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234_026predictionAIAI-timing

AI rent-a-human service feature of scoring humor/visuals will be gone in months

Predictor: Alex Wissner-Gross · ep#234 "Anthropic vs. The Pentagon, Claude Outpaces ChatGPT, and Consulting Gets Replaced" · source

Prior probability
50.0%
Current probability
40.2%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
pending
Window
2026-01-01 – 2026-11-30
Edges in / out
7 / 5
Tickers exposed
33

Prediction text

AI rent-a-human service feature of scoring humor/visuals will be gone in months | You know, is this entertaining? Is this funny? Is this image clear? Does it have six fingers? You know, all that stuff is really really good for this service. I I think that's going to be gone in in months if it's not gone already.

Verbatim quote

From episode "Anthropic vs. The Pentagon, Claude Outpaces ChatGPT, and Consulting Gets Replaced"
You know, is this entertaining? Is this funny? Is this image clear? Does it have six fingers? You know, all that stuff is really really good for this service. I I think that's going to be gone in in months if it's not gone already.

Predictor: Alex Wissner-Gross

κ + Brier as of 2026-05-22
κ (discount)
0.844
Brier
0.0341
excellent
Hits / Misses
6 / 1
of 11 resolved
Hit rate
54.5%
Calibration plot (stated vs observed)

Evidence about this node from Alex Wissner-Gross is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).

Reference class

Not linked

This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.

Probability over time

6 prob_history rows
0%25%50%75%100%prior 50%2026-04-302026-05-072026-05-17
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 40.2%

Milestone chain

Pre-event signals (upstream prereqs + window checkpoints) → resolution event → downstream cascades. Status/dates update from linked nodes; re-derive nightly via scripts/ops/derive_milestones.py.
Leading chain: 5 fired ✓ · 1 overdue ⏱ · 1 pending
  1. 2026-02-07hitRentAHuman service launches February 2026 — humans rented by AI
    How: RentAHuman.ai goes live with >=100K signups within 30 days; AI agents hire humans for tasks AI cannot do (validates that scoring/visuals tasks are flipping in direction)
    Source: https://www.gizmochina.com/2026/02/07/humans-for-hire-this-website-lets-ai-rent-humans-for-work/ — Gizmochina launch coverageconf 95%
  2. 2026-04-29overdueOSWorld leader exceeds human baseline by 10pp
    How: Top OSWorld-Verified model achieves >=82% (vs 72.4% human baseline) — proves AI can score visual/UI tasks at superhuman level, eroding human-grading need
    Source: https://benchlm.ai/benchmarks/osWorldVerified — Holo3 leaderboardconf 85%
  3. 2026-04-01 → 2026-09-30pendingMultimodal vision/humor capability matches human-grader pass rate
    How: Frontier multimodal model achieves human-grader-parity (>=95% agreement) on visual creativity / humor scoring benchmarks
    Source: Stanford AI Index 2026 multimodal capability extrapolationconf 55%
  4. 2026-06-01 → 2026-12-31pendingMajor rent-a-human platform deprecates humor/visual scoring tasks
    How: RentAHuman.ai or competitor publicly removes 'humor scoring' or 'visual creativity scoring' SKU from task catalog due to AI substitution
    Source: Pattern extrapolation from rapid multimodal capability gainsconf 50%
  5. 2026-09-01 → 2027-06-30pendingCascade: Human-as-graders gig economy contracts >30% YoY
    How: RLHF/human-grader gig labor demand (Scale AI, Surge, etc.) declines >=30% YoY measured via posted task volume
    Source: Scale AI / Surge AI public hiring patternsconf 50%

What if this resolves?

Clamp this prediction TRUE or FALSE and run a counterfactual Gibbs sample. Surfaces the predictions whose marginals shift most under that assumption.
(live posterior: 40%)

Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"

Evidence chain

Every probability update with full Bayesian provenance — chronological, latest first
LBP2026-05-17T02:00:01Z40.2%+1.2pp
Network propagation: 39.0% → 40.2%
5-iter LBP, residual 0.00689 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e607fa96
LBP2026-05-10T02:00:02Z39.0%+2.5pp
Network propagation: 36.5% → 39.0%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
metadata_milestone_miss_sweep2026-05-07T22:13:01Z36.5%-7.0pp
metadata_milestone_miss_sweep bayesian_v2 n=1 inside=0.365 blend=0.365 LLR=-0.291 κ=0.84 no_blend
Raw metadata
{
  "trf": 0.6188417233545699,
  "kappa": 0.8438,
  "base_rate": null,
  "predictor": "Alex Wissner-Gross",
  "total_llr": -0.4054651081081644,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": -0.2626418454937682,
  "bayes_factor": "1.3:1 against",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.43471439531203065,
  "kappa_source": "predictor_table",
  "n_milestones": 1,
  "blend_applied": false,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "llm_pre_event",
      "kappa": 0.7172299999999999,
      "label": "OSWorld leader exceeds human baseline by 10pp",
      "weight": 0.4,
      "strength": "weak",
      "confidence": 0.85,
      "source_url": "https://benchlm.ai/benchmarks/osWorldVerified",
      "adjusted_llr": -0.2908117394884187,
      "expected_date": "2026-04-29",
      "measurement_criterion": "Top OSWorld-Verified model achieves >=82% (vs 72.4% human baseline) — proves AI can score visual/UI tasks at superhuman level, eroding human-grading need"
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "history_v2",
  "inside_weight": 0.566810793651801,
  "outside_weight": 0.433189206348199,
  "posterior_prob": 0.36506352268234904,
  "posterior_logit": -0.5534535849821869,
  "predictor_brier": 0.03413,
  "inside_posterior": 0.36506352268234904,
  "blended_posterior": 0.36506352268234904,
  "reference_class_id": null,
  "total_adjusted_llr": -0.2908117394884187,
  "predictor_n_resolved": 11
}
LBP2026-05-03T02:00:01Z43.5%-1.4pp
Network propagation: 44.8% → 43.5%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z44.8%-2.0pp
Network propagation: 46.8% → 44.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z46.8%-3.2pp
Network propagation: 50.0% → 46.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef

Network propagation neighbors

Top edges sorted by latest LBP cross-impact
All propagation →

Top incoming (parents)

Edges that influence THIS node's belief

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.500+0.053
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.500+0.030
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.5000.050-0.025
prereqSEM_012
Nvidia quadrupled chip production output while only doublingJensen Huang
75.0%0.5000.050-0.018
prereqSEM_008
Training runs costing $10 billion for a single model will coDario Amodei
76.9%0.5000.050-0.010

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq231_013
Math is cooked (will be solved), physics cooked, biology chaAlex Wissner-Gross
35.4%0.6200.050-0.071
prereq241_043
ASI will arrive within 2 years to 5 years to this next decadPeter Diamandis
35.9%0.6500.050-0.064
prereqCMQ_002
By 2028, AI systems will reach 'independent researcher' leveSam Altman
31.4%0.5500.050-0.060
prereq235_030
Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 203Ray Kurzweil
39.2%0.7500.050-0.057
prereq232_055
We're exiting the industrial age permanently as recursive sePeter Diamandis
35.5%0.7000.050-0.039

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (7)

Predictions that must hit first
TypePredTitleDomainLag
prereq238_009Recursive self-improvement is already happening now (no longer three years out)AI
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.AI
prereqSEM_0422025 will be the definitive year that agentic systems finally hit the mainstream.AI/Agents
prereqSEM_012Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering.AI/Manufacturing
killerTK14Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (5)

Predictions enabled by this
TypePredTitleDomainLag
prereq235_030Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 2033.Biotech/Longevity
prereq232_055We're exiting the industrial age permanently as recursive self-improvement unfolds.AI
prereq241_043ASI will arrive within 2 years to 5 years to this next decadeAI
prereq231_013Math is cooked (will be solved), physics cooked, biology char broiled.AI
prereqCMQ_002By 2028, AI systems will reach 'independent researcher' level — driving autonomous scientific discoveries without human intervention.AI

Linked documents (7)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": "months",
  "url": "https://www.youtube.com/watch?v=dmtvGKuRE64",
  "mode": "PREDICTION",
  "role": "Host",
  "context": "You know, is this entertaining? Is this funny? Is this image clear? Does it have six fingers? You know, all that stuff is really really good for this service. I I think that's going to be gone in in months if it's not gone already.",
  "to_year": 2026,
  "verbatim": "You know, is this entertaining? Is this funny? Is this image clear? Does it have six fingers? You know, all that stuff is really really good for this service. I I think that's going to be gone in in months if it's not gone already.",
  "conv_cues": "going to be gone",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "Within months",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "RentAHuman service launches February 2026 — humans rented by AI",
      "source": "https://www.gizmochina.com/2026/02/07/humans-for-hire-this-website-lets-ai-rent-humans-for-work/ — Gizmochina launch coverage",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://www.gizmochina.com/2026/02/07/humans-for-hire-this-website-lets-ai-rent-humans-for-work/",
      "expected_date": "2026-02-07",
      "observed_date": "2026-02-07",
      "research_origin": "deep_research",
      "measurement_criterion": "RentAHuman.ai goes live with >=100K signups within 30 days; AI agents hire humans for tasks AI cannot do (validates that scoring/visuals tasks are flipping in direction)"
    },
    {
      "kind": "prereq",
      "label": "Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) a",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -6,
      "source_id": "SEM_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Training runs costing $10 billion for a single model will commence sometime in 2025.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -5,
      "source_id": "SEM_008",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "2025 will be the definitive year that agentic systems finally hit the mainstream.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -4,
      "source_id": "SEM_042",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Recursive self-improvement is already happening now (no longer three years out)",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -3,
      "source_id": "238_009",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "llm_pre_event",
      "label": "OSWorld leader exceeds human baseline by 10pp",
      "source": "https://benchlm.ai/benchmarks/osWorldVerified — Holo3 leaderboard",
      "status": "overdue",
      "weight": 0.4,
      "ordinal": -2,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://benchlm.ai/benchmarks/osWorldVerified",
      "expected_date": "2026-04-29",
      "miss_emitted_at": "2026-05-07T22:13:01.009021+00:00",
      "miss_emitted_by": "metadata_milestone_sweep",
      "research_origin": "deep_research",
      "measurement_criterion": "Top OSWorld-Verified model achieves >=82% (vs 72.4% human baseline) — proves AI can score visual/UI tasks at superhuman level, eroding human-grading need"
    },
    {
      "kind": "llm_pre_event",
      "label": "Multimodal vision/humor capability matches human-grader pass rate",
      "source": "Stanford AI Index 2026 multimodal capability extrapolation",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -1,
      "source_id": null,
      "confidence": 0.55,
      "
... (truncated)