Way more positive change coming from AI than negative change, at much more rapid rate.

Way more positive change coming from AI than negative change, at much more rapid rate. | there's way more positive change coming than uh than negative change at a much more rapid rate.

there's way more positive change coming than uh than negative change at a much more rapid rate.

Beneficiaries (23)

Adverse (6)

{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=C1GLT9_tag0",
  "mode": "THESIS",
  "role": "Guest-VC",
  "context": "I feel like there's way more positive change coming than uh than negative change at a much more rapid rate.",
  "to_year": 2031,
  "verbatim": "there's way more positive change coming than uh than negative change at a much more rapid rate.",
  "conv_cues": "I feel like",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "unspecified future",
  "conv_level": "MEDIUM",
  "milestones": [
    {
      "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": -10,
      "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": -9,
      "source_id": "SEM_008",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Anthropic revenue will cross OpenAI revenue in middle of 2026",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -8,
      "source_id": "234_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Anthropic will exceed OpenAI in revenue this year (2026).",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -7,
      "source_id": "235_002",
      "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": -6,
      "source_id": "SEM_042",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "llm_pre_event",
      "label": "Anthropic Economic Index or BLS-published AI labor study shows net welfare gain",
      "source": "Anthropic labor-market research framework + BLS AI projections provide measurement infrastructure",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.4,
      "source_url": "https://www.anthropic.com/research/labor-market-impacts",
      "expected_date": "2027-06-16",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2028-06-30",
        "from": "2026-06-01"
      },
      "measurement_criterion": "Anthropic Economic Index, BLS Monthly Labor Review, or peer-reviewed paper concludes aggregate welfare/productivity gain from AI exceeds aggregate displacement losses with quantified bounds (e.g., +1% GDP vs -0.6pp employment)"
    },
    {
      "kind": "llm_pre_event",
      "label": "AI-driven scientific discoveries: >=3 Nature/Science papers in 2027 with AI as primary discovery method",
      "source": "Building on AlphaFold/AlphaMissense pattern; cumulative count is positive-change rate proxy",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.85,
      "expected_date": "2027-06-16",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2027-12-31",
        "from": "2026-12-01"
      },
      "measurement_criterion": "Three or more Nature/Science publications in 2027 in which AI system (named, documented) is principal driver of novel finding (vs assistive tool); positive examples like AlphaFold, materials discovery"
    },
    {
      "kind": "llm_post_event",
      "label": "AI-attributable harms: aggregate reported AI-caused fatalities, mass-disinformation events, fraud losses",
      "notes": "Quantifies the negative side of the positive vs negativ
... (truncated)