability catches up; intervention rates fall below a quarter. | open |
Rows are the diffusion-lens indicators both worldviews make claims about. Capture-lens indicators (who keeps the surplus) are scored on the prediction ledger under the capture theses.