{
  "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": 91,
  "pageCount": 163,
  "prevPage": 90,
  "nextPage": 92,
  "slideType": "case_study",
  "function": "illustrate_case",
  "density": "dense",
  "nDataPoints": 4,
  "notes": "The slide presents two charts (A and B) showing the treatment effect of ChatGPT on time taken and output quality compared to a control group.",
  "elementsJson": [
    "headline_text",
    "paragraph",
    "line_chart"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5e88-73ef-bd5d-06b04d219fea/91",
  "deckHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea",
  "deckJsonHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea.json",
  "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd5d-06b04d219fea#slide-91",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "Specifically, for “mid-level professional writing” the study showed that, compared to a control group, workers using ChatGPT took 40% less time to complete their task, and the output quality was measured to be 18% better.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd952-47c4-7719-a229-9aeb3f5a1d14",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.45,
        "w": 0.45,
        "x": 0.05,
        "y": 0.45
      },
      "kind": "chart",
      "text": "A Time Taken Decreases",
      "attrs": null,
      "subkind": "line",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "7a01fd63-28a3-4d01-8c02-c5e62a440b5c",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.45,
        "w": 0.45,
        "x": 0.52,
        "y": 0.45
      },
      "kind": "chart",
      "text": "B Average Grades Increase",
      "attrs": null,
      "subkind": "line",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "d61720c9-7671-4037-9204-6f5efe780766",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": null,
      "kind": "metric",
      "text": "Time taken: 40%",
      "attrs": null,
      "subkind": "primary",
      "toolName": "Quantification",
      "toolSlug": "quantification",
      "confidence": null,
      "componentId": "019dd952-47c4-7719-a229-9e207ed56ce5",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.9,
        "x": 0.05,
        "y": 0.2
      },
      "kind": "paragraph",
      "text": "A new MIT study supports popular wisdom: ChatGPT helps with writing. Specifically, for “mid-level professional writing” the study showed that, compared to a control group, workers using ChatGPT took 40% less time to complete their task, and the output quality was measured to be 18% better.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "c6821e5a-2788-46d9-8c2b-7b9831acbb9e",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.04,
        "w": 0.5,
        "x": 0.05,
        "y": 0.14
      },
      "kind": "title",
      "text": "ChatGPT drives productivity in (repetitive, boring?) writing",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "29187deb-3cc6-4469-a207-9efcf9f209e0",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "AIDA Model",
      "slug": "aida-model",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "1ae95f38-a6b1-4915-a44e-aad26e4202df",
      "evidence": "The components show a clear structure of problem agitation solution which is a key component of the AIDA model.",
      "confidence": 0.7
    },
    {
      "name": "Before/after framing",
      "slug": "before-after-framing",
      "agent": null,
      "layer": "slide",
      "matchId": "e17541c3-fd42-4718-b5e4-68e818bdfb4f",
      "evidence": "The slide presents a comparison of time taken and output quality with and without ChatGPT, which is a classic before-after framing.",
      "confidence": 0.7
    }
  ],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 120,
      "from": 11,
      "beatId": "019dd95a-0682-776c-8e35-41afd44ef59f",
      "arcName": "The Triple Take",
      "arcSlug": "triple-take",
      "beatName": "The Facts (What)",
      "beatSlug": "triple-take-the-facts-what",
      "evidence": "Research + Industry sections inventory model, compute, funding facts.",
      "position": 1,
      "confidence": 78,
      "parentBeatName": "Setup",
      "parentBeatSlug": "setup"
    },
    {
      "to": 120,
      "from": 11,
      "beatId": "019dd95a-0682-776c-8e35-523bfb7f96e6",
      "arcName": "The Mountain",
      "arcSlug": "mountain",
      "beatName": "Rising Action",
      "beatSlug": "mountain-rising-action",
      "evidence": "Escalating capabilities, compute concentration and capital flows.",
      "position": 2,
      "confidence": 45,
      "parentBeatName": "Development",
      "parentBeatSlug": "development"
    }
  ],
  "loops": [
    {
      "to": 94,
      "from": 84,
      "name": "Pattern Hunter",
      "slug": "02-pattern-hunter",
      "bestFor": "Time-pressed audiences, building consensus, when data is strong",
      "matchId": "019dd95a-07fe-70ce-8d3e-019bce66e7b5",
      "evidence": "ChatGPT scale, Chegg hit, Copilot productivity, then a counter-data slide on retention shortfalls.",
      "position": 9,
      "objective": "GenAI consumer and prosumer apps explode but retention is fragile",
      "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion",
      "confidence": 70,
      "description": "Group multiple pieces of evidence that together point to a pattern or conclusion"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}