{
  "docId": "019dd923-5e88-73ef-bd5d-06b04d219fea",
  "docSlug": "dd91c78f6570bf29",
  "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
  "authorId": "AirStreetCapital",
  "authorName": "Air Street Capital",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "vc_research",
  "sourceTypeLabel": "VC research",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.777,
  "pageNumber": 136,
  "pageCount": 163,
  "prevPage": 135,
  "nextPage": 137,
  "slideType": "industry_trends",
  "function": "summarize",
  "density": "dense",
  "nDataPoints": 1,
  "notes": "Slide from State of AI 2023 report.",
  "elementsJson": [
    "headline_text",
    "bullet_list",
    "paragraph",
    "other"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/136",
  "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
  "deckJsonHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea.json",
  "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-136",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "The unanswered question is whether these initiatives can be translated from interesting experiments into practice institutions can adopt.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd952-47c4-7719-a22e-f56ddf9a6258",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.2,
        "w": 0.28,
        "x": 0.69,
        "y": 0.4
      },
      "kind": "image",
      "text": "RECURSIVE PUBLIC",
      "attrs": null,
      "subkind": "logo",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "703a1f76-8464-47b7-96d6-ee91af2957ec",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.55,
        "w": 0.65,
        "x": 0.05,
        "y": 0.32
      },
      "kind": "list",
      "text": "In May, OpenAI's non-profit arm unveiled a $100,000 scheme to fund experiments designed to foster democratic inputs into AI development.\nOne grant has been awarded to Recursive Public, a joint initiative of vTaiwan and Chatham House, which aims to bring together the AI experts, policymakers, and the public for a series of focused discussions. Meta are similarly running their own public consultations around generative AI and policy.\nFlipping the question on its head, Anthropic and DeepMind have looked at the potential of AI to improve democratic deliberation, finding that LLMs are better at finding consensus among groups of people and moderating conversations about challenging issues.\nThe unanswered question is whether these initiatives can be translated from interesting experiments into practice institutions can adopt.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "0ccaad43-93c6-4e98-935f-8783ffa33d3c",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.08,
        "w": 0.9,
        "x": 0.05,
        "y": 0.22
      },
      "kind": "paragraph",
      "text": "As interest in alignment grows, interest in whose values we should be aligning to increase. This year, many of the big labs have been experimenting with ways of involving the public in some of these questions.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "aff3ce52-1855-4b88-a8e0-13237630199a",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.6,
        "x": 0.05,
        "y": 0.14
      },
      "kind": "title",
      "text": "Could democratic involvement defuse challenging values questions?",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "cc18c36e-ef2a-4b15-9bd2-8e1d9d24437c",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Audience frame",
      "slug": "audience-frame",
      "agent": null,
      "layer": "slide",
      "matchId": "bcd28f1c-078b-48e8-84c6-b04abde910eb",
      "evidence": "The unanswered question is whether these initiatives can be translated from interesting experiments into practice institutions can adopt.",
      "confidence": 0.7
    },
    {
      "name": "Problem Statement Canvas",
      "slug": "problem-statement-canvas",
      "agent": "Architect",
      "layer": "slide",
      "matchId": "7639c515-69f4-4a22-9fc2-4006bb46dc68",
      "evidence": "In May, OpenAI's non-profit arm unveiled a $100,000 scheme to fund experiments designed to foster democratic inputs into AI development.",
      "confidence": 0.6
    }
  ],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 155,
      "from": 121,
      "beatId": "019dd95a-0682-776c-8e35-478c8c58938c",
      "arcName": "The Triple Take",
      "arcSlug": "triple-take",
      "beatName": "The Implications (So What)",
      "beatSlug": "triple-take-the-implications-so-what",
      "evidence": "Politics + Safety sections explore regulatory, geopolitical and risk implications.",
      "position": 2,
      "confidence": 78,
      "parentBeatName": "Reflection",
      "parentBeatSlug": "reflection"
    },
    {
      "to": 155,
      "from": 121,
      "beatId": "019dd95a-0682-776c-8e35-554ec1797b3a",
      "arcName": "The Mountain",
      "arcSlug": "mountain",
      "beatName": "Climax",
      "beatSlug": "mountain-climax",
      "evidence": "Regulatory divergence and the x-risk debate erupt into the mainstream.",
      "position": 3,
      "confidence": 45,
      "parentBeatName": "Turn",
      "parentBeatSlug": "turn"
    }
  ],
  "loops": [
    {
      "to": 137,
      "from": 128,
      "name": "Pattern Hunter",
      "slug": "02-pattern-hunter",
      "bestFor": "Time-pressed audiences, building consensus, when data is strong",
      "matchId": "019dd95a-07fe-70ce-8d3e-12b34e44efca",
      "evidence": "Chip wars, Huawei, government compute, defense funding, Ukraine, elections, culture wars, jobs.",
      "position": 13,
      "objective": "Sketch the geopolitical contest over chips, defense and elections",
      "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
      "confidence": 65,
      "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}